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calculet-npu-research-archive/history/llama.cpp/topics/03-performance-profiling.tsv
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1fd9bd632f346085920d523dd307a3e4c11cc0a05e08e473cf292ba73789769b993bb35bcdfc316892026-06-01T14:15:35+08:00wangbomengHEAD -> dev, origin/devllama-bench: fix device-info
2e08e473cf292ba73789769b993bb35bcdfc31689f86112d6758298241ab2fa84ad4f0f7b1ace35c62026-06-01T11:47:01+08:00wangbomengllama-bench:add device-info
3ebce9e1a548c2329aa97f53b8b2ad50d968088dce850ff4de25ad1221abc9bf3bb30df252ccd9c362026-05-27T09:38:00+08:00Yunzhe Jiaorigin/runtime_replaceRefactor cal-llm integration by removing runtime capacity loading and adjusting request handling
4e850ff4de25ad1221abc9bf3bb30df252ccd9c369985688f7fa96f755882f96a2cd8a18114fdc42d2026-05-26T10:59:45+08:00Yunzhe JiaEnhance cal-llm integration by adding runtime checks for CALRT_LIBRARY and updating link settings for Linux and Windows
538ca6895815671a87ceec86b4aa4eb976580ce76ddd60c928224b52eb4e1e60e01e8a1ecbb80ee452026-05-20T16:37:13+08:00Yunzhe JiaAdd support for cal-llm profile dumping to JSONL file
62716130010c58f1cdd9d94f0e2f8e047bc92dc66b35bda124ccd4ed581dd6088d3ffa4931c2809b62026-05-18T08:40:54+08:00Yunzhe Jiafix n_ctx_slot error by adding runtime capacity loading for cal-llm
7a43741244a646d3f8fa3ff01bb9b7d059223d0a5b2003d6c90ef0fa26ab9e930ba3e22b355eb3d392026-05-15T14:39:53+08:00wangbomengrun llama-passkey successfully, fix llama-bench, copy 3 times input to infer qwen2.5vl
81bec0db5a675ddc60fb793be2a746e8f3c8855dc465df20c3e1f3f58d0f5531c796e0941a49c32b02026-04-30T16:02:59+08:00wangbomengorigin/dev-benbench: support 2 calbins
9eeeef3f6d6a5aad9296323ca15d9d929745b8932431ad6f1c787f1b47e9e7be14b2e1a7d8565485c2026-04-28T16:16:19+08:00wangbomengadd unknown time info: prefill and decode
10a2d5bf362d6c9a546f9deadf4f8975605a915d33bd3a57a11aa008e0b5dc2a30f82fcd3a025872082026-04-09T21:01:46+08:00Bomeng Wangserver: comment fixed time
1118814f9bf1a423ebe8f32d6043c9cbc5b21b0218bbee06d6d851e3f84f75b578047967d7e0e4a8dc2026-04-08T13:55:52+08:00wangbomengserver : reset inference time
12bbee06d6d851e3f84f75b578047967d7e0e4a8dce126c21ed7b793b648d63533ea7ee30885f5a82a2026-04-08T11:29:36+08:00wangbomengcalrt: add test time print
131e8a16cd0e3ad3c9a0f8746852a0a38c6e52322e893e52bda0fee99bbda1521ea733a760bc4201f12026-04-01T10:14:22+08:00wangbomengcalrt: fix slice and add infer/copy time
1498e8f9acfe87cd93646482cb2d942b8a132f08528c8152a04036bb0d4756a4e08e54f514dae4e64d2025-12-10T00:20:57+08:00Yunzhe Jiaadd timestamp
155d2387931528fbe04aa8d66de935147efb65ca4de6285a748657add8d974b78ca920c5b41753ee122025-12-08T16:40:34+08:00Yunzhe Jiaadd timestamp for one decode process
167e994168b1ccc12337ba8de939c4fd466107c1fbbcfa87622ae46be6345a8e3dfdbdc5ba5414042b2025-11-03T03:35:33+02:00shani-fSYCL: optimized repeat_back kernel (3× fewer asm instructions, 2× faster)Feature/sycl repeat back opt (#16869)
177fd205a8e8832ead273f62c5fd81d2b8aa9105352f68ce7cfd20e9e7098514bf730e5389b7bba9082025-11-02T00:15:31+02:00Georgi Gerganovscripts : add script to bench models (#16894)
18d261223d24e97f2df50220e4a5b7f0adb69bba81dcca0d3ab840ebe9b2ccd4719033d408eeb758d72025-10-30T23:19:14+08:00JJJYmmmmodel: add support for qwen3vl series (#16780)
198b11deea4663f29d3e042ce1056ba643264cd5f1b9ce94017729465895402cbcfffb51fa926c15e32025-10-30T04:34:15+01:00Oliver SimonsHide latency of bias and gate-loading (#16847)
20b9ce94017729465895402cbcfffb51fa926c15e33464bdac37027c5e9661621fc75ffcef3c19c6ef2025-10-29T15:13:10-05:00Jeff Bolzvulkan: Fuse rope+set_rows (#16769)
213eb2be1ca5f37480aeb16102970d9e65f43347fee41bcce8f0b53032a1fed275cd253e931c041cf62025-10-29T06:29:12-07:00Max KrasnyanskyHexagon Op queue & dispatch optimizations (#16820)
22f549b0007dbdd683215820f7229ce180a12b191d9a3ea685b937c0f0cbfda2e50004ea54bf1875122025-10-29T03:53:04-05:00Jeff Bolzvulkan: Call ggml_vk_buffer_write_2d from ggml_vk_buffer_copy (#16793)
23338074c383c81366320d176d83b94b0a567ee0c2851553ea6b24cb39fd5fd188b437d777cb411de82025-10-29T08:14:39+02:00YaelLogicsycl: add RMS_NORM_BACK operation support (#16808)
24a8ca18b4b815a2abdbecb958ee5f4c542d69aac78284efc35c909217ee1b9a06903245d808ac22832025-10-28T19:41:43+02:00Georgi Gerganovllama-bench : clarify benchmarked parts of the computation (#16823)
25ad8d36beffd791db10c94eb9e964afb891e3ca55c053e18a66dd95dc340aa61317877c2a41d4e3cf2025-10-28T03:50:33+02:00tamarPalsycl: add SSM_CONV operation support (#16800)
268423d019318b446640bb620e4ce80066d8530f055cca2542ac3f3f86831d32bce744d08fc2b353b02025-10-25T00:04:12-05:00Jeff Bolzvulkan: Optimize SSM_SCAN (#16645)
2763d2fc46e17a06be5b4b5823a5ada088317f1f0aa2e0088d9242bd9e57f8b852b05a6e47843b5a452025-10-22T13:47:09-07:00Max KrasnyanskyAdd experimental ggml-hexagon backend for the Hexagon NPU (#16547)
289b9201f65a22c02cee8e300f58f480a58859122719a5a3edfd306516cc419679d69d6435943b68162025-10-22T16:58:23+02:00Pascalwebui: introduce OpenAI-compatible model selector in JSON payload (#16562)
296ea37f57391d27736c35cd3c20c1f990b7952b74fb349848f387f355450c3187556e71e6d32c145f2025-10-20T22:26:17-07:00lhezopencl: fix warnings and clean up profiling (#16688)
3084bf3c677857279037adf67cdcfd89eaa4ca9281c9c1972e2c2cc6a771fcc145bfa138700179f9612025-10-20T21:38:20+02:00Sigbjørn Skjæretmodel : add BailingMoeV2 support (#16063)
319ad4f1931ee0f3b41d9355245ef744786aaae0aa79967ec596c0dacfd2251b085a57e79df292b1cc2025-10-17T02:33:58-04:00Ilia Ilmermetal : add `CONV_TRANSPOSE_2D` (#16542)
32ceff6bb253dd306f5404d7ccb3f11fadafe71b521bb4f43380944e94c9a86e305789ba103f5e62bd2025-10-17T05:36:40+03:00GittyBursteinSYCL SET operator optimized for F32 tensors (#16350)
33adc9b60f190c1016a09f439862fa1cbb302262acee50ee1eadff58777ae746827b04de7ba0befc552025-10-16T13:10:32+08:00takuya kodamaggml-cpu: replace putenv with setenv for const-correctness (#16573)
34f4ce81c45e7bd910e36bf44c253fc5255c49b1e417304cbcc1dd24de7741cbe57925d58e90a98ac12025-10-15T23:05:56+09:00Sam/Samuelmetal: optimise `GGML_OP_SUM` (#16559)
357ea15bb64c81e3813eb0babf9a57e1bc5697f5699c7185dd28416cf67f5e3b268381f311b5e3da562025-10-14T07:51:36-05:00Jeff Bolzvulkan: Improve build time for MSVC (#16545)
3656fc38b9655fbe1869d8bd6cfb269418196cea691fb9504eb744969a990bfe4cfcf1d3d7a479541c2025-10-13T17:01:24+08:00Chenguang LiCANN: fix CPU memory leak in CANN backend (#16549)
371fb9504eb744969a990bfe4cfcf1d3d7a479541c3f750f8d760ab5a61491e6a9409072dfeee4b4d72025-10-13T10:55:32+02:00Pascalfix: add remark plugin to render raw HTML as literal text (#16505)
38f9bc66c3ebcfddb5f09e4b21253623caeb8e414aa31cf36ad946a13b3a646bf0dadf2a481e89f9442025-10-13T08:52:22+08:00hipuddingCANN: Update several operators to support FP16 data format (#16251)
39a2fba89a426ff8005d303c73f0436e7e67368b7020cc625edc2264aae2779e71bef1593e6a4e8c432025-10-12T07:19:06+02:00Daniel Beveniushparams : add check for layer index in is_recurrent (#16511)
4031d0ff1869aa2ea31f4e96d5877d0343e9a2171b97870e64975b26c5e06a3540a8dc0ff601351e862025-10-11T21:39:04+08:00Yann Folletserver / ranking : add sorting and management of top_n (#16403)
411deee0f8d494981c32597dca8b5f8696d399b0f2d00cbea63c671cd85a57adaa50abf60b3b87d86f2025-10-09T22:11:15+03:00dudutacpu : optimize the ggml NORM operation (#15953)
4274b8fc17f92ada295a648e3c5eb28f46bca7d892aeaf8a36f06b5810f5ae4bbefe26edb33925cf5e2025-10-07T13:48:56-07:00Reese Levineggml webgpu: profiling, CI updates, reworking of command submission (#16452)
438ae32dc9ecd7aeebf3a5b43557e0552a0a04cd4f3df2244df40c67dfd6ad548b40ccc507a066af2b2025-10-07T08:21:40+03:00Georgi Gerganovmetal : various optimizations + refactoring (#16446)
4404e632a4aab8e6bfff0f8bc216b36ceb1e199ff9a80ff183abe4e5a76316257ffa597da41b3b6fa02025-10-06T14:56:59+02:00Daniel Beveniusci : remove missing reranker model files (#16444)
45ca71fb9b368e3db96e028f80c4c9df6b6b370edd35266573b968e1c947b367782fb4b3eddbb4f3c02025-10-05T06:57:47-06:00Gabe Goodhartmodel : Granite docling + Idefics3 preprocessing (SmolVLM) (#16206)
46898acba6816ad23b6a9491347d30e7570bffadfde29acf74fea996014380d59d31aa504ae89642582025-10-04T12:49:16+03:00Radoslav Gerganovrpc : add support for multiple devices (#16276)
47e29acf74fea996014380d59d31aa504ae8964258128d522c04286e019666bd6ee4d18e3fbf8772e22025-10-04T11:42:56+02:00Aclyvulkan : incremental shader builds (#16341)
48ef07a4090672a3438d7f64f197795d7dc1c1895734fcc5a4ace8c69476ef2ea3857f39a60334acc42025-10-02T11:00:31-07:00Reese Levineggml webgpu: add support for soft_max, optimize rms_norm (#16357)
4934fcc5a4ace8c69476ef2ea3857f39a60334acc491a2a5655658bb9ab77894716b82fae7ecb4b4d12025-10-02T19:43:22+02:00Piotr Wilkin (ilintar)model : Apertus model implementation (#15852)
50364a7a6d4a786e98947c8a90430ea581213c0ba92df5bcf357dba0c49b4df1d684b2ffc9e88b70542025-09-30T16:39:44+02:00Adrien Gallouëtcommon : remove common_has_curl() (#16351)
516a2c6145a0b91b40eb3c3dba7b20ccc4b270490f3b53634fe35771e2e318227aa81585726bae72342025-09-28T09:34:44+03:00Georgi Gerganovmetal : extend mat-mat multiplication support (#16225)
52e6d65fb02d553bd79cad94e517cdca18b687788d8656f5de688cddcaea1d6174535eb60ee23ef6a02025-09-27T16:43:39-04:00Jeff Bolzvulkan: support arbitrary KV dimension in flash attention (#16160)
531a189278944d030211f336e103e96b65f976c361e0539eb6aed346d4b25a6ea019044e88771e76902025-09-26T18:35:42+02:00Aleksander GrygierAllow viewing conversations even when llama server is down (#16255)
549b26511857ac09ae69ab485168fe2d3ee5fb1d6e00217cd41388328c93e9e9644921c4319bb03bcc2025-09-26T18:27:25+08:00Aaron Teoggml-cpu: implement MXFP4 SIMD for s390x (#16193)
55077c94d0caf87fbd3cf3288dbb5c0fd9670294cfaa3ee0eb0b80efca126cedf9bcb4fb5864b46ce32025-09-25T22:35:05+08:00Aman GuptaCUDA: add a fused top-K MoE kernel (#16130)
5602a6a82ae7c7ddd1819ae26b0cc36675879aeceec498fc82fe5b83fc8c6e1627286bdc1f93caddbf2025-09-25T11:29:08+03:00Georgi Gerganovmetal : restore im2col perf (#16219)
57bee378e0988b44bbe93b0768208080951b3123635fb557653b8756ac2b6c6a102b1e44abcadf552f2025-09-25T05:06:06ZEveci: run the x64 and arm ci on the github machines instead (#16183)
58f2a789e33490deb483a2694b066b37e45524bb793a599719673c850647e3bb911ed6d91109bb91d22025-09-24T16:17:49+02:00Aclyggml : split graph allocations according to backend max buffer size (#15815)
593a599719673c850647e3bb911ed6d91109bb91d263b54c81a620981be020184ab99e63a8e50e47cb2025-09-24T13:42:26+02:00Tarek Dakhranmodel : add label for LiquidAI LFM2-2.6B model (#16204)
60351f3da39c85f59d581fc184f09283da7f099a3b3ecb2f671a2f49d56357f99d135a94e8417591782025-09-23T01:57:46+08:00Haiyue Wangclang-tidy : disable warning about performance enum size (#16127)
614d0a7cbc617e384fc355077a304c883b5c7d4fb69073a73d82a916cea0809de225ef5175c3a86e912025-09-22T08:31:40+03:00Georgi Gerganovci : adjust params for less runtime (#16167)
621eeb523c3e0c7ffbd59469f5463dcbdecba3535e5bb4a3edec297e74b0f7bd4ed5d0fdd12e28d8582025-09-21T08:31:55+02:00Giuseppe Scrivanovulkan: optimize UMA buffer operations and fix driver hangs (#16059)
63803dac2e48ef3ba26a504eb27c4e77ec2d21f7d0459c0c2c1a400f960d7b8e8d94d31a8426f809862025-09-20T10:42:56+02:00Ruben Ortlamvulkan: use vec dot for matrix matrix multiplications (#16056)
64be79d9fdd95ab8955527c4aaa67b90e8b9516718f432d8d83e7407073634c5e4fd81a3d23a10827f2025-09-19T15:15:21-07:00ssweensllama-bench: add --devices and --list-devices support (#16039)
650dd58b6877f3dc106593d6bc68d98305f553c56669ffd891631befa9e6b485fd646a16dab4f2c0072025-09-19T11:31:56+07:00Xuan-Son Nguyenggml : refactor forward_dup for cpu backend (#16062)
663edd87cd055a45d885fa914d879d36d33ecfc3e1c0b45097c33e2667a94444f08cc9e36bec0a5e2e2025-09-18T12:03:34-07:00Shawn Guopencl: optimize mxfp4 kernels (#16037)
67c0b45097c33e2667a94444f08cc9e36bec0a5e2e38dbdf4c057515ccea9bec0ca2518f86d5e4d28e2025-09-18T13:46:17-05:00Jeff Bolzrename optimize_graph to graph_optimize (#16082)
6838dbdf4c057515ccea9bec0ca2518f86d5e4d28e368560a1e3b9a3bc83af741b0b2bc9e46fb420d22025-09-18T11:26:03-07:00Bowen HanCUDA: Optimize PAD_REFLECT_1D (#15957)
690320ac5264279d74f8ee91bafa6c90e9ab9bbb91a7a98e0fffed794396b3fbad4dcdbbc1849636452025-09-17T20:38:12+03:00Georgi Gerganovmetal : refactor + optimize v2 (#15995)
70c959b676be29e93f8dbc3bd6056ceba812a9eb72cd08fc3ecc0264b4414b68af3874a6c689ed60c12025-09-17T15:32:42+02:00Johannes GäßlerCUDA: fix FA occupancy, optimize tile kernel (#15982)
71d5fabe3682de515fd09d6c981f7a0d1b756144558ff206097c2bf3ca1c7aa95f9d6db779fc7bdd682025-09-17T14:33:08+08:00Chenguang LiCANN: Optimize ggml_cann_set_device (#15935)
728ff206097c2bf3ca1c7aa95f9d6db779fc7bdd6877475530b8bbea3bf578632507e1284cdfe2c8c02025-09-16T16:17:08+02:00jacekpoplawskillama-bench: add --n-cpu-moe support (#15952)
7377475530b8bbea3bf578632507e1284cdfe2c8c03913f8730ec6d6245480affc30ae3049107956f42025-09-16T15:27:52+02:00Daniel Beveniusci : use macos-latest for arm64 webgpu build (#16029)
743913f8730ec6d6245480affc30ae3049107956f476888d202ed2b835ae19ea9f9db6baf39e4192972025-09-16T15:25:57+02:00Daniel Beveniusggml : fix padding in timestep embedding kernels (#15932)
7576888d202ed2b835ae19ea9f9db6baf39e419297f1fbffb5c0b34b2a68febb7da3fd0f8333f1ed4c2025-09-16T13:41:38+02:00Daniel Beveniusci : upload xcframework artifact from ios-xcode-build job (#16010)
76106220562aca42b6738b8f51acfce0db1b8a2fb6a68f31edd71cc39141113f05f7133a3e9ece8c612025-09-15T17:35:11+08:00Aman GuptaCUDA: some micro-optimizations in mmf.cuh for mul_mat_id (#15926)
77b9c9c9f789cd57fb0b28b25223305613cd90fa1050f4281a6f5c3a5d68bdeb12f904fa01e0e2ba912025-09-13T16:23:30+01:00Jeff Bolzvulkan: initialize vulkan-hpp to allow using extension function pointers (#15705)
78f161463a54d9f93d41246286aa4a9569a91d804d84d7b2fca11d1be118ce776f6d72a486c4883b742025-09-13T13:54:28+03:00Georgi Gerganovmetal : allow ops to run concurrently (#15929)
7900681dfc16ba4cebb9c7fbd2cf2656e06a0692a44f658855fa8f2e42b7ed9a5b298fa39a2e39b0962025-09-10T22:04:03+02:00Oliver SimonsCUDA: Add `fastdiv` to `k_bin_bcast*`, giving 1-3% E2E performance (#15872)
809de447d94e1ae9d1a36e5a2e5bf47483352c0d9c0f0a3c2851134d49955f3c85afbb0b1bb47c3e072025-09-10T17:31:40+02:00Daniel Beveniusggml-cpu : fix padding in ggml_timestep_embedding (#15917)
81e7b6d83b524bbc24a1343d862de6dba8e8eddbd62cfef4d117d67ab1dec002915b48a15d11ee19732025-09-10T14:17:09+02:00Daniel Beveniustests : filter out no-ops from coverage report (#15900)
82ff02caf9eed261423289d1531a56536fbf57bfc2ae355f6f7108540297d8b7f7ae71d20fe610a0b72025-09-10T05:23:19+02:00Daniel Beveniusci : cache ROCm installation in windows-latest-cmake-hip (#15887)
83a972faebed5fdc4a3d2a844d92d476058c02e02d550cf726e133fd0a069d991287fd3a2a3e3e1cbd2025-09-09T14:38:02+08:00Aman GuptaCUDA: Add mul_mat_id support for the mmf kernel (#15767)
8470cd37dbbebdb7a2f84f08207f18eabb0b291a55acc1b008cfd95e63d5f99a370dbffb98e5a99d2c2025-09-09T06:06:52+02:00Daniel Beveniusrequirements : update transformers/torch for Embedding Gemma (#15828)
85e68aa10d8f3d26fdad5b912540362d79de5460e30a16bf52e6874369cb4fd2bdc4863ef984b688e72025-09-08T13:10:07-05:00Jeff Bolzvulkan: sort graph to allow more parallel execution (#15850)
8656920f56651908d5cce7a310dabf54ac4f6fbb7fb0d52998b962bd2681c34bf52af993af79f178b82025-09-08T21:50:05+07:00Xuan-Son Nguyenserver : bring back timings_per_token (#15879)
87f28d4f4ac963f182ea9d0fe9e269f3f5f3782aaf9fcb29f22f5c33c04c7f0daebb24057899d67a1a2025-09-08T13:34:56+03:00Georgi Gerganovmetal : refactor + optimize (#15857)
88a885dcff11a7b73f9377812d6151f6b15d307de0663027fd5490438ce9c27ea866a560e1e268d11f2025-09-08T10:27:07+03:00Georgi Gerganovbatched-bench : fix llama_synchronize usage during prompt processing (#15835)
893c3635d2f20424d557b5b0605a2a356214ffe04861bdfd5298a78593be649a1035ee2a120b13c4f02025-09-06T19:45:24+07:00Xuan-Son Nguyenserver : speed up tests (#15836)
9061bdfd5298a78593be649a1035ee2a120b13c4f001806e77714ae8a78130d432945b959a0956c56f2025-09-06T18:35:04+07:00Xuan-Son Nguyenserver : implement prompt processing progress report in stream mode (#15827)
91c1c354e44c06d259679bb5bb7a8fa9f0b28480e4a68d9144262f1d0ef4f6ba7ad4a7e73e977ba78c2025-09-04T20:20:14+08:00Chenguang LiCANN: Refactor ND to NZ workspace to be per-device (#15763)
920fce7a1248b74148c1eb0d368b7e18e8bcb968098227695d7a3e5b357cb37fad263f00a8ca6db7102025-09-03T13:33:15-05:00Jeff Bolzvulkan: don't use std::string in load_shaders, to improve compile time (#15724)
93661ae31c9c68201577e70278285b349a5a662caf407c23786dd0d3a503e9429eead96e611d3950c92025-09-03T19:59:16+02:00Oliver SimonsCUDA: Optimize `rms_norm_f32` kernel and its fused variants, giving 1-6% perf E2E (#15715)
94cdedb70a998cea7052560fe0b0615a839443564d2c8dac72eb6acd4e20c0da251535dfc46d35178b2025-09-03T18:16:26+03:00Georgi Gerganovsampling : optimize dist sampler (#15704)
952c8dac72eb6acd4e20c0da251535dfc46d35178b40a751ea9a94364da73537b86502a808ebe1fc3a2025-09-03T13:35:49+02:00Daniel Beveniusllama : fix incorrect model type for Gemma 270M (#15764)
9605c0380f2ae5c7193445e03ebc7b6de9ce49f1a68c3fdf44ecf08335942f2ba558955f55e88c79912025-09-03T16:16:21+08:00xctanggml-cpu : optimize RVV kernels (#15720)
979961d244f2df6baf40af2f1ddc0927f8d91578c825f1045f07cf0daf667d63e35618842e3174a8c72025-09-02T17:12:37+08:00hipuddingCANN: Resolve soft_max precision issue (#15730)
9802c1813517412f3e00aa6ca7c0273fea64edb49277dee9de97be75b7143a213bc48893e0c0b29af72025-09-01T16:19:07+02:00Ruben OrtlamVulkan: Add Integer Dot Product mul_mat_vec shader for legacy quants (#14903)
99b9382c3877c6067feccf182efe9449a2d1cb24c73dc7397a2799bdc07bccf637ab7ae5a1e786d1a42025-09-01T08:57:23+08:00hipuddingCANN: Optimize MUL_MAT_ID (#15658)
1003dc7397a2799bdc07bccf637ab7ae5a1e786d1a4e92d53b29e393fc4c0f9f1f7c3fe651be8d36faa2025-09-01T08:57:00+08:00hipuddingCANN: fix RoPE cache issue on multi-device (#15629)
101e92d53b29e393fc4c0f9f1f7c3fe651be8d36faa0d161f021aa33ec0e90cce96f5d1a889255573272025-08-31T20:41:02+03:00Georgi Gerganovsampling : optimize samplers by reusing bucket sort (#15665)
102c37052ab4d6d1ae73c0e90bc6e560cc6409e13115c16b9c87d840e4d5d55fa83c732c6b693346f402025-08-31T02:06:43-05:00Jeff Bolzvulkan: mul_mat_id coopmat2 optimizations (#15546)
103e8d99dd0b67f2ecc1e45fca8074a3a18c3e036d2a8bca68f727844e7dcf24a956003b3c2039ea5632025-08-28T18:39:31-06:00Gabe Goodhartnvidia nemotron nano v2 (nemotronh) (#15507)
104fbef0fad7a7c765939f6c9e322fa05cd52cf0c15da54f9f1a2db07aaae390024ac466e7867685d942025-08-27T20:58:09+02:00Johannes Gäßlerserver: higher timeout for tests (#15621)
1051e7489745a74996fc36e8fd05b73aa16bc184e0c1cf123a343ab7ca5586aacb9e0a1d2de7fe33be42025-08-27T17:21:41+08:00Chenguang LiCANN: refactor mask handling and improve performance in FA (#15561)
1068b696861364360770e9f61a3422d32941a4778248ce3ff1d91245e158d98d8062cd64b0dd98dcfe32025-08-27T00:27:49+05:30Akarshan BiswasSYCL: fix rms_norm_mul_add for tensor dim not a multiple of sg_size (#15592)
10744b1efa41acd4df3f56ee0e46f898135ecd1a054a6a58d64785cb458ed9de52f391aa38142d38d642025-08-26T15:42:49ZEvetests: add performance test for mul mat id (#15543)
108a6a58d64785cb458ed9de52f391aa38142d38d640373486dbc0dccbdcb3b5fdd65759d88cec061962025-08-26T21:05:25+05:30shalinib-ibmllamafile: PowerPC Sgemm Optimization (#15558)
109b3964c1e890ef8c947afb36a5124ce6fcb2136d479a546220c719e6a70627b243a478ab8d84dc9e12025-08-26T14:22:14+03:00Georgi Gerganovmetal : optimize FA vec for large sequences and BS <= 8 (#15566)
1101d8d83deaa48d4a5491820d58ff1c0d8cf9d196cc4e9239064a564de7b94ee2b401ae907235a8fca2025-08-26T12:46:15+03:00Georgi Gerganovmetal : improve `MUL_MAT_ID` (#15541)
1110115cfb7c1dec0753aecb34f3af4338bf9de8eeb3a617cb18121a85eed17ac5585788810c5d9c1e0 0d5a470223fc90b6b6807921d68011ff06ae7f9e2025-08-26T15:19:56+08:00Yunzhe JiaMerge branch 'master' into dev
11274f52f77f28a5ad6d6075231afcb8d1ad763ca32f7207b0415986dd7f48447149da7de3a823382762025-08-26T05:21:22+08:00QeeweewCUDA: Accelerate MXFP4 table lookup using `__byte_perm` (#15451)
1134d917cd4f64cc37744e76d084659475819fb0728886b97a5d693550c2da470c091d9d27bf38398f82025-08-25T17:56:59+02:00Ruben Ortlamvulkan: fix min subgroup 16 condition for mmid subgroup optimization (#15565)
1145eff6ec9b1220b599a43b594b1110487ab6aca08dfd9b5f6c7586c88588f06a644c131bec071a0a12025-08-25T17:23:40+02:00Johannes GäßlerCUDA: MoE helper in device code, better tile sizes (#15525)
1156b64f74b55628e4193f4fb00313f07dbd85565280d5a470223fc90b6b6807921d68011ff06ae7f9e2025-08-25T13:56:43+03:00Georgi Gerganovbatched-bench : fix unified KV cache handling + pp timing (#15562)
116043fb27d3808766d8ea8195bbd12359727264402b730706a49e576fb882dc34d9966345778b3ab0b2025-08-24T19:36:36+02:00Ruben Ortlamvulkan: apply MUL_MAT_ID subgroup optimization to non-coopmat devices (#15524)
117611f419cff11e4952228162a1c44cb35dff2274ab1afcab804e3281867a5471fbd701e32eb32e5122025-08-23T13:16:17-05:00Jeff Bolzvulkan: optimize rms_norm, and allow the work to spread across multiple SMs (#15281)
1189ef536907de1b50c30e0369284898d30472a755a21dc4ddaf21b8ed551d717e7606abd2cffbacdbf2025-08-23T12:58:58+02:00Johannes Gäßlerscripts: fix compare-llama-bench.py (#15521)
119289bf4113ef5c02d8f5eb0cf2d86683d8b8bc4d9b55f06e1aa67fb10e89f53e31bbccf37eb2678ea2025-08-23T02:33:36-05:00Jeff Bolzvulkan: Rewrite synchronization to allow some overlap between nodes (#15489)
120330c3d2d21b55bca5517db7d2eea2ea8f131df4ae92734d51bcb82cc35f0a6b5a14928f0036b2c902025-08-23T01:31:54-05:00Jeff Bolzvulkan: optimize mul_mat_id loading row ids into shared memory (#15427)
121ad5c975c2d0297124fad210776ef8eed6b90d5784afb0a746f22abaa545b3ebdb76a400d7da3a7132025-08-22T16:11:04+08:00Aaron Teoggml-cpu: Support Q5_0 and Q5_1 on s390x (#15486)
122a0f98dd604d34826eb5ea2560d1e23fe726921df54a241f505d515d625767b993bfd573ecee306b92025-08-22T14:12:07+08:00Chenguang LiCANN: Optimize RMS_NORM using cache (#15419)
1232758fa10dab0556e6c3f130e664750fd6773dc7cb108e429043ee5c9fc8fa4957a0a52c3e490d5c92025-08-21T12:16:54+02:00Daniel Beveniusexamples : add model conversion tool/example (#15455)
124fec9519802ae1567048abb126cdd5ea160a22d0f657b8a77bd01854f99d37a47318fa24f2e7e298f2025-08-20T09:33:14-05:00Jeff Bolzvulkan: shorten pipeline name strings (#15431)
12537f10f955f70e0158d50343d0b9a3f92d194daae2f37014073f4c6ddc8f241c927db87337c71aa522025-08-20T12:31:16+02:00Daniel Beveniusmake : remove make in favor of CMake (#15449)
126a6d3cfe7fa6ea1fb0e1ba8243b731db22ddc0b4967f09a3a27db443f9870aac87e163dba0d08131e2025-08-19T21:28:22+08:00SHUAI YANGCANN: optimize rope operator (#15335)
1276424594c56f4dbd0573455d89a0d89a0ac093d13e9288e886970884f288533cd597b3798995b40992025-08-19T10:54:31+02:00Marvin Gießingggml-cpu: add mxfp4 VSX intrinsics for Power9+ (ppc64le) hardware (#15385)
128f0d3c7405c323784a60f14ddddfbac3f7404d417f08c4c0d8d0cb6caaf8b7ad316039232b9fa059c2025-08-19T08:45:12+03:00Georgi Gerganovbatched-bench : use rand tokens (#15398)
129de5627910df74298c998e6bb36ee3217375a571965349f26f2299e06477ec8e85e462430468013582025-08-17T03:41:45-05:00Jeff Bolzvulkan: Optimize argsort (#15354)
1301fe00296f587dfca0957e006d146f5875b61e43dde2192794f4e8e04f2e8167ef2424905145e88fc2025-08-16T11:48:22-05:00Jeff Bolzvulkan: fuse adds (#15252)
131863d341eeb81db104902b14b6f9413daa515e957d32e03f4495d3efa1c5126f53b449f1d429c56642025-08-14T08:38:10-05:00Jeff Bolzvulkan: perf_logger improvements (#15246)
1325cdb27e0917479d2d742cea7beee089574bb09fa3ea913f1ce9567289aedd866a569dbab8fb8e4192025-08-14T03:03:57-07:00Jonathan Graehlfinetune: SGD optimizer, more CLI args (#13873)
1336028bf74351d35a06bd98498624f8c2f029f7d1abc5182272c373267352bc689e5fca276934bea2d2025-08-13T10:04:46+02:00Oliver SimonsCUDA: Optimize `reduce_rows_f32` kernel, leading up to 25x perf improvement on kernel-level and 10% perf increase for Gemma3n (#15132)
134bbd57b7eafb3b32e3f7f3a2175bce0b35abc7de825ff6f7659f6a5c47d6a73eada5813f0495331f02025-08-12T16:12:13+08:00Chenguang LiCANN: GGML_OP_CPY optimization (#15070)
1354850b52aedceeb70bb4fe49f2d7cd1df6ee98682cd6983d56d2cce94ecb86bb114ae8379a609073c2025-08-08T23:04:36+02:00Johannes Gäßlerserver-bench: external OAI servers, sqlite (#15179)
1369a96389544a08fd829fccda28142ce2066017fde1d72c841888b9450916bdd5a9b3274da380f5b362025-08-07T13:45:41+02:00Christian Kastnerggml: Skip backend library linking code when GGML_BACKEND_DL=ON (#15094)
1372241453252147bb7362a286977ee9f9a921300629515c6131aecaccc955fdedcfe16c3e030aaefcb2025-08-06T14:12:42+08:00Chenguang LiCANN: add support for ACL Graph (#15065)
138fd1234cb468935ea087d6929b2487926c3afff4bf324a3b715d5c1081c110ce459f8a8486fb1ee892025-08-05T22:10:36+03:00Georgi Gerganovllama : add gpt-oss (#15091)
1394cb208c93c1c938591a5b40354e2a6f9b94489bc3025b621d12a6931ff5e9775d4f644719980ad912025-08-02T04:21:37-05:00Jeff Bolzvulkan: coopmat2 mul_mat optimizations (#14934)
1403025b621d12a6931ff5e9775d4f644719980ad91ec0b18802c91badd3ff1388ffd09ee163251bd722025-08-02T17:20:40+08:00R0CKSTARllama-bench: rename DB table name from test to llama_bench (#15003)
141a9f7541ec25c4c8547daf5ff48700ad2836e2b7d9c35706b98ea271858acef4194f526a71b24cdc92025-08-02T02:57:04-05:00Jeff Bolzvulkan: optimizations for direct convolution (#14933)
142484b2091ce5017901483b5204c07878f171d1441daf2dd788066b8b239cb7f68210e090c2124c1992025-08-01T08:47:27+08:00R0CKSTARcompare-commits.sh: support both llama-bench and test-backend-ops (#14392)
143c7aa1364fd59b2ac06fd9e0a719253d968472dc31a67fcc30677e96dda76bb1b290788e7d8852b512025-07-29T17:43:43+02:00uvosHIP: Ignore unsupported unroll transformation in fattn-vec (#14931)
144bbd0f917797e9d524680f1b30d34a46eb06d76510a5036bee9cfb946870689db4400e9e0d17844c92025-07-29T10:40:50+02:00Johannes Gäßlerserver-bench: make seed choice configurable (#14929)
145bda62193b2a6bebbf515c3c389303094a44458c1c556418b600ad5792440942079d93e393595688b2025-07-28T09:04:27-07:00Leonard Mosescutest-backend-ops : extend test case filtering (#14865)
146c556418b600ad5792440942079d93e393595688bdb16e2831c0f344f041af3d067db81c42b16eb222025-07-28T18:59:04+03:00Radoslav Gerganovllama-bench : use local GPUs along with RPC servers (#14917)
14766906cd82a4a1fd10151707cee3f66cb61fc405511dd5a44eb180e1d69fac24d3852b5222d66fb7f2025-07-26T18:28:14-04:00deepsekHIP: Enable Matrix cores for MMQ Kernels, Enable stream-K for CDNA 3 (#14624)
148793c0d7f46384001738c337d7afa46b45ae32745ce111d39d666f4a3b6a561ad020f6feb8cc677902025-07-25T10:47:39-06:00Gabe Goodhartmetal: SSM_SCAN performance (#14743)
149e4868d16d24dec55e61bcaadaca28feed8f98b13820de57d4faa427a3d0bfb14e48057247fae036e2025-07-24T16:31:48+03:00Georgi Gerganovcontext : perform output reorder lazily upon access after sync (#14853)
150a86f52b2859dae4db5a7a0bbc0f1ad9de6b43ec6b284197df426fb189cdcfe56a43c863a788ac7562025-07-23T21:43:25+02:00Johannes GäßlerCUDA: fix overflow in FA, tune performance (#14840)
151d1aa0cc5d13ec3fa553de5d298f9166679e58479c8ade30036139e32108fee53d8b7164dbfda4bee2025-07-22T13:33:37+01:00Ed Addarioimatrix: add option to display importance score statistics for a given imatrix file (#12718)
152a979ca22db0d737af1e548a73291193655c6be9990083283ec254fa8d33897746dea229aee401b372025-07-19T21:59:08+02:00Ervin Áron Tasnádiggml: adds CONV_2D op and direct GEMM Vulkan implementation (#14316)
15390083283ec254fa8d33897746dea229aee401b37d4b91ea7b2da253e1355b503f0fcb7b428ce005d2025-07-19T12:51:22-04:00compiladeimatrix : use GGUF to store importance matrices (#9400)
15401612b74090df592663cfa01f661c9628f403b59086cf81e88fb75287b71ff19c08a206b7bc2e02f2025-07-17T19:08:33+03:00Georgi Gerganovllama : reuse compute graphs (#14482)
155225e7a1438f4ea85eaa7b5ef3ab3b266ee4d9c06ab140198211385b85eeeb0abd549a4bbe259e10d2025-07-16T16:35:42+03:00Georgi Gerganovllama : add high-throughput mode (#14363)
156ab140198211385b85eeeb0abd549a4bbe259e10d64978340b0b4a0a6e2fb74270c1509383d2eff322025-07-16T20:03:51+08:00Aman GuptaSupport diffusion models: Add Dream 7B (#14644)
1575cae76654113160f691f581930b69fc5535e81594b91d6f71f14040979bcdb7b6729b3bca93ec1c12025-07-16T09:33:28+02:00Johannes Gäßlerscripts: synthetic prompt mode for server-bench.py (#14695)
15879e0b68c178656bb0632cb8602d2940b755077f8c81f4192f91a1e209c1eec7a84fe5371ef9175da2025-07-16T12:00:42+08:00Min-Huallama: add LLAMA_API to deprecated llama_kv_self_seq_div (#14708)
159494c5899cb76859f32ddd913534f2685fd684a3d0f4c6ec0f1a9607ba67071f8a02c69b0afc2f91e2025-07-14T13:14:30+02:00Johannes Gäßlerscripts: benchmark for HTTP server throughput (#14668)
16005fec5bd298d3c0243cbb9336e59b8b6aff75a81dcf7f2ea3c4e3cf36dd9ab5a36785c00e60332672025-07-13T10:36:33+03:00Georgi Gerganovggml : add build-time message to remind about ggml_set_rows (#14661)
161b3ad3a0191994d6c47b2bd389d5c7431526ecd2c98197e5c98388470030d908f355ec5937dcccaaa2025-07-12T05:12:26-05:00Jeff Bolzvulkan: support SET_ROWS (#14587)
16298197e5c98388470030d908f355ec5937dcccaaaf5e96b368f1acc7f53c390001b936517c4d189992025-07-12T04:51:58-05:00Jeff Bolzvulkan: optimizations for deepseek prompt processing (#14555)
1630aedae00e6fb48680324a5ac5da9cba0e35de6b56bdda13981d6c8189b7dc4f9fb8ecb91c21529f82025-07-10T18:20:13-06:00Gabe Goodhartmodel : Granite Four (#13550)
1644a5686da22057867c23bd4a6be941ddc8c51e58598bab638fb28cf95a5a66dd2d51b40d6c8f6d69a2025-07-09T14:59:57-04:00compiladellama : support Jamba hybrid Transformer-Mamba models (#7531)
1656efcd65945a98cf6883cdd9de4c8ccd8c79d219a699f4392a33f57c3352cf8d60bdc53db7ca235e72025-07-08T13:11:42-05:00Jeff Bolzvulkan: optimize flash attention split_k_reduce (#14554)
16653903ae6fa5f1caf187889c839cdd1ad25da40184d0dcd4a06080e796e6742a88f2ffa7fc41b28b82025-07-08T02:38:31-05:00Jeff Bolzvulkan: increase timeout for CI (#14574)
1675d46babdc2d4675d96ebcf23cac098a02f0d30cce17991c466ac835b2c71bd813c1ca7ff8dd97b942025-07-02T13:10:24-04:00compiladellama : initial Mamba-2 support (#9126)
168caf5681fcb47dfe9bafee94ef9aa8f669ac986c783790b0e7e09ab17238b16452a33053a71dbdfad2025-06-29T20:02:53+02:00matteoserver : support jinja extra template kwargs (Qwen3 enable_thinking feature), from command line and from client (#13196)
169a0535ffa0d35fccfec3e1a0a3bfc9dbb6054d7c0bd9c981d7226107f18deb8344c3301450311bb8b2025-06-29T11:04:10+02:00Sigbjørn Skjæretggml : implement REGLU/GEGLU/SWIGLU ops (#14158)
170bd9c981d7226107f18deb8344c3301450311bb8b27208bf657cfe7262791df473927225e48efe4822025-06-29T02:43:36-05:00Jeff Bolzvulkan: Add fusion support for RMS_NORM+MUL (#14366)
1718d94219a4a7f2da72ee542019ca01f36af93d1d6f667f1e6244e1f420512fa66692b7096ff17f3662025-06-27T16:41:40+03:00Radoslav Gerganovggml : add ggml_set_rows (#14274)
1728f52c6f8abb2ed9ad967cc0bfb90acb073011193d2f325130c4ed77a3dcff2c23a926587fb08e2cc2025-06-26T15:10:45+08:00Yunzhe JiaSquashed commit of the following:
17360ef23d6c14d325d83eae5752e5de39ad268e9b0b193d5306912a2adae0fde7481819f6ee0941bc62025-06-26T05:49:04+08:00Aaron Teoggml-cpu: enable IBM NNPA Vector Intrinsics (#14317)
1740142961a2e67909e33cdf410274b56c08c5dce7ace82bd0117bd3598300b3a089d13d401b90279c72025-06-24T01:12:56+02:00uvosCUDA/HIP: optimize mmv paths taken for HIP devices (#14324)
175812939a9e90f99d1bd5bb1bc6b99d12600671d504c9fdfbe1580a66fd7d77c77418ce2c606a29fdd2025-06-20T10:50:27+03:00Georgi Gerganovmodel : more uniform output id handling (#14275)
1768f71d0f3e86ccbba059350058af8758cafed73e6381174bbdaf10d6a80dc2099f284b20544d869622025-06-19T12:24:14-07:00Diego Devesaggml-cpu : remove unnecesary arm feature detection (#14281)
177fffcce535ebbdc25f81966a15b758658788e74665fc7856815920f828f9e90cb759ac82c7f0c1ea52025-06-19T13:24:12+03:00bashayer hijjillama-bench : add --no-warmup flag (#14224) (#14270)
1788d947136546773f6410756f37fcc5d3e65b8135d50d2227953ca9024f04255b4f116d06fcc0db74c2025-06-19T01:10:26+08:00Aaron Teodocs: add s390x build documentation (#14264)
1790dbcabde8c006d5cf781ca0fe071c41559572a72ad590be98c83217fcf1a101d78d9ab389fd5dc0b2025-06-16T10:32:13-03:00bandoticmake: clean up external project logic for vulkan-shaders-gen (#14179)
180b9912ac570de8945ae9383c9ca8291027bf287dd00ba7726100d7e1941d9f5a06f56a7559945b33c2025-06-15T09:18:37+03:00Georgi Gerganovbatch : auto-gen positions + verify multi-sequence input (#14177)
1812e42be42bd6bf1dcc643d6ac4e77419bfe5dd24ffb85a288d72abbd5e5daa8de96e6f8bfa7b5ab462025-06-14T16:34:20+08:00Aman Guptacompare-llama-bench: add option to plot (#14169)
182c61285e7396c8e526fe7794c19e8d4f1c99bfc5109cf2c7c655c90e53e100f29b830a788bab0653d2025-06-13T08:45:37+01:00Ewan CrawfordSYCL: Bump oneMath commit (#14152)
183532802f938c6a18cc6a704057ab571f253fd77edd4e0d95cf581f50c9a21d06eaecae2dd580076bd2025-06-11T19:07:44ZChristian KastnerImplement GGML_CPU_ALL_VARIANTS for ARM (#14080)
1843a12db23b6918682ccb70ab15d897f11fe5fc320ae92c1855b1a5b604fa1bfcced19a556ab3e78c52025-06-10T16:48:07+01:00Juk ArmstrongFixed spec timings to: accepted/tested instead of accepted/drafted (#14104)
185228f34c9ceefa3ea4f4d6933edd858121e8106cb0974ad7a7cd4bca846b15c484ff3be890135a52c2025-06-07T18:58:20+05:30Akarshan BiswasSYCL: Implement few same quantized type copy kernels (#13739)
1867e00e60ef86645a01fda738fef85b74afa016a34ea1431b0fa3a8108aac1e0a94a13ccc4a749963e2025-06-03T13:30:22-05:00Jeff Bolzvulkan: fix warnings in perf logger querypool code (#13937)
18771e74a3ac929b8af91f16f73f3c2b9b2f796d207bfb1e012a0b7658e8f00ed4333d059943ea9d6482025-06-02T16:54:58-07:00lhezopencl: add `backend_synchronize` (#13939)
188093e3f1feb16e25e58f7d61e01266c830dd424b8663445b0deb21fb602176da030d4154197a4fca62025-06-02T17:48:36+05:30shalinib-ibmcmake : Handle mixed-case 'Power' strings in POWER CPU detection (#13966)
189053b1539c02617eff744f89525ee57497c3c1fbeb3a89c3d9e34c28c5be70d8b687a84775746d4a02025-05-31T15:39:19-07:00Max Krasnyanskythreading: support for GGML_SCHED_PRIO_LOW, update thread info on Windows to avoid throttling (#12995)
190b49a8ff96b769b8a4c36d89fb783ec0135be582b53f925074de02c5304b00c14b4d6d8910c58667d2025-05-30T19:40:57+05:30Akarshan BiswasSYCL: Add mrope kernel (#13755)
19154a2c7a8cd8a32b44e3a98c2999b0f5c9114be5c21fcc21ad5e5de2daa5da8d08dbbcc86b8d815d72025-05-29T19:39:20+08:00Yibo Caiarm64: optimize q4_k_q8_k kernel with i8mm (#13886)
192bef817638780dcbd8c0c80c97b7a4f8e92c8fe7434b7c0439ed0f98575cc4689dfecd98991dee8be2025-05-27T11:39:07-05:00Jeff Bolzvulkan: use timestamp queries for GGML_VULKAN_PERF (#13817)
193bc583e3c63c04a11d287c108ea9e6a515ead042372b090da2c50e540143fd312a2f9aa5f151e61362025-05-27T14:06:10+02:00Xuan-Son Nguyenmtmd : support Qwen 2.5 Omni (input audio+vision, no audio output) (#13784)
194f5cd27b71da3ac375a04a41643d14fc779a8057ba2d02d5793fd9af7a7224773456501691b95fd022025-05-25T01:48:08+01:00Olivier Chafik`server`: streaming of tool calls and thoughts when `--jinja` is on (#12379)
1952bd1b30f6979235ec67b95c183b9b77baa7ab9ce259469c4b57c1a32606353bcac52ba683424a9902025-05-24T13:26:47-07:00Diego Devesaggml-cpu : set openmp wait time if not set (#13758)
196f7c9429c85748cde9599499601ba48d0057722e61dfbf2cf3a9f15193dd893396d07762bbd2c47852025-05-20T02:54:43+02:00Nicolò Scipionesycl : Overcoming workaround for mmap() allocation on Windows (#13482)
197725f23f1f3f0d3adf49f95d8dfa6e7c74adff14992ecdcc06a4c405a415bcaa0cb772bc560aa23b12025-05-19T14:38:20+01:00Alberto Cabrera Pérezsycl : backend documentation review (#13544)
1986c8b91500e75df6664278d1e9af3e39e8a2fb0d03cc1f1f1d24472a6558c942b1c78989ff4b0e5692025-05-15T06:46:55-07:00Diego Devesallama-bench : fix -ot with dl backends (#13563)
199b2838049ccf50859cea4c390e81405c2fb01e820aa48e373f256df9608395ee6881e7010840d62022025-05-15T05:57:02+03:00Georgi Gerganovbench : handle decode errors (#13548)
2005ab5d5fb256aa23f8ab4de8463515ea627f430063198405e98530c683d12fd123e3920f2bd2aafa52025-05-15T03:53:52+08:00Yibo Caiarm64: optimize q6_k_q8_k kernel with i8mm (#13519)
20124e86cae7219b0f3ede1d5abdf5bf3ad515cccb8bb1681fbd532eba26ae4c14cd8be884c8afeb31c2025-05-14T18:55:26+09:00Jeff Bolzvulkan: KHR_coopmat flash attention (#13506)
202be1d4a13db26750fac702ceb3af88ae4f39dc9f4ab3971f2a0a526564bfde0e4cc8a5b90f9d33ad22025-05-14T08:41:01+02:00Sigbjørn Skjæretscripts : fix compare-llama-bench.py show parameter (#13514)
203f0995d28ce3d15095b6845d94ce4465e46575873c252e0c4097b34666e5a81db9d0450d71fa3098f2025-05-13T18:04:39+03:00Georgi Gerganovmetal : use FA-vec kernel up to batch size 20 (#13496)
204c252e0c4097b34666e5a81db9d0450d71fa3098f4f711afed5e7ef4304b567c8888ee1aa60e868eb2025-05-13T18:04:00+03:00Georgi Gerganovmetal : optimize multi-sequence FA vec kernel (#13493)
205b89d605a91dee0a518ecd582f8991a07d523e2fab4726345aca49e2ad62d615e6e370b3dbad6434f2025-05-13T18:01:53+03:00Georgi Gerganovbatched-bench : fix pp batch contents (#13492)
206bf7937112058f2815fc3825a9ff7b536ecafa3bbd590cd4c244e5f260c42c290b83a358b9d86d7632025-05-13T15:31:12+02:00Sigbjørn Skjæretscripts : support arbitrary input file formats in compare-llama-bench.py (#13455)
207cf0a43bb6490bd49344775abb22ba26f8047cb54f0d46ef15717cd609a7b69cf6190edde64d466c82025-05-12T15:31:37-07:00Diego Devesallama-bench : add defrag-thold, check for invalid ranges (#13487)
20822cdab343b63edd0906f1c132616746085f81983a71a4075cdb8e81eaaa834e48ffda88b038286bc2025-05-12T13:08:22+02:00Diego Devesallama-bench : accept ranges for integer parameters (#13410)
20909232370fc6426aa5dd9be01a8271b9c28f5af3a7474e00b34629e9cd8b06bc87ad935584ea30f8e2025-05-11T16:20:39+02:00Sigbjørn Skjæretscripts : exit compare-llama-bench.py gracefully when there's nothing to compare (#13451)
2107f323a589f8684c0eb722e7309074cb5eac0c8b53eac209319a6726fd9687c6188fc6b916b65953d2025-05-11T20:18:39+08:00David HuangAdd `--no-op-offload` to improve `-ot` pp perf in MoE models like llama4 400B (#13386)
211dc1d2adfc0f4de84da7923866d00781ec5c4e6667c28a74e0783f4bb74a246fb9f19bf212139e3652025-05-09T23:07:07-07:00Jeff Bolzvulkan: scalar flash attention implementation (#13324)
21233eff4024084d1f0c8441b79f7208a52fad7985817512a94d636c4b6c1332370acb3e5af3ca709182025-05-09T19:29:37+02:00Xuan-Son Nguyen server : vision support via libmtmd (#12898)
213611aa914ef4231fab5d1ad04773c42e119ae2d2e0cf6725e9f9a164c39f7a87214d60342f7f946d82025-05-09T15:14:56+03:00Georgi Gerganovmetal : optimize MoE for large batches (#13388)
2141e333d5bba18e99bc328bb87ac1ee6a4e6260e0e2f54e348ad2999c4e31b8777592247622b20420f2025-05-06T20:27:06+05:30Akarshan BiswasSYCL: Disable reorder optimize by default and stop setting tensor extras when optimize is disabled (#13254)
215b34c859146630dff136943abc9852ca173a7c9d69b61acf06041dcbaff6afa5f28940e93297f85202025-05-05T17:03:31+03:00igardevserver : Webui - change setText command from parent window to also send the message. (#13309)
216b34443923cad751483cc53af2e680d595daadce7a75cb30dc9e63488c3614e2d5a9fe2306eaf47cd2025-05-02T20:54:30+03:00Georgi Gerganovsync : ggml (#13268)
2173f3769ba76061a511f02f2a48da2ad2d93fce5112f567611c0234bbca0a4009762acb47b568660952025-05-02T22:23:12+05:30shalinib-ibmggml : Enable MMA for BF16 in llamafile_sgemm (#13148)
21819e899ce21a7c9ffcf8bb2b22269a75f6e078f8fe2e1ddb93a01ce282e304431b37e60b3cddb61142025-04-29T23:32:04+02:00Johannes Gäßlerscripts: n_depth for compare-llama-bench [no ci] (#13201)
2195a6398011704c31178d7b774be67856ba57647c8cdf76586b23c67abd3ca064ee2c084c57ae240bd2025-04-29T16:24:36+01:00Alberto Cabrera Pérezllama-bench: fixed size of fields to correctly map to values (#13183)
2201831f538f720d1d99fba146f24f0a8e970838cc44e87962e34a4b257ec374c4baf6b1568554b81a92025-04-28T20:20:39+05:30Vishal Agarwalllama-bench: add `-d` depth arg (#13096)
221c0a97b762e5ec767dc414f0dc4979befd4c09a52ced44be34290fab450f8344efa047d8a08e723b42025-04-27T14:48:26-07:004onenllama-bench : Add `--override-tensors` arg (#12922)
2222d451c80590b9ac250322769ac13d3b4870dbcf74753791e70acd4d4e02f2098f14a03df26c992bd2025-04-26T22:58:12+02:00Xuan-Son Nguyencommon : add common_remote_get_content (#13123)
22377d5e9a76a7b4a8a7c5bf9cf6ebef91860123cbad5fe4e81bd447124836ecfb47d794f8768665b9f2025-04-26T22:05:31+08:00SXXggml: move fp16/bf16 conversion optimizations to CPU backend + export conversion APIs (#13107)
224553a5c3a9fdf771be2101bc3529937963f81745713be08daf992c89d5169518229b3740041c0f4192025-04-25T10:08:08+03:00Radoslav Gerganovrpc : do not wait for response when sending RPC_CMD_SET_TENSOR (#12943)
2257a395f67a7a02bb361d944b816d6e933889e28e1971f245b3b5f3f55991bb779cb541b00f82eea1d2025-04-17T20:34:16+08:00hipuddingCANN: Add support for async operator submission (#12864)
226015022bb53387baa8b23817ac03743705c7d472bb43d89e311c5e7fbf62e5ec3c0401eb5366772672025-04-16T13:37:25-05:00Jeff Bolzvulkan: enable coopmat2 FA gqa and split_k optimizations more often (#12931)
22784778e97703740d8ac5fb64e14d83b80eafa0f3c510676475f885ec064ff147af9f20ee7a9b12a502025-04-15T17:20:38+08:00David HuangCUDA/HIP: Share the same unified memory allocation logic. (#12934)
228daa422881a0ec7944771bcc8ff8de34d11f5bd3beccc7a1602f0752507de4aaad1008b9618a282c82025-04-15T07:49:57+01:00Juk Armstrongllama : DeepSeek V2/V3 MLA implementation (#12801)
2290019279bb56f028e4eee19b59b19750736c719f7b0c75ac9f93322b45e3766e149417334b4fd1ed92025-04-15T10:09:35+08:00Chenguang LiCANN: Opt ROPE optimization (#12865)
230b0c75ac9f93322b45e3766e149417334b4fd1ed9d6d2c2ab8c8865784ba9fef37f2b2de3f2134d332025-04-15T10:04:24+08:00Xinpeng DouCANN: Optimize CANN buffer pool memory management (#12875)
231d6d2c2ab8c8865784ba9fef37f2b2de3f2134d3375afa0ae31f0a51aaadcc5ff146eb7a32a7f90882025-04-15T01:18:20+08:00RussyydsAdd performance print for gemma3 in example (#12929)
2328b9cc7cdd8a0dcf0176c60c755322c95b596529964eda5deb9859e87a020e56bab5d2f9ca956f1de2025-04-10T22:57:16+02:00Xuan-Son Nguyenllava : introduce libmtmd (#12849)
2330090950f679475c5ecaac2f7bca5049cca96492b7ecd780b1a1d5214b8d04c25ebfc194d310816ed2025-04-09T00:25:08-05:00Jeff Bolzvulkan: In coopmat2 mmq, load q4_k/q5_k scales through shared memory (#12833)
2348ca6e1c3a4deb6bb27ee294bfd5706098d94ae88656babd6c21a3b9b3622324cfcc80a2ab78da25b2025-04-08T14:14:59+05:00characharmserver : webui : Improve Chat Input with Auto-Sizing Textarea (#12785)
2356bf28f0111ff9f21b3c1b1eace20c590281e7ba6f1e3eb4249db68d97be352c0adf16eef7ae537952025-04-05T18:04:03+02:000cc4mVulkan: Tune Vulkan mmq int dot shader for performance (#12767)
23674d4f5b041ad837153b0e90fc864b8290e01d8d535e592eb30832187412360912ab8f2f5b7984df12025-04-04T00:54:35-05:00Jeff Bolzvulkan: Hybrid waitForFences/getFenceStatus to reduce fence latency (#12630)
237c262beddf29f3f3be5bbbf167b56029a198769565dd5d1ab00d074e3b7c02ca3ae12f6bf3e86336a2025-04-03T21:50:29+05:30Gaurav GargCUDA: Prefer vector flash decoding kernel for Gemma models (#12738)
238be0a0f8cae039e2286f757612accebfb8f21b36e92e3006bb69dfeb656ccf5c7c1c1efadb03c88c22025-04-02T12:40:32-05:00Jeff Bolzvulkan: Implement grouped query attention in the coopmat2 FA shader (#12559)
2399bacd6b37461608385360fd64326c13247ccf18e267c1399f15a278ec8c3cdcf9c90dc94151fbc382025-04-02T15:22:13+08:00Chenguang Li[CANN] get_rows and dup optimization (#12671)
240e408d4351a4ad143656672479d8ae1479306ce313891e183c61c1e25c2c61afe68d7b95019ea3f892025-03-24T09:53:38+01:00Daniel Beveniusggml : add logging for native build options/vars (whisper/2935)
2413891e183c61c1e25c2c61afe68d7b95019ea3f89af6ae1efb27a9a7c3f7f7f84639d2243f7303ac12025-03-20T07:02:18+01:00Daniel Beveniusexamples : command.wasm updates (whisper/2904)
242b4ae50810e4304d052e630784c14bde7e79e4132b86f6007234da4bff51a3ebef2bdb952b52059c62025-03-28T20:21:59+02:00Georgi Gerganovmetal : improve FA + improve MoE (#12612)
2435d01670266859444366e4f333ade5e0e5e2ae63def03229ff423dd1991f4f44ef1352f03334d86eb2025-03-28T01:05:44-07:00Benson Wongserver : include speculative decoding stats when timings_per_token is enabled (#12603)
24413731766db91ec927c1b61bf502ac7a9be2b11b9ab6ab8f809bd514d88e02a63869b4d619f13fa862025-03-28T13:13:22+05:30amritahs-ibmllamafile : ppc64le GEMV forwarding for FP32. (#12594)
245c7b43ab60855f752ae79937fb93d561bc30b69a424feaec05792b972d5ff3e2b12d9237ebd50d1ac2025-03-27T12:21:47+05:30amritahs-ibmllamafile : ppc64le MMA implementation for Q4_0. (#12489)
246ef19c71769681a0b3dde6bc90911728376e5d236053b3f9aae63151732eccf6b7408c6418ba8746e2025-03-25T17:46:11ZEric Curtinrun: de-duplicate fmt and format functions and optimize (#11596)
247e2f560175a195f63c3276972a3d1caec0bd13e0536ee06dd2dcf8d3d1157ebe36366d7670770e75f2025-03-25T16:10:18+05:30Akarshan BiswasSYCL: disable Q4_0 reorder optimization (#12560)
248eddfb438502bd5d1014d63a812e9b6d03d326f8c4375415b4abf94fb36a5fd15f233ac0ee23c0bd12025-03-22T03:40:11-05:00Jeff Bolzvulkan: Optimize mul_mat_vec p021 and nc shaders (#12505)
249732b5fbf5e7f9cf069942f0c5850ee959ef321ba568013d0cd3d5add37c376b3d5e959809b711fc72025-03-20T02:36:37-04:00Bartowskiconvert : avoid calls to tokenizer.added_tokens_decoder (#12473)
250517b5ddbf002b91fd6d6daf5d8db8c88a0173039a9b59288e222f39fc0311dc66944ed5a86c815fa2025-03-20T01:22:06+05:30Gaurav GargCUDA: Improve flash decoding kernel GPU occupancy for BS=1 case (#12183)
251a9b59288e222f39fc0311dc66944ed5a86c815fa0fd8487b142b2b92565bc95b39ddc440955a237c2025-03-19T13:56:23-05:00Jeff Bolzvulkan: optimize iq1 coopmat2 dequant functions (#12427)
252c446b2edd2a9fe2772a1a18923c3e54a6749c364d84635b1b085d54d6a21924e6171688d6e3dfb462025-03-19T02:26:26-05:00Jeff Bolzvulkan: Submit once enough matmul work has been recorded (#12406)
253d84635b1b085d54d6a21924e6171688d6e3dfb4675422e8bc42646005be0754f7aa438b97a5e777e2025-03-18T12:54:55-07:00lhezopencl: improve profiling (#12442)
254484a8ab513bbd740cc49f30280c1acf52cb4e7e9cf2270e4d3685ac46f4a166d8718997ba7cbc45a2025-03-17T09:26:18-05:00Jeff Bolzvulkan: Add N/2 and N/4 optimized paths in coopmat2 shader (#12312)
255891c63956dbfbdf7ed2ecd0b5882cff49dbfe90f2f21123c1deb3ce1be3c0578c5f6980fe19ed0772025-03-17T04:41:59-05:00Jeff Bolzvulkan: Pad N dimension of B matrix for coopmat2 perf, to avoid bounds checking (#12273)
25692a391327e9201b9b5b32fdd3afb452026c22d4c9f2250ba722738ec0e6ab684636268a79160c8542025-03-15T09:31:08+08:00Chenguang Li[CANN]MUL_MAT optimization (#12382)
2579f2250ba722738ec0e6ab684636268a79160c854774973b8f3d5e375b0b74d58638eeb1817e950a82025-03-14T16:41:20ZEric CurtinAdd CLI arg to llama-run to adjust the number of threads used (#12370)
2585e2d57b2b2e43eadbe6d66ba3e873a824b95e725f1648e91cf6c52e9593810aa70857e412d474c092025-03-07T15:35:57+08:00BB-fatmetal : simplify kernel arguments using a struct (#3229) (#12194)
259e721c05c9336a72fbb59d5c75967360bc67036c657b6abf85acb1f697913a44e5e105e333d894b782025-03-06T08:20:52+01:00uvosHIP/CUDA: set the paramerter value in maintain_cuda_graph instead of replaceing it. (#12209)
260ed4ce0dda24986c80d58e2ce112049af00f632f407d15723470a0a5b15d8ccad1aff5b20354ffbe12025-03-06T09:30:05+08:00simon886212opencl : fix profile-related errors (#12095)
261669912d9a5bf927312c553332ff997f0a99da8fbfa31c438e0e709242ab7334d26fc3be3dcda07a02025-03-05T13:05:13ZOlivier Chafik`tool-call`: fix Qwen 2.5 Coder support, add micro benchmarks, support trigger patterns for lazy grammars (#12034)
2623ccbfe5a71c74ac574b00607067d0aa0a49df04c06a92a193a07afe445929607be9d5e4d033956fb2025-03-05T08:34:02+01:00Daniel Beveniusci : remove xframework upload (#12190)
2632679c3b55d1c9c3fed56dea00fea713622e42594c43af9276b119dae7436b7878d59671d0f6b1a972025-03-03T16:17:36+01:00Daniel Beveniusci : set GITHUB_ACTION env var for server tests (#12162)
2647b69003af74924ac04d97313c2e57c45ba56b616ece9745bb8079b9f4af45df29b67ad0c6e50584d2025-03-03T11:42:45+01:00Xuan-Son Nguyenwebui : add ?m=... and ?q=... params (#12148)
265438a83926afcff3643ffef5543db67545ceffe399c42b1718ca8299f9afeabdc122badeab64c96902025-02-28T09:42:52+01:00Rémy Ovulkan: add specific MMV kernels for IQ2 and IQ3 quants + optimizations (#11595)
266581650b7cacec2872982fde381bd3bcda0f78699b95c8af37ccf169b0a3216b7ed691af0534e50912025-02-28T06:52:51ZDanielevulkan: improve im2col (#11826)
2677a2c913e66353362d7f28d612fd3c9d51a831eda08d5986290cc42d2c52739e046642b8252f97e4b2025-02-24T09:09:51-07:00Alex Brooksllava : Add Granite Vision Support (#11794)
26808d5986290cc42d2c52739e046642b8252f97e4b651adf4b6675339465179b81b194d98cc14704d62025-02-24T22:33:23+08:00Neo Zhang Jianyu[SYCL] Optimize mul_mat for Q4_0 on Intel GPU (#12035)
269af7747c95ae71a5db4184947f837179e82c70b77a28e0d5eb18c18e6a4598286158f427269b1444e2025-02-23T05:39:24+08:00Aaron Teoggml-cpu: Support s390x SIMD Instruction Set (#12019)
27036c258ee921dbb5c96bdc57c0872e4a9a129bef6f3e64859edb0d55d4223ead78672597cd1a218df2025-02-22T22:28:28+08:00Ting Loullava: build clip image from pixels (#11999)
2715fa07c2f93c73161bf09ef0b23b5d2686f9a073e335eb04a91f481f37c0c9b302ee31b449b04c3e92025-02-22T12:20:17+01:00Johannes GäßlerCUDA: optimize FA for GQA + large batches (#12014)
2726dde1782483d6b0a1d59f5a5fbcb3119b9d34c27fc10c38ded84670955d4c44770f8acfb64617e152025-02-15T20:23:22+01:00Johannes Gäßlerscripts: fix compare-llama-bench commit hash logic (#11891)
27322885105a6b034abaf1c1471ad90fb2ae96146bbc2cd24fbfdfeacc2fc6ad03878379de1042641142025-02-15T19:39:20+01:00Adrian Kretzmetal : optimize dequant q6_K kernel (#11892)
274fc1b0d0936e4dfc52a81f38e7420c7d23f6caa8889daa2564f6eab33be53c6a1b39273af536d6bb32025-02-15T09:01:40+01:00Rémy Ovulkan: initial support for IQ1_S and IQ1_M quantizations (#11528)
27538e32eb6a0cec32130b699ce9fefad6c74571953a4f011e8d02179f032627130f961eb77ee30401c2025-02-14T16:54:27+08:00Jinyang Heggml: optimize some vec dot functions for LoongArch ASX (#11842)
276a7b8ce226071b2b0faaad0d36cc5ebd7fb07473004045bb84288dc7e9e424d4e2bf7f40d259b4c6a2025-02-14T09:13:43+08:00theraininskyllama-bench : fix unexpected global variable initialize sequence issue (#11832)
27727e8a23300e30cd6ff6107ce262acf832ca60597e4376270d971cff7992bdb6c5412a739195b14592025-02-13T00:45:57-06:00Vinesh Janarthanansampling: add Top-nσ sampler (#11223)
278be3bbd62153820ff6d358c817360927f429105c431afcbee0eebbc998ab311aa314e389d60aa21272025-02-13T00:33:45+01:00Xuan-Son Nguyenggml : x2 speed for WASM by optimizing SIMD (#11453)
279c2a67efe38e6782c0217e1de3edc68de6951612bb044a0fe3ca0cbef9dd041edce3ebda8c501fae42025-02-10T07:17:21+01:00Danny Milosavljevicvulkan: Make Vulkan optional at runtime (#11493). (#11494)
28055ac8c7791ff44aeb82bd7fe3ca2041844fc77f1e6e658319952f7ad269dc11275b9edddc721fc6d2025-02-08T21:54:50+01:00Xuan-Son Nguyenserver : (webui) revamp Settings dialog, add Pyodide interpreter (#11759)
2812d219b389e8c8c40bce547b08c8aa7add60fde1f333820d7491cd31c707a340ff23b984a84e401542025-02-07T08:55:47-05:00Christian Fillionvocab : ignore invalid UTF-8 input in the BPE tokenizer (#11729)
2827ee953a64a40c09438b2064539becdbc577cefd0ec3bc8270bc67b58955748d40a3e558a05b2d8f22025-02-07T04:33:27-05:00Christian Fillionllama : add llama_sampler_init for safe usage of llama_sampler_free (#11727)
283225bbbfa39930cda38a2e5d1f3e5b38226732009855cd0734aca26c86cc23d94aefd34f934464ac92025-02-07T15:38:31+08:00Jinyang Heggml : optimize and build warning fix for LoongArch (#11709)
2842fb3c32a1634488a5265d1304ab37628eeb5480d9ab42dc722ad19a12af80f38a06474d498f96da32025-02-06T17:32:29+01:00Xuan-Son Nguyenserver : (webui) migrate project to ReactJS with typescript (#11688)
2852c6c8df56d8a3edd657b9a295e95d469a37f00448a7e3bf17aa5a8412854787746c92a28623a89252025-02-06T00:15:30-06:00Jeff Bolzvulkan: optimize coopmat2 iq2/iq3 callbacks (#11521)
28684ec8a58f7b6aad6887bbfbd1321f3ff417341a5bfcce4d693617ec843d0b2510f6ee16e6bc6720d2025-02-02T16:14:48+01:00Eric CurtinName colors (#11573)
287ff227703d6d6e1888bdc7af6138514092ffcdb960cec062a638700495673f5494d200b74340538be2025-02-01T23:55:32-08:00Michał Moskalsampling : support for llguidance grammars (#10224)
28866ee4f297cff3c7ce98b31dbc0ce909d41b9e408e51c47b401f8cb5f21630a05171e2529cde4d1862025-01-29T18:29:39+01:00Rémy Oudomphengvulkan: implement initial support for IQ2 and IQ3 quantizations (#11360)
289be5ef7963fcf14a9c77c963fdd3f7b606eacb498cae9fb4361138b937464524eed907328731b81f62025-01-28T23:06:32+01:00uvosHIP: Supress transformation warning in softmax.cu
290cae9fb4361138b937464524eed907328731b81f67fee2889e6565830631fbe76d47ef85cf8fd946a2025-01-28T07:42:20-08:00Nikita SarychevHIP: Only call rocblas_initialize on rocblas versions with the multiple instantation bug (#11080)
291f643120bad8ab3a753daa64aaac8288ee5800e066e84b0ab8e10b8f6f99a32855f976ebcd35b03532025-01-28T11:42:32+01:00Nunodocker: add perplexity and bench commands to full image (#11438)
292a5203b4465c5c87813936bde98170e25bb09024fdf984e014714cba4c99ef894b20b51cbcef31b162025-01-27T17:42:09+04:00lexasubllama : minor fixes for up llama load model speed (#11448)
2934a75d19376f2f00dbae6c266eb9c4f3001872b5226771a1491f3a4c3d5b99c4c267b81aca9a7dfa02025-01-25T15:29:57-06:00Jeff Bolzvulkan: compile shaders on-demand (#11406)
29458456616408c828a1ce6d2481940fd1c97bce3b5f211d1dc10332b7e89a4abd1041903fa63bfed272025-01-23T13:56:05+01:00Xuan Son Nguyenserver : add more clean up when cancel_tasks is called (#11340)
29592bc493917d43b83e592349e138b54c90b1c3ea7b9daaffe02d6a77d85f0420bce5dfe0e00daeff62025-01-19T20:22:30+02:00Georgi Gerganovtests : increase timeout when sanitizers are enabled (#11300)
29644e18ef93995f3040660750b527e5becf85899d03edfa7d3753c29e44b964c0ff424d2ea8d5fdee62025-01-18T02:26:50-06:00Jeff Bolzvulkan: fix coopmat2 flash attention for non-contiguous inputs (#11281)
297466300fe1416de2802b710215817db28d4496f41206bc53422521a67de5e2caba661e21d590d2bae2025-01-16T15:23:49-06:00Jeff Bolzvulkan: optimize coopmat2 q4_k/q5_k dequant functions. (#11206)
298206bc53422521a67de5e2caba661e21d590d2bae4dbc8b9cb71876e005724f4e8f73a3544646bcf52025-01-16T15:16:39-06:00Jeff Bolzvulkan: optimize coopmat2 q2_k dequant function (#11130)
299adc5dd92e8aea98f5e7ac84f6e1bc15de35130b5f11cfdfd7fe29436fce512d934c2ff6b94bd89d22025-01-15T19:50:13ZEvevulkan: scale caching for k quants + misc fixes (#11081)
30039509fb082895d1eae2486f8ad2cbf0e905346c4a29f0870d4846f52eda14ae28cea612ab66d903c2025-01-13T16:45:53+01:00Andreas Kieslingercuda : CUDA Graph Compute Function Refactor (precursor for performance improvements) (#11042)
301afa8a9ec9b520137bbd1ca6838cda93ee39baf20c05e8c9934f94fde49bc1bc9dc51eed2826051502025-01-12T11:32:42+02:00Georgi Gerganovllama : add `llama_vocab`, functions -> methods, naming (#11110)
3028cef75c743ba13ebbd6d380c531200c768a8b8aa0d52a69e4bf0d6181beec7853307bdcdeec9905b2025-01-08T16:24:19+05:30amritahs-ibmllamafile : ppc64le MMA INT8 implementation (#10912)
30302f04301417e7fb44fa1025bc1b0aef866e2ca89bec2183f2c8d37cf1278c11d1adb9311e9eaa2422025-01-08T09:18:13+01:00Mathieu BaudierDisable GL_KHR_cooperative_matrix Vulkan extension if not available. (#11117)
3042f0ee84b9b02d2a98742308026f060ebdc2423f10da5d860266c6928b8c9408efbd264ae59fedda62025-01-02T18:06:12+01:00Pierrick Hymbertserver: bench: minor fixes (#10765)
305716bd6dec3e044e5c325386b5b0483392b24cefec250ecb3157f3bae0a45f44c3c953b5414d4c2f72024-12-30T11:27:11-06:00Jeff Bolzvulkan: optimize mul_mat for small values of N (#10991)
306a813badbbdf0d38705f249df7a0c99af5cdee678fdd21889123bec62b1db3b2fc22b5a4abab321742024-12-29T03:16:34-06:00Jeff Bolzvulkan: im2col and matmul optimizations for stable diffusion (#10942)
3072cd43f4900ba0e34124fdcbf02a7f9df25a10a3d09fe2e76137dde850b13313f720e7ffa17efdefa2024-12-24T18:54:49+01:00Djip007ggml : more perfo with llamafile tinyblas on x86_64 (#10714)
3087024d59e6a572730626cb11896829d115043a1b17c0e28585843b366864b43b48f92425e2ea17df62024-12-22T16:20:11-08:00yuri@FreeBSDggml : fix run-time on FreeBSD in get_executable_path() (#10948)
309a91a41364b25705dbb81ae996bc35c3440c63b35e34c5af43f941f0ddb92466776339897295aca112024-12-21T01:04:45-06:00Jeff Bolzvulkan: optimize coopmat2 dequant functions (#10855)
310644fd71b44c4cdbfc6482fbf0353d289c3bc29e64ddd199f6f6b980e0a7ed9f9b44efeae2fbdf5c42024-12-16T12:31:14+02:00Georgi Gerganovsampling : refactor + optimize penalties sampler (#10803)
311e52aba537a34d51a65cddec6bc6dafc9031edc63ba1cb19cdd0d92e012e0f6e009e0620f854b6afd2024-12-14T18:17:36ZEvgeny Kurnevskynix: allow to override rocm gpu targets (#10794)
31264ae0655114f84f11a724bc6878c6f8f4a55560b83ed24a97b500ccdb32b90b94e6f9621ad8db79e2024-12-13T08:42:04ZEvevulkan: small mul_mat_vec optimizations (#10665)
313235f6e14bf0ed0211c51aeff14139038ae1000aa1a31d0dc00ba946d448e16ecc915ce5e8355994e2024-12-11T20:52:14+01:00Xuan Son Nguyenserver : (UI) add tok/s, get rid of completion.js (#10786)
31419d8762ab61df8286367588a80b9c7db4cb568dbc2a16c0bdbe2e51adf318918bad82f0c3e3d6f3b2024-12-07T13:37:50+01:00Djip007ggml : refactor online repacking (#10446)
3153df784b3050f657ea681f804187ce5bddb433e8886a1934978ce5daffc7e5b4251f6540ee5e7b47b2024-12-07T10:24:15+01:000cc4mVulkan: VK_KHR_cooperative_matrix support to speed up prompt processing (#10597)
31640c6d79fb52f995f47507fedfeaae2ac05d9b35c98036d5670f21e9b9a99d5e3dbb3bf7589f5c4e32024-12-04T02:29:20+01:00Nicolò ScipioneSYCL : Move to compile time oneMKL interface backend selection for NVIDIA backend (#10584)
317cc98896db858df7aa40d0e16a505883ef196a48291c36c269bca75b2d08119c653512cd20b4ea2ba2024-12-03T13:29:54-06:00Jeff Bolzvulkan: optimize and reenable split_k (#10637)
318efb6ae963031709fc331e6e48cc4606ac8f9c3a7667d70d1704dfa6977505f5d01d4638669b90dce2024-12-02T19:27:24+01:00PABfeat: add `GGML_UNARY_OP_ARGMAX` Metal kernel (ggml/1019)
319938f6087421889a3af7d0786c64406ced2be81b8f095a649ec390e04dfab1b04e646ae8549dafaef2024-11-29T14:46:55+08:00Chenguang LiCANN: RoPE operator optimization (#10563)
320f095a649ec390e04dfab1b04e646ae8549dafaef678d7994f4da0af3d29046be99950ac999ee97622024-11-29T00:18:02-06:00Jeff Bolzvulkan: get the first command buffer submitted sooner (#10499)
321c202cef1686182a78f8f4e253ab8d0c0ffe2fcc82025fa67e94358deda4740a74fe9803916cb2f602024-11-28T20:52:03+08:00Shupei Fanggml-cpu: support IQ4_NL_4_4 by runtime repack (#10541)
322b7420131bf8ab3e067bc660439ab1ab18be7edbd9f912511bc9414fa7a3c521378b6388cd932b58d2024-11-28T14:24:46+08:00Chenguang LiCANN: ROPE operator optimization (#10540)
3233ad5451f3b75809e3033e4e577b9f60bcaf6676a46c69e0e752ff16206347bb12f96ed69f4a01abf2024-11-27T17:10:08+01:00uvosAdd some minimal optimizations for CDNA (#10498)
32446c69e0e752ff16206347bb12f96ed69f4a01abf9e2301f4a4ef1690bd99360c11de43fe830b1c8d2024-11-27T11:03:25+01:00Diego Devesaci : faster CUDA toolkit installation method and use ccache (#10537)
325249a7902ec710c8d027b9cc0ed10219d2b4184f871a64989a5d2e25c13507efada145f12cf3589142024-11-27T01:21:59-06:00Jeff Bolzvulkan: further optimize q5_k mul_mat_vec (#10479)
3264a57d362e1948ada50af997a92c3cbff9711e78bc9b00a70b080d5c0668608024afc3e0e2fed822f2024-11-27T01:00:50-06:00Jeff Bolzvulkan: optimize Q2_K and Q3_K mul_mat_vec (#10459)
3279a4b79bcfa4338b922fa8cf903bd5ac058aaf46f7066b4cce2898993e943ad6af5d8f1de5840c8e92024-11-26T18:08:37+08:00Shanshan ShenCANN: Improve the Inferencing Performance for Ascend NPU Device (#10454)
3287066b4cce2898993e943ad6af5d8f1de5840c8e90eb4e12beebabae46d37b78742f4c5d4dbe52dc12024-11-26T17:31:05+08:00Chenguang LiCANN: RoPE and CANCAT operator optimization (#10488)
3296dfcfef0787e9902df29f510b63621f60a09a50b599b3e0cd40432cd1975a8906f3db70bbe53b6272024-11-22T17:44:08+08:00蕭澧邦ci: Update oneAPI runtime dll packaging (#10428)
330a5e47592b6171ae21f3eaa1aba6fb2b7078750631bb30bf28cb5a7adf111bc41c935bdaf128397e72024-11-21T18:18:50+01:00Diego Devesacuda : optimize argmax (#10441)
3311bacb9f62514b520bdf74ed6feb46c80508dad38ad21c9e1f14d82b8c15ae369a8839019e3d498b42024-11-20T01:11:00-06:00Jeff Bolzvulkan: further optimize mul_mat_vec using larger loads (#10387)
3322a1507c1629975d9d20a503d6a14f44eff292c25b3e585988fc65d3a8083c6d94dfc0629f9ce226d2024-11-19T09:02:23+01:00Romain Biessysycl : Add option to set the SYCL architecture for all targets (#10266)
333b3e585988fc65d3a8083c6d94dfc0629f9ce226d557924f22237c76387a39c4db5abae154d57e7542024-11-19T01:25:17-06:00Jeff Bolzvulkan: Optimize soft_max (#10301)
334cf32a9b93ad859ea592c31785b6bd3b4b2121463a43178299c2f74f14bcfc659bfd9fd32d931d1f42024-11-17T11:23:01+02:00Georgi Gerganovmetal : refactor kernel args into structs (#10238)
3358a43e940ab0daaff198809bf9277289994ec62f55c9a8b22b10132db620529435e3cfa49304b65cc2024-11-16T22:17:59+02:00Johannes Gäßlerggml: new optimization interface (ggml/988)
336f245cc28d4eb900efad0bc740145f58d713c6e4f772703c8fffdd83d2e28f60119e83525f11894122024-11-16T10:32:50+02:00Georgi Gerganovscripts : fix missing key in compare-llama-bench.py (#10332)
337772703c8fffdd83d2e28f60119e83525f1189412dd3a6ce9f84d21ba05fe98af9f983bdea0398e6c2024-11-16T00:26:57-06:00Jeff Bolzvulkan: Optimize some mat-vec mul quant shaders (#10296)
3381e58ee1318429a3e97aa66f3034cdfd65ffc6c3489e4caaaf081f4712af61a3e08cb67b406c02b802024-11-16T01:53:37+01:00Dan Johanssonggml : optimize Q4_0 into Q4_0_X_Y repack (#10324)
3394047be74da398acb8717a4d21b77b929ad7ed4f7883d206fbd2c5b2b9b589a9328503b9005e146c92024-11-15T21:19:03+01:00Johannes Gäßlerscripts: update compare-llama-bench.py (#10319)
34018429220bdb344da1bc7df9bc580c7b41b3cd57bf0204a0ec70d50ca60e07bc0096ec1d6508ab0c72024-11-15T11:47:58ZEveAVX BF16 and single scale quant optimizations (#10212)
3415a54af4d4f588f109f31e456483fdf77096399d91607a5e5b08f4e55f118af3d7de325949d8f18352024-11-15T04:09:12+01:00Romain Biessysycl: Use syclcompat::dp4a (#10267)
342af148c9386da825a60c7038549c121c35ca56b5066798e42fbe636f1cb6236e4bc30939d23ef7c252024-11-13T23:22:55-06:00Jeff Bolzvulkan: Optimize binary ops (#10270)
3432e82ffa4af29f87e7d3d6dff8060a2a79613b72f80dd7ff22fd050fed58b552cc8001aaf968b7ebf2024-11-13T09:40:57ZAlberto Cabrera Pérezsycl : Fixes to broken builds and test-backend-ops (#10257)
34480dd7ff22fd050fed58b552cc8001aaf968b7ebf54ef9cfc726a799e6f454ac22c4815d037716eda2024-11-13T00:58:57-06:00Jeff Bolzvulkan: Optimize contiguous copies (#10254)
345e89213492d3e01705739789733f0f2d250b4c4498fc393f246c550d2481e53323a47644a94e8d01f2024-11-09T12:47:50+05:30amritahs-ibmggml : optimize llamafile cpu matrix multiplication for ppc64le (#10156)
346841f27abdbbcecc9daac14dc540ba6202e4ffe40d05b3127bd30515955aa4ee2bacdb68ebafe88f42024-11-08T13:47:22+02:00Georgi Gerganovmetal : optimize FA kernels (#10171)
3473bcd40b3c593d14261fb2abfabad3c0fb5b9e3185c333e014059122245c318e7ed4ec27d1085573c2024-11-07T18:19:10+11:00Zhiyuan LiOptimize RWKV6 Operator Naming and Implement Multi-core CPU/ SYCL Acceleration (#10133)
348340736477651095a98a3b10e19b038ec62593a1dd5a409e57fe8bd24fef597ab8a31110d390a63922024-11-04T22:06:31ZEveQ6_K AVX improvements (#10118)
349fc83a9e58479e4dd70054daa7afe5184c1bbe545c5b0f4b5d90297f3e729fca7f78ddb25fcab5ddc2024-10-30T15:00:40+08:00xctanggml : add Q4_0_8_8 RISC-V GEMV and GEMM kernels (#10029)
3508f275a7c4593aa34147595a90282cf950a8536908d8ff715367480b856ad86ac3888e9742b13a6fa2024-10-29T17:52:56+09:00Changyeon Kimggml: Add POOL2D OP for GPU acceleration to the Vulkan backend in the MobileVLM model. (#9763)
3512d3aba9ee8da9c026d54e8a912a1d64f56809be380273a306d07ed95059d6130389deacb3b2d71962024-10-23T17:16:56+03:00Georgi Gerganovllama.vim : bump generation time limit to 3s [no ci]
3524c9388fb96ac2415fbb1239b7ba8346616606e2e873279b1592e433c4d9eb5065091cc98473c7bee2024-10-23T19:33:45+09:00Jun Hee Yoometal : add POOL2D and fix IM2COL (#9943)
353cda0e4b648dde8fac162b3430b14a99597d3d74fafd9909a6481402844aecefa8a8908afdd7f52f12024-10-18T23:18:01+02:00Xuan Son Nguyenllama : remove all_pos_0, all_pos_1, all_seq_id from llama_batch (#9745)
35413dca2a54a394757d56fdd652b9f0df08f44ea22d4c19c0f5cdb1e512573e8c86c79e8d0238c73c42024-10-14T01:49:08+01:00agray3Vectorize load instructions in dmmv f16 CUDA kernel (#9816)
355edc265661cd707327297b6ec4d83423c43cb50a51bde94dd024b632f98428f4bf2ce4832951307792024-10-12T16:14:27+03:00Georgi Gerganovserver : add option to time limit the generation phase (#9865)
356a39ab216aa624308fda7fa84439c6b61dc98b87af536f4c4391bec74c432a924625c04e8c484d3ee2024-10-02T15:49:55+02:00Xuan Son Nguyenllama : reduce compile time and binary size (#9712)
35776b37d1541a880b9645557c8715a343fd074cc5c148844fe97fff4c1563a3111bf238ba4dd22ef562024-10-02T15:21:57+08:00Zhenwei Jingguf-split : improve --split and --merge logic (#9619)
358148844fe97fff4c1563a3111bf238ba4dd22ef563f1ae2e32cde00c39b96be6d01c2997c29bae5552024-10-02T10:14:44+03:00Georgi Gerganovexamples : remove benchmark (#9704)
359cb00020504416606601f8cb35f55ee07b710b4b76c5322481a75f1be54e58a000c3f78484d07f9482024-09-30T09:14:09+02:00Salvatore Mesoracavulkan : mul_mat: fix UB with small warps (ggml/952)
3601b2f992cd2cff0b69e5abe78bb8888d51ed19d67739842703e32cd43443c45e0b4f6647cc4e6b3d62024-09-28T14:32:46+02:00slarentest-backend-ops : use flops for some performance tests (#9657)
3616a0f7794847244fb3b99a983e03137d7e832b58589f9944981010d195e411a9fbfbb19959412f7102024-09-28T14:06:16+02:00Dan Johanssonggml : add run-time detection of neon, i8mm and sve (#9331)
3621e436302188a704ac9ea044af03193648806f19cafbbfaa537a96f562c34df4542930fa951b40d9e2024-09-25T15:12:20+02:00Charles Xuggml : remove assert for AArch64 GEMV and GEMM Q4 kernels (#9217)
363904837e0cb2f5f01bf5d5901b7aa57a026860ae470392f1f81470607ba3afef04aa56c9f655876642024-09-25T11:30:38+08:00Dou Xinpengcann: fix crash when llama-bench is running on multiple cann devices (#9627)
364f0c7b5edf82aa200656fd88c11ae3a805d7130bf1d48e98e4f3316bd2f6b187d288c7b6cb88d5cb32024-09-23T11:42:43-07:00Max Krasnyanskythreads: improve ggml_barrier scaling with large number of threads (#9598)
365424c5d00a9b97dd5559635872db9b57f87c23b02a6809c6a2e8163cba296d4cc0c5cd4bbc80736382024-09-20T19:04:44+03:00Johannes Gäßlerggml/examples: add backend support for numerical optimization (ggml/949)
3667be099fa817e9c53ffb4c3ed7d063e1cffcd675a8b836ae731bbb2c5640bc47df5b0a78ffcb129cb2024-09-17T22:41:38+02:00Michael Podvitskiyllama-bench: correct argument parsing error message (#9524)
367acb2c32c336ce60d765bb189563cc216e57e9fc2a6a3a5c531c73aef85750a847d21e7d4671e723d2024-09-16T13:07:13+02:00Daniel Beveniusllama : rename n_embed to n_embd in rwkv6_time_mix (#9504)
3685c3d0f1824714e9a97fc9b06e046eefcb6ecc7210aadac10c7dd704f8285ddf5a63d6f764cb340aa2024-09-16T06:48:24ZEveggml : IQ4_NL sgemm + Q4_0 AVX optimization (#9422)
3690abc6a2c25272d5cf01384dda8ee8bfec4ba8745bd35cb0ae357185c173345f10dc89a4ff925fc252024-09-13T09:53:38+03:00Georgi Gerganovllama : llama_perf + option to disable timings during decode (#9355)
370d2b496bff4f353a6429f8e833448f071bd237ba7b34e02348064c2f0cef1f89b44d9bee4eb15b9e72024-09-11T10:03:54+03:00Georgi Gerganovbatched-bench : remove unused code (#9305)
3710b4ac75772b744bb0a0d674927587621d1057884fb3f2498156b3140e2050ec9c7bf61372f63ff562024-09-10T15:02:30+08:00Molly SophiaRWKV v6: Add time_mix_decay_w1/w2 in quant exclusion list (#9387)
372b2e89a327457179a34eae4d7de0d412ed945679cdaa9623ab051a8162ae750b150b9522571b55f212024-09-09T09:02:45+02:00Dan JohanssonArm AArch64: Documentation updates (#9321)
3731b9ae5189cd279c6b45e36d43e4f9ccae628d02fe32d0816edfd247784f6780b0bb9ae0bceef5e472024-09-07T20:43:51+02:00Xuan Son Nguyencommon : refactor arg parser (#9308)
374df270ef74596da8f1178f08991f4c51f18c9ee82947538acb8617756a092042ff7e58db18dde05ec2024-09-07T15:16:19+03:00Georgi Gerganovllama : refactor sampling v2 (#9294)
375134bc38ecf3e2c5460581badce289a1ffa680453815b1fb20a53e439882171757825bacb1350de042024-09-07T00:03:01+03:00Aarni Koskelallama-bench : log benchmark progress (#9287)
376815b1fb20a53e439882171757825bacb1350de04409dc4f8bb5185786087f52259ee4626be93f54d2024-09-06T18:59:58+03:00Aarni Koskelabatched-bench : add `--output-format jsonl` option (#9293)
3779bc6db28d011d47a5f318dc4aebbe7927fac462932b2ec88bc44b086f3807c739daf28a1613abde12024-09-05T21:48:47-04:00compiladeggml-quants : ternary packing for TriLMs and BitNet b1.58 (#8151)
378bdf314f38a2c90e18285f7d7067e8d736a14000a581c305186a0ff93f360346c57e21fe16e967bb72024-09-05T02:19:39+02:00slarenllama-bench : fix NUL terminators in CPU name (#9313)
3798962422b1c6f9b8b15f5aeaea42600bcc2d44177b69a480af4db8ffd6cbb2efe7ed8132bc7d390732024-09-03T20:58:54+03:00Aarni Koskelallama-bench : add JSONL (NDJSON) output mode (#9288)
38048baa61eccdca9205daf8d620ba28055c2347b64f1485161e58d562099dd050f8ac3a9ea9f4cd7652024-09-02T22:08:38+02:00Xuan Son Nguyenserver : test script : add timeout for all requests (#9282)
3818f1d81a0b6f50b9bad72db0b6fcd299ad9ecd48ca47667cff41f5a198eb791974e0afcc1cddd32292024-09-01T22:38:17+08:00Molly Sophiallama : support RWKV v6 models (#8980)
382ea5d7478b1edcfc83f8ea8f9f0934585cc0b92e349271efbaf3f7a4ae52c4ca299b6d4e82598a97d2024-08-31T13:50:35+05:30Srihari-mcwsgemm : improved Q4_0 and Q8_0 performance via 4xN and Mx4 gemm (#8908)
38342c76d1358021ccdbe8ba89109c143dd7ae166df9f7d4bcf5c27d37b0c7da82eeaf9c1499510554b2024-08-29T19:20:53-04:00Faisal ZaghloulThreadpool: take 2 (#8672)
384f12ceaca0c7b59def30b7a832a6904df7ed3f4f7436787f170329b3f549e6c2c46593d2af8482e7c2024-08-26T11:03:30+02:00slarenggml-ci : try to improve build time (#9160)
385436787f170329b3f549e6c2c46593d2af8482e7c93bc3839f980ff14be86efe408b4cd7e89b268352024-08-25T23:09:53-07:00Justine Tunneyllama : fix time complexity of string replacement (#9163)
3862f3c1466ff46a2413b0e363a5005c46538186ee650addec9a532a6518146ab837a855048506273162024-08-21T04:00:00+09:00Changyeon Kimllava: Add ACC OP for GPU acceleration to the Vulkan backend in the LLAVA CLIP model. (#8984)
387d5492f0525fa533817a67e93a4bde9d71d81cf58234b30676a97ce227b604c38beb9dcaca406dea92024-08-15T10:11:11+03:00Georgi Gerganovci : disable bench workflow (#9010)
3885fd89a70ead34d1a17015ddecad05aaa2490ca4698a532d474c73d3494a5353024cb6a4fbbabbb352024-08-14T18:32:53+02:000cc4mVulkan Optimizations and Fixes (#8959)
3897c5bfd57f83fd3630934cfa70892aa4022d3faf76e02327e8b7837358e0406bf90a4632e18e278462024-08-11T10:09:09+02:00Markus TavenrathOptimize Vulkan backend for better CPU performance and less GPU synchronization overhead. (#8943)
390506122d854c5d05b4a3d45a294f14bd4c02d9868725e3d94379d5b619c027347308bccf2e0ead89f2024-08-07T09:01:06+08:00Zhenwei Jinllama-bench : add support for getting cpu info on Windows (#8824)
391bc0f887e159c0d78c28121e2c8b5c58094170875b42978e7e4d56eaaa93588414e804d9fbbc3cae22024-08-05T21:10:37+08:00wangshuai09cann: fix buffer_num and runtime speed slowly error (#8865)
392a3738b2fa7c60ef2c4592435d1aa7fb8f1f69c3e655858ace0cf2720e56eb01f84ad05e0c94ada3c2024-08-04T17:28:08+02:000cc4mvulkan : implement Stable Diffusion operators (ggml/904)
3930d6fb52be0c1b7e77eb855f3adc4952771c8ce4c978ba3d83d17b10fdf9807006048432b5b3769fc2024-08-04T14:17:16-04:00Brandon SquizzatoInstall curl in runtime layer (#8693)
394ecf6b7f23e664afd7ff856ec39034240ce438daa01aae2b4975b57a265ce8194928fd87f2d71027e2024-08-04T03:55:03-07:00Brian Cunniebatched-bench : handle empty `-npl` (#8839)
39576614f352e94d25659306d9e97321f204e5de0d3b72c20b85c1029d135022d39e9a20d4807c118932024-08-04T01:34:41+09:00jdomkeggml : reading the runtime sve config of the cpu (#8709)
396ed9d2854c9de4ae1f448334294e61167b04bec2a398ede5efeb07b9adf9fbda7ea63f630d476a7922024-07-31T15:51:06-04:00Clint HerronBuild: Fix potential race condition (#8781)
397268c5660062270a2c19a36fc655168aa287aaec27e72aa74fd676a093eb9970e761085ec22734c712024-07-30T23:35:30+03:00Someonenix: cuda: rely on propagatedBuildInputs (#8772)
398c887d8b01726b11ea03dbcaa9d44fa74422d007675af08c475e285888f66556d0f459c533b7deb952024-07-30T14:56:51+08:00zhentaoyu[SYCL] Add `TIMESTEP_EMBEDDING` OP (#8707)
399a05ca9369716a8319014cd1fc365980d43f8aae99f77d899b7b0d56496f679e54b797da6199fed8e2024-07-25T00:54:08-07:00Mahesh Madhavggml : loop tiling optimizations for scalar path (ggml/898)
400b5e95468b1676e1e5c9d80d1eeeb26f542a38f4292090eca212650727e38b335c1d4accfbcc9b79c2024-07-27T05:03:45-07:00Jeffrey Morganllama : add support for llama 3.1 rope scaling factors (#8676)
40146e47417aa4f18c08738afd4d9a3e838e97ca03fe7e6487ba06634edf58dfdf9673bad9df41b445a2024-07-23T10:50:40+02:00Jeroen MostertAllow all RDNA2 archs to use sdot4 intrinsic (#8629)
402566daa5a5b38018b2727950bbd280239adb981b66f11a83e4e7700fdf353ed4a29599cb662c792f62024-07-22T15:44:53+02:00Jiří Podivín*.py: Stylistic adjustments for python (#8233)
40322f281aa16f44d8f6ec2c180a0685ff27e04e714328884f4219c0228673cf1870ac63987fb4f9fd02024-07-20T22:09:17-04:00M-Aexamples : Rewrite pydantic_models_to_grammar_examples.py (#8493)
4047acfd4e8d55082c1b597dfc3ffe04fb5d530c6dc97bdd26eee11fe109dec00de75690ceef61c03f22024-07-15T23:13:10-04:00compiladeconvert_hf : faster lazy safetensors (#8482)
405808aba39161e5d7ca2ff24110b5aa14d2e536988a977c115448e40856fb9cbe3ceb6d8ce802553b02024-07-11T16:47:47+02:00Johannes GäßlerCUDA: optimize and refactor MMQ (#8416)
406dd07a123b79f9bd9e8a4ba0447427b3083e9347af4444d992c16b6b9442f4770c7c3a10b19a083432024-07-10T12:35:18-04:00Clint HerronName Migration: Build the deprecation-warning 'main' binary every time (#8404)
4070f1a39f3439825acf7e3a1663566d410be15217083321c6958acf20747d288031174cc1bf8816e332024-07-10T07:14:51-05:00Dibakar Gopeggml : add AArch64 optimized GEMV and GEMM Q4 kernels (#5780)
408fd560fe680c72fd0a0af2bc8881add20ad919071e500d6135ac42c4a23baf6a9a1a934dc023e5c7d2024-07-09T11:58:44-07:00Andy SalernoUpdate README.md to fix broken link to docs (#8399)
409e500d6135ac42c4a23baf6a9a1a934dc023e5c7da03e8dd99d3954e7547137936c5a2a3b348bdb7f2024-07-09T11:54:43-04:00Clint HerronDeprecation warning to assist with migration to new binary names (#8283)
410470939d483d1c89b7292f78bac1fd27c42c171ce6f0dbf6ab087bcd286fb78560099ca04583167352024-07-08T03:26:53-04:00Kevin Wangcommon : preallocate sampling token data vector (#8363)
4113fd62a6b1c9ca7b7c0093e984cc9c133c6f2726da8db2a9ce64cd4417f6a312ab61858f17f0f85842024-07-07T15:04:39-04:00compiladepy : type-check all Python scripts with Pyright (#8341)
412905942abdba5ba0b28a1b0805e51e4f818c54bc9b5040086d436e7345e4fa33a5b9558060c75603f2024-07-07T20:52:10+08:00toyerllama : support glm3 and glm4 (#8031)
4130a423800ffe4e5da3d83527ef3473da88cd78146d12f781074b92589a72a36ffabb583933f7b9dc02024-07-05T07:06:09ZDanieleCUDA: revert part of the RDNA1 optimizations (#8309)
414f09b7cb609d80b8031803f89255991dc8b35db69a38b884c6c4b0c256583acfaaabdf556c62fabea2024-07-05T10:32:29+08:00Neo Zhang Jianyurm get_work_group_size() by local cache for performance (#8286)
415d23287f122c34ebef368742116d53a0ccb2041ee5f2d4e60e202aabee10051e6615bb821e51787be2024-07-03T23:02:58ZDanieleDefine and optimize RDNA1 (#8085)
416cb5fad4c6c2cbef92e9b8b63449e1cb7664e4846dae57a1ebc1c9bd5693ab999e19d77c5506ae5592024-07-01T20:39:06+02:00Johannes GäßlerCUDA: refactor and optimize IQ MMVQ (#8215)
4179a590c82262dd518137f85406e65e452fdf2aca352fc8705a0617452df08333e1161838726c322b42024-06-24T12:41:23+02:00Johannes GäßlerCUDA: optimize MMQ int8 tensor core performance (#8062)
41895f57bb5d5b18ef0beb2702a0d6c06e46804075ce112b610a1a75cb7fa8351e1a933e2e7a755a5ce2024-06-24T03:07:59+02:00slarenggml : remove ggml_task_type and GGML_PERF (#8017)
419a927b0f3dd9a86ee042cd2bdcc8c9da4a855926b80ea089d771f0c2d97afa8bead80ded412f600d72024-06-21T08:51:28+03:00Georgi Gerganovllama : optimize long word tokenization with WPM (#8034)
42061665277afde2add00c0d387acb94ed5feb95917b96f9afb0d58b003ac8d1d0c94cd99393a3bc4372024-06-18T14:00:14+02:00Ulrich DrepperAllow compiling with CUDA without CUDA runtime installed (#7989)
4216a2f0b3474d479bda4ac2ee7cfd5dcdcf0be1f7921be9cab94e0b5b53cb6edeeebf8c8c799baad032024-06-17T16:10:15+02:00Markus TavenrathImplement non-mapped async IO for CUDA on Windows. (#7896)
422b5fcf8ef5c29df53cfff60e180b4992a3b2332a6398105ff4373eea385ea8e8625cb417b2ae511342024-06-16T16:53:11+08:00Hong Bo PENGggml : fix and optimize ppc64le (ggml/849)
423e65bbf606c61f49dc06c7ac060cd5ba7ae4460256fcd1331efbfbb89c8c96eba2321bb7b4d0c40e42024-06-14T16:47:41+03:00Radoslav Gerganovllama-bench : fix RPC indication (#7936)
424f578b86b2123d0f92afbaa98a031df4d4464e5821c641e6aac5c18b964e7b32d9dbbb4bf5301d0d72024-06-13T03:11:35+02:00slarenmove BLAS to a separate backend (#6210)
425148995e5e57b313cce2672f75610db58c6327a514bfe50f741479c1df1c377260c3ff5702586719e2024-06-11T14:45:40+02:00Johannes Gäßlerllama-bench: more compact markdown tables (#7879)
4265795b941827fdec6c1662986de962badff456718ed9f2521185706481501a5e6d5315397b11802ff2024-06-08T22:47:25-04:00compiladeconvert-hf : match model part name prefix and suffix (#7687)
42755b2d0849d3ec9e45e4a4d9e480f5fa7977872a6f5d7b268ec4bf8628aa6ccc9f6631d0230dde76f2024-06-06T10:07:06+01:00Olivier Chafikgrammars: x{min,max} repetition operator (#6640)
4281442677f92e45a475be7b4d056e3633d1d6f813b554c247caffed64465f372661f2826640cb104302024-06-04T21:23:39+03:00Georgi Gerganovcommon : refactor cli arg parsing (#7675)
429adc9ff384121f4d550d28638a646b336d051bf42987d743d6bc4cee4bde6820733ea33a2abc0afac2024-06-04T14:32:42+02:00slarenllama-bench : allow using a different printer for stderr with -oe (#7722)
4302ac95c9d5678d05e253691fb1f26471675bff5ad750f60c03e4d3f53fa51910551ce87a3d508d2d72024-06-01T21:50:18+05:30HanishKVCSimpleChat: Simple histogram/repeatMatching driven garbageTrimming, Settings UI, Streaming mode, OpenAi Compat (Model, Authorization Bearer), Save/Restore session, Auto Settings UI (#7548)
431c8047d538f3addab40e3112be60bb92e70ce1a5030e238b246f8002cc6eb7cb79afe242243f1f66d2024-05-31T16:26:21+02:00Johannes Gäßlerscripts: update compare_llama_bench.py [no ci] (#7673)
432210d99173dc82aafb48f6e39d787c387951fe3a987bdf2a199acd62e19814d7a4d0500a04a7f09f32024-05-29T14:45:44+03:00Radoslav Gerganovllama-bench : add support for the RPC backend (#7435)
433b9adcbbf92fc7096bee23fe61496d25652ebf7659588f196b1d7b21bdff013fcf958c249576b26192024-05-26T06:26:34+05:30HanishKVCSimpleChat Completion Mode flexibility and cleanup, Settings gMe, Optional sliding window (#7480)
4341e374365d170b7f692fd7753c145e21bc14486c8197ff91462dd05bb9a3be03578114abf0c3555362024-05-22T23:23:21+05:30HanishKVCSimpleChat: a simple and dumb web front end for testing /chat/completions and /completions end points and try chat (#7350)
435b18532a4efeca8796fea8e36195c81cbfd596a4afcda1128bc5f8eb7e1811708fe9d9867b9aec8152024-05-22T16:10:46+02:00slarenphi3 : duplicate rope factors in each layer (#7447)
43665c58207ece92ad213f4bfd0f91dcb2dfb664f5b1cc0155d04918cb3017afa472acea51b77483c4a2024-05-20T15:19:21+08:00junchao-loongsonggml : add loongarch lsx and lasx support (#6454)
4371cc0155d04918cb3017afa472acea51b77483c4ae932094d58f513d5996c3efc9f6fed8238894c572024-05-20T10:16:41+03:00Georgi Gerganovserver : tuning tests (#7388)
438d273c1402b25086fd91aef2467ac13f2e49fa0ea27b040691cbe45314147c2745e891a38e9c048d42024-05-17T15:11:45+03:00Aarni Koskelapy : convert-hf-to-gguf-update improvements (#7340)
439934266c0e0b2aa9781fdba2deb112c161ff038a99c4fdcbec8c7fcc428e723b0d8a1cf1f351ba6422024-05-17T02:58:52-04:00Justine Tunneyggml : rewrite silu and softmax for cpu (#7154)
44013ad16af1231ab2d245d35df3295bcfa23de13058f7080bf48828b538bc9387c3d150bbd4fb4cf2d2024-05-15T19:47:36-07:00Max KrasnyanskyAdd support for properly optimized Windows ARM64 builds with LLVM and MSVC (#7191)
441583fd6b000ec9ad1b465b5c98524f4a0ae3880779f773486ab78d65f5cca3f7e31c862b7043bf7212024-05-15T08:44:16+02:00Johannes Gäßlerserver bench: fix bench not waiting for model load (#7284)
4420d26d8ccd8caebab75af697c0275f599075fdacf4f0263633b40e94e8b69fd6e7e4395cfedfd5c122024-05-12T17:17:18+08:00Hong Bo PENGggml : optimize for ppc64le using VSX intrinsics (ggml/784)
443cbf75894d256f1861f6409565db599365de3d4b80d5cef78aeafae4d4e6d56e2d4bcda771af58cc92024-05-13T08:04:29+08:00Neo Zhang[SYCL] Add oneapi runtime dll files to win release package (#7241)
444e849648888a11de13aaaa4cb2eda3f5a9c7b444d18e437665ce626dddbd79119aa7498493e7cb13b2024-05-10T18:03:54+02:00slarenllama-bench : add pp+tg test type (#7199)
445fd9f92b154850014146f61717cd292a59a5cee5a22842164bcae3251b81ad9e497a16ef66833cb9e2024-05-09T13:03:29+02:00Daniel Beveniusllama : update llama_timings.n_p_eval setting (#7160)
446bc4bba364fb96d908f2698e908648df5e6f55e02c12452c7aec8a02264afc00196a13caa591a13ac2024-05-08T21:55:49+01:00agray3Introduction of CUDA Graphs to LLama.cpp (#6766)
447acdce3cdef6fc2f0b7b5623231fd7762c0884d1c3855416027cb25d9a708ffa5581cf503a87856a62024-05-08T18:54:39+10:00Briancompare-llama-bench.py: add missing basicConfig (#7138)
4483855416027cb25d9a708ffa5581cf503a87856a6c0e6fbf8c380718102bd25fcb8d2e55f8f9480d12024-05-08T02:30:09-04:00Justine Tunneyggml : introduce bfloat16 support (#6412)
449858f6b73f6e57a62523d16a955d565254be889b4b3a995b416e13ae3123a117a743e11d0ede0ca4c2024-05-06T11:12:14-07:00William TambelliniAdd an option to build without CUDA VMM (#7067)
450628b299106d1e9476fdecb3cbe546bf5c60f1b898f8acc8683a00ce40fa5a81161a079d2167126e62024-05-05T07:17:47-05:00kunnisAdding support for the --numa argument for llama-bench. (#7080)
4518f8acc8683a00ce40fa5a81161a079d2167126e6ca3632602091e959ed2ad4c09c67a7c790b10d312024-05-05T13:38:55+02:00Sigbjørn SkjæretDisable benchmark on forked repo (#7034)
452a2ac89d6efb41b535778bfeaecaae8fe295b6ed3433def286e98751bf17db75dce53847d075c0be52024-05-04T05:36:41+10:00Brianconvert.py : add python logging instead of print() (#6511)
4539c67c2773d4b706cf71d70ecf4aa180b62501960952d03dbead16e4dbdd1d3458486340673cc24652024-04-30T12:16:08+03:00Georgi Gerganovggml : add Flash Attention (#5021)
454b8a7a5a90fd3187175d84227dad705ade395ba46d2c898f746a527f09effb061829e68b2e1812a282024-04-29T17:02:45+01:00Olivier Chafikbuild(cmake): simplify instructions (`cmake -B build && cmake --build build ...`) (#6964)
4555790c8dac1a4f0aa80b4efee3b962d8c04c829e846e12c4692a37bdd31a0432fc5153d7d22bc7f722024-04-26T09:26:16+02:00Pierrick Hymbertbench: server add stop word for PHI-2 (#6916)
4565cf5e7d490dfdd2e70bface2d35dfd14aa44b4fb40f74e4d739e9250431cf339ae7588b28d8d06632024-04-21T18:48:53+01:00Olivier Chafik`build`: generate hex dump of server assets during build (#6661)
4579958c81b798a5872087b30b360e4674871f2479e8b1b1f4982d3e9b994308d05a1c8b9e45c23edb52024-04-19T09:35:54ZnopperlImplement the OLMo architecture (#6741)
4588cc91dc63c0df397d644a581b2cbeea74eb51ae0dbceec87c0221ec952e69448df6a71f1372a74872024-04-16T14:55:30-04:00Justine Tunneyggml : add llamafile sgemm (#6414)
459de17e3f7455dc7fd298cc61d86798533b9ca7a29b5e7285baffb0da8a6619567b52d8e67de41291d2024-04-14T10:42:29+08:00Neo Zhang Jianyufix memcpy() crash, add missed cmd in guide, fix softmax (#6622)
460ab9a3240a9da941fdef5cd4a25f2b97c2f5a67aafbbc030ba93561fac842af994c5c6c4c1147f13b2024-04-12T19:43:38+01:00Olivier ChafikJSON schema conversion: ⚡️ faster repetitions, min/maxLength for strings, cap number length (#6555)
46104a5ac211ef40936295980b7cdf0ba6e97093146f7001ccc5aa359fcf41bba19d1c99c3d25c9bcc72024-04-11T21:44:50-04:00Clint HerronOptimization: eliminate addition of redundant stacks when advancing grammar. (#6616)
46257dd02c44b2a0eb79e28f6c5eb8242a5d2d3174d75cd4c77292034ecec587ecb401366f57338f7c02024-04-06T10:31:33-04:00Clint HerronTests: Added integration tests for GBNF parser (#6472)
46375cd4c77292034ecec587ecb401366f57338f7c0a8bd14d55717754a1f48313a846a2b16fa998ad22024-04-06T05:40:47+02:00Pierrick Hymbertci: bench: support sse and fix prompt processing time / server: add tokens usage in stream OAI response (#6495)
46487e21bbacd830437ab653cf03b6f26d45c15395d1b496a745c315022df2d919374052e6004ced8d32024-04-06T01:34:53+07:00Ting Sunbench : make n_batch and n_ubatch configurable in Batched bench (#6500)
4657dda1b727ef1730783a6077136d28b83e70dd397c666ba26c39d5c07e07b4e1e411332f408e309ad2024-04-05T01:30:53+09:00Minsoo Cheongci: exempt master branch workflows from getting cancelled (#6486)
4668120efee1d9931b514aeb5a047209d576f23286ca74401f0e5ebb15fa4d8b6619d1baa6ea91791232024-04-04T16:59:04+02:00Pierrick Hymbertci: bench fix concurrency for workflow trigger dispatch with sha1 (#6478)
4677a2c92637ae265654a68f62e6a7610b358255d3f4bcd6b959ca3991084ad1d8464caf2a734e29b1d2024-04-04T11:57:58+02:00Pierrick Hymbertci: bench: add more ftype, fix triggers and bot comment (#6466)
4685fb1574c8112c757fc202fdae279da883f34e61060cdf40cc32f0ad4cb11e0ca8fd38f3b93d8d6402024-04-03T13:22:57-07:00FattireA few small fixes to server's README docs (#6428)
46933a52448061cfd2ea44da9e6cb30b2ec22e2f6d0226e819371eec0f298d9075198394a07b23ecfa92024-04-01T13:30:43+02:00Johannes Gäßlercompare-llama-bench.py: fix long hexsha args (#6424)
47037e7854c104301c5b5323ccc40e07699f3a62c3ec342d070c64a1ffe35d22c1b16b672e684a302972024-03-30T11:36:07+01:00Pierrick Hymbertci: bench: fix Resource not accessible by integration on PR event (#6393)
471057400a3fd457f4f214684eeb171444663b47a23b75c38166cf0c66793a32d5c3d6cb69929dd083d2024-03-29T08:23:22+01:00Daniel Beveniusllama : remove redundant reshape in build_kv_store (#6369)
47228cb9a09c4d10a489be1238abe7a858dcd4d65f2cfc4d75df6399b36153ef739f2c1abee4c114bb82024-03-28T11:27:56+01:00Pierrick Hymbertci: bench: fix master not schedule, fix commit status failed on external repo (#6365)
473a016026a3ac16d8c9b993a3573f19b9556d67de453c7ec53d5eca26b2c0c648605543a5fa6c128172024-03-27T20:26:49+01:00Pierrick Hymbertserver: continuous performance monitoring and PR comment (#6283)
474557410b8f06380560155ac7fcb8316d71ddc983755c1b2a3bbd470e9e2a3a0618b92cf64a885f8062024-03-26T10:46:41-04:00compiladellama : greatly reduce output buffer memory usage (#6122)
47555c1b2a3bbd470e9e2a3a0618b92cf64a885f806e097633f63fdd26d492844f7eff056e4083fd9eb2024-03-26T15:21:27+01:00KawrakowIQ1_M: 1.75 bpw quantization (#6302)
476cfd3be76e37dab92c846d75a2421178f20db4a115b7b0ac8dfdd800c0fd0dc69b69991e8cb19fb462024-03-21T13:59:38+01:00Kawrakowggml : same IQ4_NL quantization for CPU/CUDA/Metal (#6196)
4775b7b0ac8dfdd800c0fd0dc69b69991e8cb19fb461943c0198125a0da1a200390e82cf461f9080d992024-03-21T11:50:43ZOlivier Chafikjson-schema-to-grammar improvements (+ added to server) (#5978)
47876aa30a26353f597e4fbe3cf776772ae812af89ac5b8595e3f4f4ed319ef71c9c9d868d1b7a276262024-03-21T08:27:57+01:00KawrakowAdd ability to use Q5_0, Q5_1, and IQ4_NL for quantized K cache (#6183)
479bd60d82d0cc8b6852ec535495a5042dbdf05de246c0b287748327741b113d7d6018b68c63039b1c52024-03-20T01:33:49-04:00Jared Van Bortelserver tests : more pythonic process management; fix bare `except:` (#6146)
480a56d09a4407f29c21e149b44fd5308f83aa1cb09d84c48505f60bcd358b82a751d40418c4d2356432024-03-16T13:20:53+01:00Pierrick Hymbertci : close inactive issue with workflow (#6053)
481b0bc9f4a9da7c19f4779106ea83b23feca7475664755afd1cbd40d93c017e5b98c39796f523453142024-03-15T09:22:24+01:00slarenllama-bench : use random tokens to improve accuracy with mixtral (#6069)
4826e0438da3cc95b89cdbf55f45fa4e324d9076792727107707a73b3dc8a497cf9fc9405722c16dd2b2024-03-14T14:29:32-04:00Steve Grubbgguf : fix resource leaks (#6061)
48343241adf22e8231ffaf3827d2c9310cc0ffd5ac5a44bc969e4cd62ca9f4332e17fe3c51f2093e7c62024-03-14T12:15:39+01:00Pierrick Hymbertserver: disable debug release type sanitizer, simplify trigger (#6047)
4842c4fb69246834503db7b78bcbedcef506bbc60c43ca23481dd309bd51cc31c73a4cc34f922cc372f2024-03-14T11:56:48+01:00Michael Podvitskiyllama : optimize defrag moves + fix fragmentation calculation (#6037)
485f30ea47a87ed4446ad55adb265755dc9102956a2d8fd0ccf6ac8b07791ffd1575eed436930854ae32024-03-13T18:54:21+01:00slarenllama : add pipeline parallelism support (#6017)
48644ca159faf4fbe1a7ace13a962845ba7cdfd95ec05b06210c954491cf0f12034b0a62bd4d69ce78b2024-03-11T16:53:15+01:00Kawrakow1.5 bit: we can do even better (#5999)
487be858f620508385ad12d0e5e862010e666ca729cef3ced26a3817d92890b97b83acaeb018ade02d02024-03-11T07:51:49+01:00KawrakowBetter 1.5 bit quantization (#5971)
488621e86b331f8b0e71f79fd82a4ae1cd54c3e439677d1ac7e00bf049b9f2bba1b5a310a78318c49c42024-03-09T23:41:49+01:00Pierrick Hymbertserver: benchmark: chat/completions scenario and other llm servers comparison (#5941)
489c2101a2e909ac7c08976d414e64e96c90ee5fa9e515f7d0d4fce41c752fc253acf30707c3be2531e2024-03-08T17:31:00-05:00compiladellama : support Mamba Selective State Space Models (#5328)
49076e868821a94072fbc87cb1fcca291694319eae8e457fb3540e0aaec47cfde0abf784c213f9216ee2024-03-08T12:25:04+01:00Pierrick Hymbertserver: metrics: add llamacpp:prompt_seconds_total and llamacpp:tokens_predicted_seconds_total, reset bucket only on /metrics. Fix values cast to int. Add Process-Start-Time-Unix header. (#5937)
4916cdabe652695167263c8b447520987b11856f7ca89fb735fcfd21781a8194b211cf32824beb3f71f2024-03-07T16:32:38+02:00Georgi Gerganovllama-bench : add embeddings option (#5924)
4922002bc96bf2cbf5ab981a17d7e994d817c9801f5ceca1aef0738b57951cd12c603c3477e75312dec2024-03-07T11:41:53+02:00Georgi Gerganovserver : refactor (#5882)
493652ca2bded3c818320d92c70d2b67f64bdbff5e5bd836944f826f07e19b7edcf994a78728da49c1c2024-03-05T22:27:29+01:00slarencompare-llama-bench.py : remove mul_mat_q (#5892)
49461d1c88e155515dd03940913a5707ea84a8b119b21b08674331e1ea1b599f17c5ca91f0ed173be312024-03-05T13:33:42+01:000cc4mVulkan Improvements (#5835)
49521b08674331e1ea1b599f17c5ca91f0ed173be316a87ac3a52668e117d97bcea07b529c93188b3032024-03-05T16:08:35+08:00Neo Zhang Jianyu[SYCL] fix mul_mat fault in CI/unit-test (#5862)
4967d43c585dc174bb586775c22c15e5db9242b5b4b82f3e668adafba647de703f835991e91a96b5ac42024-03-03T20:23:52+08:00leejetadd some new ops, fix some operators and add batch operations to certain operators. (ggml/747)
4979731134296af3a6839cd682e51d9c2109a871de54a6e2d6142ab815c964924896891e9ab3e0506322024-03-02T22:00:14+01:00Pierrick Hymbertserver: tests: passkey challenge / self-extend with context shift demo (#5832)
4983ab8b3a92ede46df88bc5a2dfca3777de4a2b2b69600d59e010c18f5872580a21734ea1bf1968d042024-03-01T12:39:06+01:00Pierrick Hymbertllama : cleanup unused mmq flags (#5772)
4999600d59e010c18f5872580a21734ea1bf1968d045cb02b4a012bb16c6c699c0c62c05ffa653eee0f2024-03-01T03:15:36-06:00Douglas Hanleyunicode : switch to multimap based nfd_map (#5799)
50087c91c07663b707e831c59ec373b5e665ff9d64a317709b2a81dbaf87850202686ec5bb2602a504e2024-02-28T21:44:21+02:00Georgi Gerganovci : reduce 3b ppl chunks to 1 to avoid timeout (#5771)
5010becb22ac05b6542bd9d5f2235691aa1d3d4d307c24a2a6e6005e5d424301525a42ba45a4a362d302024-02-27T16:34:24+02:00KawrakowIQ4_XS: a 4.25 bpw quantization (#5747)
502e3965cf35aac00d4e24998c8a3d0093ae1d98bd38b350356b28f782deab63d8b0e9ae103ceb25fcd2024-02-25T22:48:33+01:00Pierrick Hymbertserver: tests - slow inference causes timeout on the CI (#5715)
5034c4cb30736582cacb1a164a9d4bc8e17b1014be7525213d2f5da1eaf4b922b6b792cb52b2c6133682024-02-24T16:23:52+02:00KawrakowIQ3_S: a much better alternative to Q3_K (#5676)
50470847553963c85e86051d06df848236829f5f9514480542b2271ba1438f0daff8e5f3a74b1dc86092024-02-19T09:31:59+01:00Daniel Beveniusllava : avoid changing the original BakLLaVA model (#5577)
505fc0c8d286a533363a9a663510b62af85ffad58b3bd2d4e393b2b7d2a1b2e201058e26017c9728ead2024-02-18T17:19:23+01:00Daniel Beveniusllava : update surgery script to not remove tensors (#5536)
5068f1be0d42f23016cb6819dbae01126699c4bd9bc6e4e973b2615f8d390b1c4f4a7e05a119078bb0f2024-02-17T23:04:16+02:00Georgi Gerganovggml : add ALiBi support for ggml_soft_max_ext (#5488)
507d2819d5577b35507be83d0c3f4d2d3c0ab1488ca4cb072769804c77ab466bc8351c76ede9d5ba49d2024-02-16T15:14:40+02:00Georgi Gerganovscripts : add helpers script for bench comparing commits (#5521)
5089060a1e9dfca6038906e819be5fa42217f49028c9350a1cf21b1492c69b20175b73a419b897d6a3a2024-02-15T16:49:01+01:00slarencuda : print message when initialization fails (#5512)
5090d4177126b0556e202efb85bf3f768be810764007930a8a6e89a04c77c51e3ae5dc1cd8e845b6b8f2024-02-15T09:01:57+01:00Elbiosllava : fix memory management bug (#5491)
510704359e29985a06a389337a2617b7f3fa8eff908594fca3fefe27b8e95cfb1656eb0e160ad15a7932024-02-15T17:11:15+11:00Neuman Vongvulkan: Find optimal memory type but with fallback (#5381)
51149cc1f7d67de2da99f3ac185f9ff1319b7bf35f899b8b43d7b185a6483f28cf798a2d968b2e16ca72024-02-13T13:01:29+02:00Georgi Gerganovbert : add tests + fix quantization (#5475)
51285910c5b30f6e268321be8df044f5528a6efac52139b62a839825ef20084ed75ed624db7a5ad554a2024-02-11T15:35:50+02:00Georgi Gerganovmain : ctrl+C print timing in non-interactive mode (#3873)
513a07d0fee1f05c5c1dc49948ae1a3293db017275fe4640d8fdf56f14a6db3d092bcd3d2d315cb5d042024-02-11T07:22:33-06:00snadampalggml : add mmla kernels for quantized GEMM (#4966)
514e4640d8fdf56f14a6db3d092bcd3d2d315cb5d04907e08c1109f498b01036367804cff3082c445242024-02-11T12:44:51+01:00Johannes Gäßlerlookup: add print for drafting performance (#5450)
5154b7b38bef5addbd31f453871d79647fbae6bec8ae00d2a62dd1441e3b089570ec06d05c18800d3682024-02-10T05:30:19+11:00Neuman Vongvulkan: Set limit for task concurrency (#5427)
5166fdfa2ecc684000a25a4ad91823bc82a6652b645a2d60c9158435ae9a6f14632f07f1acf7a3becef2024-02-05T10:46:06+02:00Kawrakowiq2_xxs: tune quantization (#5320)
5173cc5ed353c07201d8d5b98b0a4713ab633da6d0460ecf099eddfe70fec797ef6790572e452054add2024-02-03T20:14:59+01:00Johannes Gäßlermake: fix nvcc optimization flags for host code (#5309)
518e920ed393d989ed35625ddaf182ebb52cda07fcd52bb63c7082c859c3f1dfc527227e6a95b299c7c2024-02-03T18:15:00+01:000cc4mVulkan Intel Fixes, Optimizations and Debugging Flags (#5301)
519af3ba5d94627d337e32a95129e31a3064c459f6be1e721094d8169636d55f68efe37f222cd3f06772024-02-02T15:53:27+08:00Neo Zhang Jianyu[SYCL] update guide of SYCL backend (#5254)
520128dcbd3c9c4b12f42b560a4430427d7b28286284d0924a8902010d31bd737b6f1f594943d120d0f2024-02-02T03:48:53+08:00Neo Zhang Jianyuadd --no-mmap in llama-bench (#5257)
521e8dc55d0065d076d4c20f3c4bfca562701b4edfee0085fdf7c758f0bc2746fc106fb29dd9df959de2024-01-30T19:04:37-05:00Jared Van Bortelkompute : llama-bench support and ggml_cpu_has_kompute() (#5226)
5228e14e3ddb3744566aef7bc0fa734180e47ae6bdff4d7e5497485ce6ce0e322533930b7da4657dd2d2024-01-30T15:15:07+02:00KawrakowFaster AVX2 dot product for IQ2_XS (#5187)
523f4d7e5497485ce6ce0e322533930b7da4657dd2d2256f36b79a932a478d4dcdf02c1e5a60056e5f32024-01-30T15:14:12+02:00KawrakowSOTA 3-bit quants (#5196)
5242307523d322af762ae06648b29ec5a9eb1c730320f648573dde61c510560f68244f70ece7e60d8c12024-01-28T18:03:59+01:000cc4mggml : add Vulkan backend (#2059)
5250f648573dde61c510560f68244f70ece7e60d8c1b764b8f1d079ba44d912801ce6d29bd0d94d51cf2024-01-28T21:26:23+05:30Abhilash Majumderggml : add unified SYCL backend for Intel GPUs (#2690)
5267032f4f6349c17a8352f9f93f7d2122f45469e595f1925a8cef81eb9b372faaae34b0dd76d5361d42024-01-26T11:17:59-06:00snadampalggml : update softmax n_task calculation (#5126)
5275eaf9964fc797d4585c214db32a463d557f3ed33d292f4f2047963f558dd516f1baaa71793e9acf22024-01-26T05:06:22+09:00l3utterflyllama : dynamic temperature sampling (#4972)
5283ce7e8f8e7ccfce07e5947ac5f1f3f4628cf68eab2d80e105a59b54822edf7ce7f3ed5f317e96e212024-01-22T21:09:35+08:00XiaotaoChenllava : MobileVLM support (#4954)
529726c0fa9a2da976e9c5d5c51e185d9dd453fc9e5942c0107a7301434c0a5e7da46bc4cf2393aa5562024-01-21T08:01:20+02:00KawrakowSlightly faster imatrix (#5050)
53077bc1bbd05f0c31cb45773eb5eb59b9ff2b07e1b48e2b1337257bb77573bf76cfffcff3a5efa87042024-01-20T08:11:31ZHerman Semenovcmake : add support for ccache (#5002)
531381ee195721d8e747ee31a60c0751822b3072f02a5cacb22b2114fd9adf61c00cbb237384d86bced2024-01-19T13:20:50-05:00Uzo Nwekefinetune : fix ggml_allocr lifetimes (tmp workaround) (#5033)
5327051aacfac0057fa5fac9ea46c55bffc3892d8102b3b999cacc7ad1207c32fbdf3479a19c06e1a342024-01-19T11:39:11+02:00Kawrakowwinogrande: evaluate log-probs in parallel (#5036)
5333e945cc1e9c06d2001031360e4e303e9548fb02cad19812cda4062c9f154ef16315df41fbe6a770a2024-01-18T19:18:21+02:00KawrakowHellaSwag: speed up by parallelizing log-prob evaluation (#5020)
534ba69bbc84ced580fe4fdb0713ca2d95634325b7a44a1a4a41a4c0b03afaa7d9e06bcbc7cf95aa1e62024-01-17T18:46:30+02:00Georgi Gerganovimatrix : offload to GPU support (#4957)
53544a1a4a41a4c0b03afaa7d9e06bcbc7cf95aa1e6c918fe8dca8fa1c4602427e0a4b88e20046f6c342024-01-17T18:39:41+02:00Georgi Gerganovbackend : add eval callback (#4935)
536158f8c9e21302114bac3c646f80ea85b52ffa0bd862f5e41ab1fdf12d6f59455aad3f5dd8258f8052024-01-16T17:05:19ZPaul Tsochantarismetal : localized logic in `ggml_metal_graph_compute` (#4924)
537862f5e41ab1fdf12d6f59455aad3f5dd8258f8053a48d558a69c88ac17efcaa5900cd9eb19596ac42024-01-17T00:47:34+11:00Neuman Vongandroid : introduce starter project example (#4926)
538a0b3ac8c48b66206b9c5921ce57bd5c0ea6557c3d75c232e1da56f19ac4d2530dadbe0ab3a11fde52024-01-16T03:16:33-08:00Justine Tunneyggml : introduce GGML_CALL function annotation (#4850)
5397dc78764e2ff86512e6e31cb0fcb8087df4b4708356327feb3f66980ab687040495d722696d989702024-01-13T15:52:53+01:00Johannes Gäßlercompare-llama-bench: tweak output format (#4910)
540e7e4df031b9e29d4b55a4e0b0295187f6b213db1584d674be622fbf1578694ada6e62eebedbfd3772024-01-12T20:07:38+01:00slarenllama : ggml-backend integration (#4766)
541e739de790921e6abbc8c70398303cacd74913f61c910e3c28a1caee8cb1398143d582dd9ab697e682024-01-10T21:13:42+08:00leejetggml : change GGML_MAX_NAME at compile time (ggml/682)
542d34633d8db6c2e400355de4862cd699154ecc73f4f56458d34cb13dcbf69aca650e9bf77d5497e6f2024-01-10T14:37:09+01:00Johnclip : support more quantization types (#4846)
5434f56458d34cb13dcbf69aca650e9bf77d5497e6f6efb8eb30e7025b168f3fda3ff83b9b386428ad62024-01-10T01:04:33+01:00Johannes GäßlerPython script to compare commits with llama-bench (#4844)
5446efb8eb30e7025b168f3fda3ff83b9b386428ad636e5a08b203542dca53cca4eaf172c5dc4bbc9912024-01-09T13:46:46-05:00Austinconvert.py : fix vanilla LLaMA model conversion (#4818)
545dd5ae06405c5565b99889bdb3f168f4351252cfb668b31fc7d86245435ad6574e0e1126e734049e22024-01-08T16:02:32+01:00KawrakowSOTA 2-bit quants (#4773)
546226460cc0d5b185bc6685fb76f418fd9418d7addd5a410e8556191672465f7ff58682ea2474038b02024-01-07T17:59:01+01:00slarenllama-bench : add no-kv-offload parameter (#4812)
547f3f62f0d835d559e80714bbeb05d03125574e3dd0ef3ca2ac62016c0c545de1c89dc2e3e130f4a992024-01-02T21:07:47+02:00Georgi Gerganovmetal : optimize ggml_mul_mat_id (faster Mixtral PP) (#4725)
54826f3071d714f0b27ad7f021a46a66a1085480258775ac8712a7b42cfead2585f42cec0dfd56644ab2024-01-02T16:23:38+07:00Nam D. Tranpy : re-enable mmap in convert hf (#4732)
54968eccbdc5b56f2a2450f9a8463f9934388cafabf97bbca6e8522d18041fcde6c3d0907a52ce364462023-12-29T06:42:26-08:00Philip Taronflake.nix : rewrite (#4605)
550db49ff8ed7f0bb201176703441cc02911b08ef2a60f55e888c29cbd87c4238dd19e85d0eef87245d2023-12-29T06:24:12-08:00Justine Tunneyserver : replace sleep with condition variables (#4673)
551afd997ab6011dfefe9e917425b04ef4d83614841c8255f8a6b2a3b3ebc6cb340cc2487f39fc95ffc2023-12-29T05:58:56-08:00Peter Sugiharallama.swiftui : fix infinite loop, ouput timings, buff UI (#4674)
55265e5f6dadbba4b496bba27f573e473c66b446496ea5497df5d138c83b2b0ca70aefdc4b1175c10012023-12-28T11:20:00-08:00Justine TunneyFix OpenAI server sampling w.r.t. temp and seed (#4668)
553f6793491b5af6da75edad34d6f503ef86d31b09f879b690a9e1eb1ab0a29b58236fc76978fb4d9022023-12-27T22:39:45+07:00Nam D. Tranllama : add AWQ for llama, llama2, mpt, and mistral models (#4593)
55448b7ff193e64c97ab174280ba0eb8d14b47c49ba48b24b170e3b4f9dc28200306840cb07d1c123df2023-12-22T12:12:53+01:00slarenllama : fix platforms without mmap (#4578)
555d232aca5a73b290e218a2e48b91023d5e994203f31f27758faf4a4bd08101a57c7ec3a473f771f862023-12-21T21:07:46+01:00slarenllama : initial ggml-backend integration (#4520)
556800a489e4a8be199122259a995b1ee9dd7fae320f7f468a97dceec2f8fe8b1ed7a2091083446ebc72023-12-17T19:38:41+02:00Georgi Gerganovllama.swiftui : add bench functionality (#4483)
557799a1cb13b0b1b560ab0ceff485caed68faa8f1ffecac45658a99eddc4d6e36ba0310ca8f87a77f02023-12-13T13:04:25+01:00slarenllama : add Mixtral support (#4406)
558bcc0eb4591bec5ec02fad3f2bdcb1b265052ea5681bc9214a389362010f7a57f4cbc30e5f83a2d282023-12-07T13:03:17+02:00Georgi Gerganovllama : per-layer KV cache + quantum K cache (#4309)
55981bc9214a389362010f7a57f4cbc30e5f83a2d2805cd6e5036d72d0930de4d8f6be7bce09e8dda242023-12-07T02:25:22-08:00Hongyu Ouyangtrain : fix #4227 (double free in examples/train-text-from-scratch/train-text-from-scratch.cpp) (#4351)
5605aa365d88fdb8fdd430ef3fc141c7a5fd37c350252c8bc3cf312e1caf02d37bfb9d9d865cbe335942023-12-05T10:19:18-07:00Kerfufflellama : allow overriding GGUF metadata when loading model (#4092)
561ef47ec18da469423c276b683dd9b5741cee7023e1d144112c0fbbb4ecc07dbcf4f05a380148bd6de2023-12-01T10:51:24+02:00Georgi Gerganovggml : add ggml_soft_max_ext (#4256)
5628e672efe632bb6a7333964a255c4b96f018b9a650b871f1a04ef60e114bbe43004fd9c21114e802d2023-11-21T16:22:30+01:00Galunidstablelm : simplify + speedup generation (#4153)
563f23c0359a32871947169a044eb1dc4dbffd0f40540a34fe8d034bd484efd79ccbb95059ca6308dcb2023-11-20T11:35:47+01:00Galunidci : add flake8 to github actions (python linting) (#4129)
564f7d5e975424ff0eea55ca5a9181ac8e15553c1fcba4cf5c0bf37a729d29e899dadf14541cddd23d42023-11-17T16:20:53+01:00Jiří Podivínpy : remove superfluous import statements (#4076)
5653e916a07ac093045d88ef0c4fa78647ae0efc010947f64f1630bb8b0b363a3bb5e29e11425312d572023-11-17T14:48:19Zgwjrfinetune : speed-up ggml_compute_forward_out_prod_f32 via BLAS (#4079)
56691f6499393d2d999331fbfdba47a7f8b9f913f0d8da46278e1a57107591653275f8e03a281de94f02023-11-16T19:14:37-07:00KerfuffleRespect tokenizer.ggml.add_bos_token value when tokenizing (#4040)
567ca190bca8e844d171020d6147687e71472d7173471e3718abdb2771b50c9606d3a7569623a0b0afe2023-11-01T09:28:28ZAdrian Heskethserver : re-enable completion and embedded at the same time (#3876)
56871e3718abdb2771b50c9606d3a7569623a0b0afe238657db2364cfb728c694470a4a81702afea7602023-11-01T08:04:02+02:00Georgi Gerganovllama : refactor graph build code (#3837)
5692f9ec7e271220a78fe27c9e6ccbcc0dda31cda0f34b2a5e1ee4fe6295fb4420eb91131d743694c652023-10-27T17:01:23+03:00Georgi Gerganovcuda : improve text-generation and batched decoding performance (#3776)
5706961c4bd0b5176e10ab03b35394f1e9eab761792cc448774866e6479c750bd7c135cd8f92cedee672023-10-25T10:26:27+03:00Georgi Gerganovbatched-bench : print params at start
5712b4ea35e56792064598e922e46d081e02bc96b94daab3d7f45832e10773c99f3484b0d5b14d86c0c2023-10-24T16:48:37+03:00Georgi Gerganovcuda : add batched cuBLAS GEMM for faster attention (#3749)
572438c2ca83045a00ef244093d27e9ed41a8cb4ea99e70cc03229df19ca2d28ce23cc817198f8972782023-10-22T22:53:08+03:00Georgi Gerganovserver : parallel decoding and multimodal (#3677)
573a5e7dbd6141128bfa3c40a19c2945a181df625d3d3956aea53369455008159cc405ed4c4969766922023-10-22T12:14:56-06:00Kerfufflellama : validate special token ids are in range when loading GGUF model (#3635)
574f439e506e8ae8b01df2ae2156380f8156d7553e3e78f3ef24af4ca74e77e725644b41ae8ca3b10a52023-10-20T10:02:12ZHerman Semenovggml : fix rope + llama minor optimizations (#3560)
575370359e5baf619f3a8d461023143d1494b1e8fde9e24cc6e2e589d405bd1720c400f5b0b9d0ca3ee2023-10-12T18:23:18+03:00M. Yusuf Sarıgözexamples: support LLaVA v1.5 (multimodal model) (#3436)
5768c70a5ff25964f0a81e20d142a2f5ac5baff22fc24ba3d829e31a6eda3fa1723f692608c2fa3adda2023-10-11T21:25:33+03:00Georgi Gerganovbatched : add bench tool (#3545)
577b0ec5218c3d24755786b80ecce9cf4ffc07583f863d3b06a4318329f92b078e8aa0be7ab6e9f871f2023-10-08T10:01:53+03:00Georgi Gerganovmetal : support MTLGPUFamily < Apple7, formatting, style (#3524)
578f93af02488179b9c52d0d391b08ae4c4d891b8d3f72f8f22c9cb60465b2e79df2767e4ba9604e5762023-10-04T15:29:58+03:00Georgi Gerganovsync : ggml (conv 1d + 2d updates, UB fixes) (#3468)
57979f34abddb72ac5ddbf118f3d87520b611a10a7d8186242b6d67cf87ae179fb1a62f52fdf0e5c5eb2023-10-03T23:38:19+05:00Tameemggml : add RISC-V Vector Support for K-Quants and improved the existing intrinsics (#3453)
580f5ef5cfb18148131fcf45bdd2331f0db5ab7c3d040e07a60f9ce06e79f3ccd4c903eba300fb31b5e2023-09-30T18:12:57+02:00slarenggml-cuda : perform cublas mat mul of quantized types as f16 (#3412)
58116bc66d9479edd5ee12ec734973554d4493c5dfa0512d66670de3f650c579519833c085014b0f2002023-09-28T21:42:38+02:00slarenllama.cpp : split llama_context_params into model and context params (#3301)
5820e76a8992c8200237bbc6471a53fb8796b3872f72db94d98eda56982d80238840b0652b4137a2a842023-09-28T20:40:11+02:00xaedestrain : finetune LORA (#2632)
583ec893798b7a2a803466cc8f063051499ec3d96f745855b3f1c7bdd0320aa632334d0b3e8965c26c42023-09-28T19:04:36+03:00Georgi Gerganovllama : custom attention mask + parallel decoding + no context swaps (#3228)
584da0400344be12074e67dcabc565140289cf7efaae519621010cac02c6fec0f8f3b16cda0591042c02023-09-28T12:08:28+02:00slarenggml-cuda : perform cublas fp16 matrix multiplication as fp16 (#3370)
585c091cdfb24621710c617ea85c92fcd347d0bf34051a7cf5c6e490b2f51c82daa76c4ca4f8d8458262023-09-23T21:48:24+02:00slarenllama-bench : add README (#3317)
58665c2c1c5ab7c5089dbc6d10bc49b9c58f016431780834daecf4b9021770361a6d5e1b9c7a60e68542023-09-20T12:06:08-04:00Cebtenzzrebenchmark-matmult : do not use integer abs() on a float (#3277)
587d119c04c159d015a93567df7e73e0e45a22d0f1d8781013ef654270cbead3e0011e33a6d690fb1682023-09-20T10:02:39+03:00Georgi Gerganovexamples : fix benchmark-matmult (#1554)
5888c00b7a6ff38e27fa1e471452b8a480913772c2a7e50d34be68aae2cc766203703dd188e910e033a2023-09-15T19:06:03+03:00Georgi Gerganovsync : ggml (Metal F32 support + reduce ggml-alloc size) (#3192)
58983a53b753a9499a2a3535c93975b430cb2c828a95c872dbca2c7979b1f6dafc97db0774b8bbf93722023-09-14T20:21:25+03:00AlonCI: add FreeBSD & simplify CUDA windows (#3053)
590d54a4027a6ebda98ab0fef7fa0c2247d0bef132a1b0d09259e37898c519edb6c52d58f4d096f10bd2023-09-11T19:55:51+02:00Johannes GäßlerCUDA: lower GPU latency + fix Windows performance (#3110)
591f31b6f4e2d6def3c0bd7c75f75c0c1e8698e05896eeb4d90839bac1e6085e5544654ab5c319ad09a2023-09-11T09:30:11+02:00Kawrakowmetal : PP speedup (#3084)
592ba7ffbb2517ff8cf4c689f94a9ad866f3ee71225e64f5b55783e910d8287363895d652b4bea6527a2023-09-08T18:01:04+02:00Kawrakowmetal : Q3_K speedup (#2995)
59315b67a66c2f2d6032415b28a699b5131962318f1be8c9c245bd129ebabb80e0a7a8dd7daeb4d30af2023-09-07T15:52:34+02:00slarenllama-bench : use two tokens in the warmup run for prompt evals (#3059)
59431035681445181fb414e0def7ec3f84462b3bd975b8530d88c489f9d0c0ef3d0886b369f655b792e2023-09-04T06:40:18-04:00Cebtenzzrellama-bench : make cpp file non-executable (#2999)
59547068e517004d90f13c16352bb3b4cafd53a00cd8f429fa5111901f9646cf998643ac5310846d4872023-09-03T15:12:08+03:00Georgi Gerganovspeculative : PoC for speeding-up inference via speculative sampling (#2926)
596ca82cf7bac0c91d03e3d320b3a865dd006f854ac6a31a3bd9806c85ed08266f6ab65181da0f30d032023-09-03T11:06:22+03:00Kawrakowmetal : more optimizations (#2959)
59713268c533177a4dc76bce0b465645d74f0d51d554dcd47d71df8ca4edcc31302744bd93f0c31298e2023-09-01T13:42:41+03:00Georgi Gerganovmetal : slight speed-up for add and mul kernels (#2917)
59895b6e5212f5e4e1419de1d833d7f8d788f9f222744c117f41ee01c5ac8fb86bba041f08d8b87b46d2023-08-28T23:33:27-07:00Marcus Dunnadded `struct` to llama_dump_timing_info_yaml's `llama_context` (#2857)
59944c117f41ee01c5ac8fb86bba041f08d8b87b46d43033b7bb4858da4f591715b3babdf906c9b7cbc2023-08-28T21:51:47+02:00xaedestrain : mem usage and other improvements (#2439)
60043033b7bb4858da4f591715b3babdf906c9b7cbc6b73ef120114beb5664ea94aab48d07ed248ee522023-08-28T19:19:18+02:00slarenllama-bench : set locale to utf8 (#2832)
601463173a6c0ff353055eb90665794884c888c790feaa13a48ff4136f01c1cdb79cacd61b67ec530952023-08-27T16:50:33+03:00Kawrakowllama : speedup tokenization (#2831)
602789c8c945a2814e1487e18e68823d9926e3b1454c1ac54b77aaba10d029084d152be786102010eb22023-08-27T09:03:27+02:00slarenci : add LoRA test to CI (#2650)
603730d9c681e339b76407659344e5a2cd50af7d7d5c7d92e6dfec3f54849f3a0ba373054d29f321ea22023-08-26T14:13:36-06:00Kerfuffleconvert.py : advanced option (#2753)
604154725c5436808e5c519685d0279e850596dbe6212e2e33a977af73e75885eeee91c5575a77f4e5f2023-08-25T15:16:19+02:00slarenllama-bench : add model sizes (#2771)
6056bbc598a632560cb45dd2c51ad403bda8723b6293f460a2b723c8b936ac29ecfd02f244b3adeba552023-08-25T12:09:42+03:00Henri VassermanROCm Port (#1087)
60638b16dfca6e5032e6cfb90c1653bf1ba4cf647b48f8c28e89cb9531211783da697d6e7c445e2af1d2023-08-24T12:27:25-04:00Shouzheng Liumetal : bug-fix when enable ggml-alloc (#2757)
6076e91a1b0706c2e0e52b9d9be7ee82d3c1e7a33c144d5462b5cddc1c5cbcd7647646f7b55b175b01f2023-08-24T00:07:13-04:00Evan Jonesllama : fix grammar sometimes generating null char (#2756)
608cf658adc832badaaa2ca119fe86070e5a830f8f6a192860cfec89a38d59a943623bf595b1fe4495b2023-08-23T23:08:04+03:00Georgi Gerganovllm : add Falcon support (#2717)
6097f7ddd5002040804e33fcdbde44aa22f8635f57db8ad1b66b23f9b2e6e4531e9a62753323036a5562023-08-23T06:31:09-03:00IgnacioFDMFix ggml to gguf conversion on Windows (#2733)
6108e4364f2af9cd5d57240f23e83c0e29bc068bc021e3bc523d8053a77df3ac7126a84d0297ee97ef62023-08-22T09:56:03+02:00slarenllama-bench : minor fixes (#2695)
611097e121e2f17ed3541cf02c55ff7e9febc091b19eaf98c2649d7da705de255712f0038ac7e47c6102023-08-18T12:44:58+02:00slarenllama : add benchmark example (#2626)
612a872a2b28eaefc8d464eaa535c94deeb501666f90919a0f73d95cfb93a1646a1d1741a0615fe2c5e2023-08-17T03:35:53-04:00Shouzheng Liuggml-alloc : fix discrepency between measure&eval (#2639)
613bf83bff6742c0f1795b4c18695a13a34ac7adf62b5ffb2849d23afe73647f68eec7b68187af09be62023-08-16T16:07:04-04:00Shouzheng Liumetal : matrix-matrix multiplication kernel (#2615)
6145517d6e69214cdead000a76983b9fe175c3f8329f31b5397143009d682db90fd2a6cde83f1ef00eb2023-08-14T15:16:54+08:00Jhen-Jie Hongserver : implement json-schema-to-grammar.mjs & add grammar param in the UI (#2588)
615f64d44a9b9581cd58f7ec40f4fa1c3ca5ca18e1eb19edd54d51cef5e3616c18b1d0d8626895b2cba2023-08-13T00:24:45+02:00Johannes GäßlerCUDA: Fixed OpenLLaMA 3b mmq, reduced compile time (#2590)
61653dc399472d5bd35ee739b865e843b1996bd38149ca4abed893685692f90413e4d43153af12342d92023-08-12T06:35:14+08:00Equimserver: fixed wrong variable name in timing json (#2579)
6171a941869cbef8e9cc351a6c6987e4ae3b0f021f7b5472ea0ada081a6e1c06998ebbc9a24aa2cd4a42023-07-27T11:00:54+03:00Georgi Gerganovmetal : disable graph concurrency optimization due to bug (#2413)
618da1889834a036a63ead2b0ca5c9ed8967712568c82552b7f5403ca13957ac9a2cdc1732470057b622023-07-25T14:32:20+02:00slarenggml : improve graph build time via hash table lookup (#2329)
6191aa18ef994a6a2b531434eb13251ef48e56d345b9a08eaf3c4010962d0126e9e5bfbe9af64b2ac902023-07-25T08:00:19-04:00Shouzheng Liumetal : concurrently dispatch commands (#2358)
6209a08eaf3c4010962d0126e9e5bfbe9af64b2ac90129d844c87d90e74aafc23dcc84c980fd408def42023-07-25T13:48:29+03:00KawrakowAnother speed gain for Q4_0 and Q4_1 on Metal (#2375)
6212f9cf974a066ac0e03fbb235d834b01b0164d7434f06592cc6b83979e4b442e8cb97b3948c8571882023-07-24T00:19:47+03:00KawrakowSome more Q4_K and Q5_K speedup on CUDA (#2346)
622d2a43664f93ba30a84e42713bb69f936cbdacf2ab9b7d94fc10a8039befd1bc3af4f4b09c620c3512023-07-23T08:49:20+03:00KawrakowSpeed up Q4_K (#2322)
623b47b8a9cfeb439d271bf997fb985fd6d82b3af5eb5fe67f8c69113bd9354bc1adcfe2df6be3237402023-07-22T21:17:57+03:00Georgi Gerganovllama : optimize memory buffers (#2325)
6245d500e8ccf5eee3de3ae66685cc3be75e43e08b97d5f18468ceabd7a38f414f9f21b26b0c137f9942023-07-22T11:48:22+03:00Georgi Gerganovci : add 7B CUDA tests (#2319)
6254d76a5f49b9b5382dba5d13d92edb9159536c2250db14fef06836caaa13cc123c0a24dc598bdb9f02023-07-21T17:05:30+03:00KawrakowFaster Q3_K implementation on Metal (#2307)
626e782c9e735f93ab4767ffc37462c523b73a17ddc785829dfe8baf0213f2ff66963d28c62f92d79302023-07-20T18:19:45+03:00KawrakowFaster Q5_K and Q6_K on Metal (#2294)
627417a85a0010519224cf154eb85d383ffeafeeead294f424554c1599784ac9962462fc39ace92d8a52023-07-20T06:32:22-04:00Shouzheng Liumetal: minor q4 optimization and reduce code size (#2248)
628294f424554c1599784ac9962462fc39ace92d8a545a1b07e9b20c33d71d8c849ff27d693a75a02692023-07-19T15:06:40+08:00Rinnellama : extend API to get max devices at runtime (#2253)
629672dda10e4d8ac79df5d5970da7fb69d242ca9a727ab66e437797aedbb23b3599385756b6c26ac392023-07-17T03:57:28+08:00Qingyou Mengggml : fixed runtime bugs and compile errors related to GGML_PERF and GGML_DEBUG (#2219)
630c9c74b4e3f9dcfab8b0032749ff8a579ab4e4d8d3ec7e596b2ba3f43c22f441254ca2bcfa91102ba2023-07-12T00:18:43+08:00Bach Lellama : add classifier-free guidance (#2135)
63118780e0a5e17348236230bbe891901b9b57187093bbc1a11f04a9adc0d0e08c2940ba4d2978755ab2023-07-09T05:20:43-03:00JackJollimorereadme : update Termux instructions (#2147)
6321d656d6360359cfdaaf5d64ed9690047b600dbcb72421402834141df6cbdcf595fe46dbd11874dce2023-07-08T00:24:01+08:00Qingyou Mengggml : change ggml_graph_compute() API to not require context (#1999)
633a17a2683d8fdb899ba497d0c28ccafb28c62efb631cfbb1013a482e89c72146e2063ac4362becae72023-07-06T09:17:50-07:00tslmyalpaca.sh : update model file name (#2074)
63431cfbb1013a482e89c72146e2063ac4362becae7983b555e9ddb36703cee4d22642afe958de093b72023-07-05T16:51:13-04:00Tobias LütkeExpose generation timings from server & update completions.js (#2116)
635051c70dcd55709c9cbbfa849af035951fe7204339e4475f5cf639315f61ed7b8da6258bb0c7c5ca92023-07-05T18:31:23+08:00Howard Sullama: Don't double count the sampling time (#2107)
636b2132270678c473f7cd9ba871b03d694126bc33a2f8cd979ecd1fa582852e7136e92ff8990b98fd82023-07-01T20:31:44+02:00Daniel Drakecmake : don't force -mcpu=native on aarch64 (#2063)
637b8c8dda75fdf5fdea49c80af36818e7c30fe0ddf96a712ca1b7f427e3bd7ffc0c70b2105cfc7fbf12023-06-29T21:15:15+08:00Howard SuUse unsigned for random seed (#2006)
63896a712ca1b7f427e3bd7ffc0c70b2105cfc7fbf1d3494bb86bf7ad5b0b60aae0220ea576f273b5c02023-06-29T11:56:43+08:00LostRuinsPorting the improved K-Quant CUDA kernels to OpenCL (#1966)
639a84ab1da8dc6a59a5b67420ae1322f09503ffc725743ca80928d8410754ec64a5673d5c2dd6cfbb72023-06-27T01:47:02+09:00katsu560tests : fix quantize perf (#1990)
6406769e944c727c63612dcafbef52009d21ae00fffcbebf61ca7584e9709265395f0127ae7fc0f18822023-06-26T19:43:07+03:00Kawrakowk-quants : support for super-block size of 64 (#2001)
64118b35625c3c19c64b7818a12460ba5ddb006dfdcba4e85a8339b9dd7cdffad31838235f2fe45a8ea2023-06-19T20:43:30+03:00Georgi Gerganovggml : fix bug in LBFGS optimizer (found by ggml tests)
642794db3e7b982fee37e3995db9c3a216a57ff65e35ddf7ea1fb42bac21026de2f77e0f9c069b922342023-06-17T07:53:04-04:00Randall FitzgeraldServer Example Refactor and Improvements (#1570)
6433d0112261042b356621e93db3fa4c6798a5d098f602c748863e15270d80d74aa2c3bf86ab8139e072023-06-16T20:08:44+03:00KawrakowCUDA : faster k-quant dot kernels (#1862)
644a09f9195be39afb4b023b646c0a6ec8a86915174bed92756172d4514b23aaf9744cf8e2dc892fc7b2023-06-15T21:49:08+02:00Johannes GäßlerFixed CUDA runtime version check (#1879)
645254a7a7a5ff4c874ff8488f1f5cbdd7e9c89d68292549202659fc23ba9fec5e688227d0da9b06b402023-06-14T19:47:19+02:00Johannes GäßlerCUDA full GPU acceleration, KV cache in VRAM (#1827)
646e32089b2c20b1b87b22912f4a8b93fe01647d5b92347e45e7bdb09c9a7d74b2c0bc86c2b65f0c3432023-06-13T21:04:40+02:00xaedestrain : improved training-from-scratch example (#1652)
6472347e45e7bdb09c9a7d74b2c0bc86c2b65f0c34374d4cfa3438cb58bd177eed30014e6588694aaa82023-06-13T20:20:07+03:00Georgi Gerganovllama : do a warm-up eval at start for better timings (#1824)
64874a6d922f12ccfe16b0c265f43be8978c6f25e98e4caa8da59c1c97dc23fa336f4d726984a20560f2023-06-12T22:39:21+03:00KawrakowMetal implementation for all k_quants (#1807)
649e9b66ee9829039d4ab54550d6222e42a0b31e52a4f0154b0bad775ac4651bf73b5c216eb43c45cdc2023-06-10T11:28:11+03:00Kawrakowmetal : add Q4_1 implementation (#1785)
6504f0154b0bad775ac4651bf73b5c216eb43c45cdcef3171d16241c18581d4d08374f0b9e396ade6b72023-06-10T01:59:17-06:00Kerfufflellama : support requantizing models instead of only allowing quantization from 16/32bit (#1691)
65172ff5282bf0388c60821f504c4c8cc2b1f491aa60bf7cf1b296fc9fca05411b37afdf08a531487d22023-06-08T22:28:21+03:00Kawrakowmetal : add Q2_K implementation (#1762)
6520f291e1f65c1d68201e71ce99c89562a36686b6d8fc8179919a11738910db07a800f2b176f8adf092023-06-08T19:46:22+03:00Kawrakowmetal : Q6_K implementation (#1752)
6534161bdc04debb70bf5f275492b4d89fd9330087c0035858273ebe0694926bf4414d279f3e1cd109d2023-06-08T10:08:23+03:00Kawrakowmetal : add Q4_K implementation (#1733)
6545c64a0952ee58b2d742ee84e8e3d43cce5d366db5b57a5b72676540b6a45a3f527126299969ad2412023-06-07T10:59:52+03:00Georgi Gerganovk-quants : allow to optionally disable at compile time (#1734)
65535a84916fb029905c44746127026079268216e7a2d7bf110edd8c49209401a16132052cba706ffd02023-06-07T04:10:17+02:00Willy Tarreaumain: add the possibility to open the prompt cache read-only (#1640)
656f4c55d3bd7e124b101bc974cbbf0e0dbbc32d5a3f1465624c2cbc8ee65b566e3d87f2af27796d4c42023-06-05T23:32:36+03:00Yuval Peleddocs : add performance troubleshoot + example benchmark documentation (#1674)
657efe05076323f5c6bafece109e21cce046f5e4b07e7fe66e670537990ccc075cce9286df88bba052a2023-06-05T22:11:49+02:00grahamethggml : fix internal overflow in ggml_time_us on Windows (#1702)
65899009e72f8072fa552eb02efee436be596c71cdd5220a991a5e92bddad9542267ab445a2c033681c2023-06-05T22:56:18+03:00Kawrakowggml : add SOTA 2,3,4,5,6 bit k-quantizations (#1684)
6595220a991a5e92bddad9542267ab445a2c033681cd1f563a743a83dabc11e125d4a7d64189c16498c2023-06-05T13:43:08+03:00Henri VassermanIncrease 3B scratch buffers. (#1698)
660ecb217db4fcfa3880300ad08531a5fb6bb142d45dcb2ed48268e421baf25adc00d602dad0f4155642023-06-04T23:34:30+03:00Georgi Gerganovllama : Metal inference (#1642)
6611fcdcc28b119a6608774d52de905931bd5f8a43dac7876ac20124a15a44fd6317721ff1aa25388062023-05-25T23:07:29+02:00Johannes Gäßlercuda : performance optimizations (#1530)
662affc76edfdefa7b326f526e463cc65ff13fcfb92ea600071cb005267e9e8f2629c1e406dd5fde0832023-05-20T14:19:28+02:00Johannes Gäßlercuda : loading models directly into VRAM, norm calculation on GPU, broadcasting for ggml_mul (#1483)
6632d5db48371052087a83974abda3767d1aedec5986986c7835adc13ba3f9d933b95671bb1f3984dc62023-05-19T22:17:18+03:00Georgi Gerganovggml : use F16 instead of F32 in Q4_0, Q4_1, Q8_0 (#1508)
664c238b5873a1ea496db03ffcfe124c9d0d83afbc62b2646931bd2a2eb3e21c6f3733cc0e090b2e24b2023-05-17T22:47:58+08:00rankaiyxbenchmark-matmul: Print the average of the test results (#1490)
665b5c9295eef2b56e307393b35b3a923e3518d226eeb363627fda5f47de8ab5e9be8abd426049d00df2023-05-14T22:46:00+02:00slarenbenchmark-matmul: fix clang-tidy issues, report results in GFLOPS (#1458)
666bda4d7c215aa16b2a78e522521dfc0e1c2e8b1945a5aeb1e91009c72bf816400b758bb8a305616d72023-05-13T17:25:09+03:00Georgi Gerganovmake : fix PERF build with cuBLAS
667f954edda935a70a14cf0cc45ecc7fe7d60cf3e4bf048af0230ad5381bb20b9e3c1467ec6fc7debdf2023-05-13T14:56:40+02:00xaedesggml : implement backward pass for llama + small training-llama-from-scratch example (#1360)
668b9fd7eee57df101d4a3e3eabc9fd6c2cb13c9ca1b608b55a3ea8e4760c617418538465449175bdb82023-05-12T00:23:08+03:00Georgi Gerganovggml : remove bit shuffling (#1405)
6691b0fd454650ef4d68a980e3225488b79e6e9af253924088512d9e12e90ed6dbf28a6c5712481d33e2023-05-07T10:03:23+07:00swittkggml : Allow usage of CLBlast alongside Accelerate.framework (#1336)
67058b367c2d757c0ea12aec672382462b42204c724ea3a0ad6b6b5ca4693b94acd4cb32e2803f66fae2023-05-01T18:11:07+02:00slarencuBLAS: refactor and optimize f16 mat mul performance (#1259)
671f0d70f147d969e41fa410b8af2965a27aa901eb93e5aa8a1c44051153d6d7b3eeca2f4b4e5fb310c2023-04-30T12:32:37ZStephan WalterVarious fixes to mat_mul benchmark (#1253)
6727296c961d9303010a2b98379f738da2a8a55aa1b78ec543733d10a1629f984fd0302fdaa4e87fe662023-04-28T16:57:16+02:000cc4mggml : add CLBlast support (#1164)
673574406dc7e350ddbffaeca33bf0392b7bfeb143687a6f846d3e929632c45916dd08f1e2a9c72d2a32023-04-26T23:14:13+03:00Georgi Gerganovggml : add Q5_0 and Q5_1 quantization (#1187)
67487a6f846d3e929632c45916dd08f1e2a9c72d2a3ea3ad7eb60cfb44526a58122e8019850f437cd1b2023-04-26T20:08:43ZÁsgeir Bjarni IngvarssonAllow setting the rng seed after initialization. (#1184)
675ec9cdb6752dd96b3cc74d90ad1adeba5b4fa2b0ee4422e299c10c7e84c8e987770ef40d31905a76b2023-04-23T18:32:52+03:00Georgi Gerganovggml : do not print perf ops that have not been used at all
6765f939498d517b4dddbe904f202e895a3ecfb9dc436b4f7e06406eed8a605cc9f2921d9244ef6a8e52023-04-22T11:10:39+02:00unboundedggml : unit test for quantization functions (#953)
67736b4f7e06406eed8a605cc9f2921d9244ef6a8e510f19c1121068ce3dab9bece03a8b9caaea2db362023-04-22T16:56:35+08:00wbpxre150llama : print timings on ctrl+c exit (#1021)
678c5aa5e577741d0359ad26ec50b9e21a74c65d911e9a9cb0c54461ffbda75b7b2f99f3ea5562291c22023-04-22T07:37:05ZStephan Walterggml : AVX2 optimization for vec_dot_q4_3_q8_0 and refactoring (#1099)
67950cb666b8a2e35a49b08c0f6bc81138c8f6f2ac125d7abbd1f73582b7e0fdc422a936e8541c0780b2023-04-21T21:59:17+02:00slarenImprove cuBLAS performance by using a memory pool (#1094)
6801bfc153e2f35ddd9d64b084e8d1a5e6fa57ad1c93d59769c3bb7e72c915646ddb1e239b1face19f52023-04-21T17:18:26+02:00Kawrakowggml : a faster version for Q4_1 x Q8_0 dot products (#1083)
681c8c2c524827be8fd681a63f0e5a697b0bf4c587b02d6988121510c067e06d498a273a351a888f5b92023-04-20T06:45:41ZStephan WalterAVX2 optimization for vec_dot_q4_2_q8_0 (#1068)
68202d6988121510c067e06d498a273a351a888f5b9834695fe3a3ed2a962e774c9615e3f7b41d360a82023-04-20T03:14:14+02:00slarenImprove cuBLAS performance by dequantizing on the GPU (#1065)
683f7d05095b404b5500b4a702ea16f67fc22446e49884e7d7a2bfd7325b107442d6758983f5886ed3d2023-04-19T20:20:14+02:00KawrakowQ4_2 quantization with rmse-optimized scale and quants (#1062)
684884e7d7a2bfd7325b107442d6758983f5886ed3d7cd5c4a3e9106151d48f328bb3c94c298a211f182023-04-19T20:10:08+03:00Georgi Gerganovggml : use 8-bit precision for Q4_1 intermediate results (#1047)
68577a73403ca8eaced2590559d0f9cebd2b3649d3250a8a2af97cb92e53e7a3195aa201c3d87da54152023-04-18T23:54:57+03:00Georgi Gerganovggml : add new Q4_2 quantization (ARM only) (#1046)
68650a8a2af97cb92e53e7a3195aa201c3d87da54154caebf6d408b91c2d29d0abc7b1e867b5de64db52023-04-18T23:11:23+03:00Georgi Gerganovggml : scratch that - vmlaq_n_f32 is always better
687dcdd65e2969bc03c91a1ebd1160162d5054e69235ecff35151156118c2df74899637ad34ee384b9b2023-04-18T22:59:17+03:00Georgi Gerganovggml : optimize ggml_vec_dot_q4_0_q8_0() using vectorized accumulators
6885ecff35151156118c2df74899637ad34ee384b9b7faa7460f03bdd88becf1e659cf359f2740554042023-04-18T21:00:14+02:00KawrakowAdding a simple program to measure speed of dot products (#1041)
689f266259ad9a2bce5a34d919592310147af23f3dc47f61aaa5f76d04286792e2fbd0c95b659ab2af02023-04-17T15:10:57+02:00Ivan KomarovSpeedup the AVX-512 implementation of ggml_vec_dot_q4_0() (#933)
690489537e6cf6c93b74a029a11533dbcaa89791dcc2d3481c72125cd388258864c7ad8d7d36777bad72023-04-16T12:13:00+02:00Pavol Rusnakexamples: add missing <ctime> include for time() (#1011)
691e95b6554b493e71a0275764342e09bd5784a7026aa485cee334e84437e21681c14b6f80b65876d8b2023-04-15T17:53:22+03:00Georgi Gerganovggml : add Q8_0 quantization for intermediate results (#951)
692c12b14b77fced0ce9a0e2d81f670c3a746dec251106faaf2971d6c89d6010279a9a95737772470ef2023-04-15T07:51:54+02:00Ivan Komarovbenchmark : fix result validation in benchmark-q4_0-matmult (#987)
693723dac55fa2ba7adc6e3fc8609781d1ad03789060f07cacb05f49704d35a39aa27cfd4b419eb6f8d2023-04-14T00:03:03-07:00comexpy : new conversion script (#545)
694c5d70f5c9ea5a8f0f6b0d6aa741455978a1dabfdbe87b6ed20a5f7528bf491a83e759a9fc6a24fea2023-04-14T14:24:52+08:00Howard Suggml : optimize rope function to avoid call powf in the tight loop (#807)
695d990e3fffc5b0f5448e90a16c79a4f2675100af09190e8eac8bdc108c40d2d7505e9b45fa773251f2023-04-13T18:32:36+03:00Georgi Gerganovggml : speed-up ggml_vec_dot_q4_1() ARM_NEON + 32-bit ARM support (#900)
696c85980acd04631a7c43d13676276f76ec72f5dfe6232f2d7fd7a22d5eeb62182b2f21fcf013597542023-04-13T18:01:22+03:00Georgi Gerganovgitignore : benchmark
6976232f2d7fd7a22d5eeb62182b2f21fcf013597546c248707f51c8a50f7792e7f7787ec481881db882023-04-13T14:59:50ZStephan Walterggml : optimize non-SIMD Q4_0 vector dot product (#703)
69895ea26f6e92d620a5437f576b80868aee7f808d682d146df9b43cf677e0dbce20b03cf864958a0cc2023-04-13T14:46:23+02:00SebastianApelbenchmark : add tool for timing q4_0 matrix multiplication (#653)
699c3ac702e5ee3533457e0489df4906ee112fe88e79d634ef452d0fc24fcd49592952d13d0ab0f41b72023-04-10T22:40:28+03:00Georgi Gerganovggml : add ggml_cont() + optimize ggml_cpy() for contiguous dst
700f963b63afa0e057cfb9eba4d88407c6a0850a0d8aaf3b23debc1fe1a06733c8c6468fb84233cc44f2023-04-08T12:24:37-07:00comexRewrite loading code to try to satisfy everyone:
701eeaa7b0492fc79baab8bb1fe195d6c87159f2bd3986b6ce9f99503c51ec5afd8a10baa32359434c62023-04-05T22:11:03+03:00Georgi Gerganovggml : multi-thread ggml_rope() (~3-4 times faster on M1) (#781)
702986b6ce9f99503c51ec5afd8a10baa32359434c634162989297fdfe3ab7305451ce55bc87e3f4c9c2023-04-05T22:07:33+03:00Georgi Gerganovggml, llama : avoid heavy V transpose + improvements (#775)
7030c44427df10ee024b4e7ef7bfec56e993daff1db594cc95fabab0b662dabba3ea619ca5dca18bf6b2023-04-05T17:38:37+03:00Ivan Stepanovmake : missing host optimizations in CXXFLAGS (#763)
704437e77855a54e69c86fe03bc501f63d9a3fddb0ecd7fa956904cb8e321b72b3499f4a3a82e43c2662023-04-03T09:52:28+02:00SebastianApel10+% performance improvement of ggml_vec_dot_q4_0 on AVX2 (#654)
7051d08882afa647c44195f4f6495a68ea455650cae02c5b27e91a6d18cf1043d3a2d8dbc59610ac2572023-03-31T17:55:52+02:00slarenOptimize AVX2 ggml_vec_dot_q4_0 (#642)
70678ca9838ee36660a776e97e3391b6fb5dcaacf7fa017390358cdb23fffb30988dc84bb190d0403ca2023-03-29T13:51:37-07:00Justine TunneyMake loading weights 10-100x faster
707b51c717d5cf9181c33afcb84554e47f6d539c8910ba76c1e73ae21038b80bfb5a746157376c881732023-03-29T22:15:34+03:00Georgi Gerganovggml : init time on first ggml_init() call
70853635c081c49321d523567112f9fddfbba6b787b41318d708ed196ff727dce14d263a64b23c7333d2023-03-29T19:29:26+03:00Georgi Gerganovpy : add GPT4All conversion script
709436e56193199a1625f8c561069f702e8840a9e0820e1e84884376b3fb44ffbfd48d478b2934b0b5e2023-03-28T16:48:20ZStephan Walterall : be more strict about converting float to double (#458)
71029b7baab670ae8b76ac0da21c2ded69ff18971ee4a7129acd2e939b92d70dd568c746f2fa078232c2023-03-25T15:34:23+01:00slarenAdd timings for the prompt evaluation (#478)
711481044d50cfe8eaa6cd0c1a1b445680e4b0b3ebc563cdc391dde140f1084d1012234e8e6f57f881f2023-03-24T08:19:26-07:00Cameron Kaiseradditional optimizations for POWER9 (#454)
7128d4a855c241ecb0f3ddc03447fe56002ebf27a37b6b268d4415fd3b3e53f22b6619b724d4928f7132023-03-24T08:05:13-07:00LucianoAdd embedding mode with arg flag. Currently working (#282)
713305ba6f0e6daa3796aad9dd18053a1945dd4cc584122dffff958cd137175b58f1f27c0913528d7ba2023-03-22T18:16:35+01:00tjohnmanDon't force immediate interactive without `-i` (#354)
714f5a77a629bd0f37ae1696747633ab42a5530ec15da0e9fe90ccf6e73597eb19dd0cfc0a28363fb3b2023-03-22T07:32:36+02:00Georgi GerganovIntroduce C-style API (#370)
715353ec251a42491f5192c48561da4b444ef67f23c89d5d90f3b6d25f134da7a8e252c3432bffcf6742023-03-21T14:21:50-03:00Fabio R. SluzalaWe could use std::unordered_map over std::map (#305)
71616ffc013c62f22bdaa3cdc022d7a13fd952d73fc486ae645fd3eda8b9d7413d5ff34fb65a3e337fb2023-03-21T09:42:25-07:00comexImporter for GPTQ quantized LLaMA models (#301)
717486ae645fd3eda8b9d7413d5ff34fb65a3e337fb3ab3e6582f7320c2b6568c892fdfc8215caf7e6c2023-03-21T09:27:42-07:00Gary LinscottCompute perplexity over prompt (#270)
7182e664f1ff413995506c9a54f3a8d5b8c64e37a918cf9f34eddc124d4ab28f4d2fe8e99d574510bde2023-03-21T07:35:42-07:00Casey PrimozicAdd initial AVX512 support for dot product on Linux (#320)
7192af23d30434a677c6416812eea52ccc0af65119c904d2a8d6acd667c9633138d45a361d40fbf76d02023-03-17T10:47:06+01:00Bernat Vadell🚀 Dockerize llamacpp (#132)
720904d2a8d6acd667c9633138d45a361d40fbf76d0721311070e31464ac12bef9a4444093eb3eaebf72023-03-17T05:48:39+01:00Matvey SolovievQ4_1 quantization (#193)
72184d9015c4a91ab586ba65d5bd31a8482baf46ba163fd76fbb06f9b723ca11505352387a3148b18142023-03-13T18:36:44+02:00Georgi GerganovUse vdotq_s32 to improve performance (#67)
72263fd76fbb06f9b723ca11505352387a3148b18142a20f48efad692a8c2744f10c673bbdbe0c751b72023-03-14T01:33:43+09:00uint256_tReduce model loading time (#43)
723113a9e83ebc0f788f861394437087bf3ca0e019b404fac0d623c9eea74ad7a9347da69e33f10984e2023-03-13T00:56:10+02:00Georgi Gerganov10% performance boost on ARM