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AgeCommit message (Expand)Author
2024-01-16ggml : introduce GGML_CALL function annotation (#4850)Justine Tunney
2024-01-12llama : ggml-backend integration (#4766)slaren
2023-12-07sync : ggml (new ops, tests, backend, etc.) (#4359)Georgi Gerganov
2023-11-07cuda : supports running on CPU for GGML_USE_CUBLAS=ON build (#3946)Meng Zhang
2023-10-08sync : ggml (ggml-backend) (#3548)Georgi Gerganov
2023-09-28llama : custom attention mask + parallel decoding + no context swaps (#3228)Georgi Gerganov
2023-08-25ROCm Port (#1087)Henri Vasserman
2023-08-22ggml-cuda : use graph allocator (#2684)slaren
2023-08-18llama : add benchmark example (#2626)slaren
2023-07-31CUDA: mmq CLI option, fixed mmq build issues (#2453)Johannes Gäßler
2023-07-01Better CUDA synchronization logic (#2057)Johannes Gäßler
2023-06-28CUDA GPU acceleration for LoRAs + f16 models (#1970)Johannes Gäßler
2023-06-14CUDA full GPU acceleration, KV cache in VRAM (#1827)Johannes Gäßler
2023-06-12Leverage mmap for offloading tensors to GPU (#1597)Howard Su
2023-06-06Multi GPU support, CUDA refactor, CUDA scratch buffer (#1703)Johannes Gäßler
2023-05-20cuda : loading models directly into VRAM, norm calculation on GPU, broadcasti...Johannes Gäßler
2023-05-13ggml : GPU-accelerated token generation (#1412)Johannes Gäßler
2023-05-01cuBLAS: refactor and optimize f16 mat mul performance (#1259)slaren
2023-04-29cuBLAS: use host pinned memory and dequantize while copying (#1207)slaren
2023-04-29cuBLAS: non-contiguous tensor support (#1215)Henri Vasserman
2023-04-28Remove Q4_3 which is no better than Q5 (#1218)Stephan Walter
2023-04-26ggml : add Q5_0 and Q5_1 quantization (#1187)Georgi Gerganov
2023-04-25ggml : add Q8_0 quantization format (rename the old one to Q8_1) (ARM NEON) (...Georgi Gerganov
2023-04-21Improve cuBLAS performance by using a memory pool (#1094)slaren
2023-04-20Add Q4_3 support to cuBLAS (#1086)slaren
2023-04-20Improve cuBLAS performance by dequantizing on the GPU (#1065)slaren
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