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template-instances
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CUDA: FA support for Deepseek (Ampere or newer) (#13306)
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2025-05-09 13:34:58 +02:00 |
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vendors
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HIP : Add HIP 7.0+ compatibility for hipBLAS compute types (#14634)
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2025-07-11 18:55:00 +02:00 |
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CMakeLists.txt
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CUDA: FA support for Deepseek (Ampere or newer) (#13306)
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2025-05-09 13:34:58 +02:00 |
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acc.cu
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llama/ggml: add LLM training support (#10544)
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2025-05-12 14:44:49 +02:00 |
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acc.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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arange.cu
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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arange.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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argmax.cu
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cuda : optimize argmax (#10441)
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2024-11-21 18:18:50 +01:00 |
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argmax.cuh
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ggml/ex: calculate accuracy in graph, adapt MNIST (ggml/980)
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2024-10-03 21:17:26 +03:00 |
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argsort.cu
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ggml : reduce hash table reset cost (#8698)
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2024-07-27 04:41:55 +02:00 |
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argsort.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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binbcast.cu
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Support pure float16 add/sub/mul/div operations in the CUDA (and CPU) backend (ggml/1121)
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2025-03-03 18:18:11 +02:00 |
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binbcast.cuh
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ggml/examples: add backend support for numerical optimization (ggml/949)
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2024-09-20 21:15:05 +03:00 |
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clamp.cu
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cuda: unary ops as float + de-duplicate (ggml/1130)
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2025-03-03 18:18:11 +02:00 |
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clamp.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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common.cuh
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musa: fix build warnings (unused variable) (#14561)
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2025-07-08 07:58:30 +08:00 |
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concat.cu
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musa: fix all warnings, re-enable `-DLLAMA_FATAL_WARNINGS=ON` in ci and update doc (#12611)
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2025-03-30 10:59:38 +02:00 |
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concat.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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conv-transpose-1d.cu
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musa: fix all warnings, re-enable `-DLLAMA_FATAL_WARNINGS=ON` in ci and update doc (#12611)
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2025-03-30 10:59:38 +02:00 |
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conv-transpose-1d.cuh
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feat: cuda implementation for `ggml_conv_transpose_1d` (ggml/854)
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2024-07-08 12:23:00 +03:00 |
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conv2d-dw.cu
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CUDA: add conv_2d_dw (#14265)
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2025-06-20 09:50:24 +08:00 |
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conv2d-dw.cuh
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CUDA: add conv_2d_dw (#14265)
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2025-06-20 09:50:24 +08:00 |
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conv2d-transpose.cu
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CUDA: add conv_2d_transpose (#14287)
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2025-06-20 22:48:24 +08:00 |
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conv2d-transpose.cuh
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CUDA: add conv_2d_transpose (#14287)
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2025-06-20 22:48:24 +08:00 |
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convert.cu
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CUDA: add bf16 and f32 support to cublas_mul_mat_batched (#14361)
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2025-06-29 01:30:53 +08:00 |
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convert.cuh
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CUDA: add bf16 and f32 support to cublas_mul_mat_batched (#14361)
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2025-06-29 01:30:53 +08:00 |
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count-equal.cu
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ggml: fix zero division in ‘dne’ calculation in CUDA COUNT_EQUAL operator when ‘ne’ is small (#10213)
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2024-11-09 08:35:46 +01:00 |
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count-equal.cuh
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ggml/ex: calculate accuracy in graph, adapt MNIST (ggml/980)
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2024-10-03 21:17:26 +03:00 |
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cp-async.cuh
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CUDA: FA support for Deepseek (Ampere or newer) (#13306)
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2025-05-09 13:34:58 +02:00 |
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cpy-utils.cuh
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CUDA: set_rows + cpy.cu refactor (#14712)
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2025-07-18 14:54:18 +08:00 |
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cpy.cu
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CUDA: set_rows + cpy.cu refactor (#14712)
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2025-07-18 14:54:18 +08:00 |
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cpy.cuh
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ggml: Re-enable CUDA graphs in presence of CONT and DUP nodes (#12970)
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2025-04-17 15:19:42 +02:00 |
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cross-entropy-loss.cu
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CUDA: add dynamic shared mem to softmax, refactor general usage (#14497)
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2025-07-03 07:45:11 +08:00 |
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cross-entropy-loss.cuh
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ggml/examples: add backend support for numerical optimization (ggml/949)
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2024-09-20 21:15:05 +03:00 |
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dequantize.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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diagmask.cu
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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diagmask.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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fattn-common.cuh
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llama : add high-throughput mode (#14363)
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2025-07-16 16:35:42 +03:00 |
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fattn-mma-f16.cuh
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llama : add high-throughput mode (#14363)
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2025-07-16 16:35:42 +03:00 |
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fattn-tile-f16.cu
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llama : add high-throughput mode (#14363)
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2025-07-16 16:35:42 +03:00 |
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fattn-tile-f16.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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fattn-tile-f32.cu
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llama : add high-throughput mode (#14363)
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2025-07-16 16:35:42 +03:00 |
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fattn-tile-f32.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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fattn-vec-f16.cuh
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llama : add high-throughput mode (#14363)
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2025-07-16 16:35:42 +03:00 |
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fattn-vec-f32.cuh
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llama : add high-throughput mode (#14363)
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2025-07-16 16:35:42 +03:00 |
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fattn-wmma-f16.cu
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llama : add high-throughput mode (#14363)
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2025-07-16 16:35:42 +03:00 |
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fattn-wmma-f16.cuh
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CUDA: use mma PTX instructions for FlashAttention (#11583)
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2025-02-02 19:31:09 +01:00 |
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fattn.cu
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CUDA: faster Deepseek FA, add Turing support (#13435)
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2025-05-14 16:08:20 +02:00 |
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fattn.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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getrows.cu
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CUDA: add bf16 and i32 to getrows (#14529)
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2025-07-07 21:45:43 +08:00 |
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getrows.cuh
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CUDA: batched+noncont MMQ, refactor bs>1 MoE code (#13199)
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2025-04-30 23:12:59 +02:00 |
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ggml-cuda.cu
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CUDA: set_rows + cpy.cu refactor (#14712)
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2025-07-18 14:54:18 +08:00 |
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gla.cu
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llama: add support for QRWKV6 model architecture (#11001)
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2025-01-10 09:58:08 +08:00 |
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gla.cuh
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llama: add support for QRWKV6 model architecture (#11001)
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2025-01-10 09:58:08 +08:00 |
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im2col.cu
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CUDA: fix 1D im2col, add tests (ggml/993)
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2024-10-23 16:50:02 +03:00 |
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im2col.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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mean.cu
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CUDA: add mean operation (#14313)
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2025-06-22 12:39:54 +08:00 |
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mean.cuh
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CUDA: add mean operation (#14313)
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2025-06-22 12:39:54 +08:00 |
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mma.cuh
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musa: fix all warnings, re-enable `-DLLAMA_FATAL_WARNINGS=ON` in ci and update doc (#12611)
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2025-03-30 10:59:38 +02:00 |
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mmq.cu
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CUDA: fix crash on large batch size for quant. MoE (#13537)
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2025-05-14 16:41:02 +02:00 |
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mmq.cuh
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CUDA: add dynamic shared mem to softmax, refactor general usage (#14497)
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2025-07-03 07:45:11 +08:00 |
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mmv.cu
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CUDA/HIP: optimize mmv paths taken for HIP devices (#14324)
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2025-06-24 01:12:56 +02:00 |
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mmv.cuh
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CUDA: mul_mat_v support for batch sizes > 1 (#14262)
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2025-06-23 13:11:31 +02:00 |
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mmvq.cu
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CUDA: fix crash with partial offloading of MoE (#13439)
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2025-05-11 16:09:33 +02:00 |
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mmvq.cuh
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CUDA: noncont MMVQ + batched bs1 MUL_MAT_ID (#13014)
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2025-04-22 21:27:40 +02:00 |
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norm.cu
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llama: Add support for RWKV v7 architecture (#12412)
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2025-03-18 07:27:50 +08:00 |
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norm.cuh
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llama: Add support for RWKV v7 architecture (#12412)
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2025-03-18 07:27:50 +08:00 |
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opt-step-adamw.cu
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ggml: new optimization interface (ggml/988)
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2024-11-17 08:30:29 +02:00 |
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opt-step-adamw.cuh
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ggml/examples: add backend support for numerical optimization (ggml/949)
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2024-09-20 21:15:05 +03:00 |
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out-prod.cu
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CPU/CUDA: fix (GQA) mul mat back, add CUDA support (#11380)
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2025-01-24 12:38:31 +01:00 |
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out-prod.cuh
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ggml/examples: add backend support for numerical optimization (ggml/949)
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2024-09-20 21:15:05 +03:00 |
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pad.cu
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musa: fix all warnings, re-enable `-DLLAMA_FATAL_WARNINGS=ON` in ci and update doc (#12611)
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2025-03-30 10:59:38 +02:00 |
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pad.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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pool2d.cu
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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pool2d.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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quantize.cu
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CUDA: fix crash on large batch size for quant. MoE (#13537)
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2025-05-14 16:41:02 +02:00 |
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quantize.cuh
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CUDA: batched+noncont MMQ, refactor bs>1 MoE code (#13199)
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2025-04-30 23:12:59 +02:00 |
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rope.cu
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cuda : fix rope with partial rotation and non-cont src (#14580)
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2025-07-08 10:15:21 +03:00 |
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rope.cuh
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RoPE: fix back, CUDA support for back + noncont. (#11240)
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2025-01-15 12:51:37 +01:00 |
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scale.cu
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ggml : add ggml_scale_bias (#14417)
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2025-07-09 18:16:12 +02:00 |
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scale.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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set-rows.cu
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CUDA: set_rows + cpy.cu refactor (#14712)
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2025-07-18 14:54:18 +08:00 |
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set-rows.cuh
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CUDA: add set rows for f32 and f16 (#14551)
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2025-07-12 16:31:38 +03:00 |
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softmax.cu
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CUDA: add dynamic shared mem to softmax, refactor general usage (#14497)
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2025-07-03 07:45:11 +08:00 |
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softmax.cuh
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CUDA: backwards pass for misc. ops, add tests (#11257)
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2025-01-16 16:43:38 +01:00 |
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ssm-conv.cu
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model : support LiquidAI LFM2 hybrid family (#14620)
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2025-07-11 20:27:01 +02:00 |
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ssm-conv.cuh
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ggml : faster ssm scan (#10558)
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2025-03-31 18:05:13 +02:00 |
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ssm-scan.cu
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cuda : support Falcon-H1 state size for SSM_SCAN (#14602)
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2025-07-09 23:54:38 -04:00 |
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ssm-scan.cuh
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ggml : faster ssm scan (#10558)
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2025-03-31 18:05:13 +02:00 |
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sum.cu
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llama/ggml: add LLM training support (#10544)
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2025-05-12 14:44:49 +02:00 |
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sum.cuh
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tests: add gradient tests for all backends (ggml/932)
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2024-09-08 11:05:55 +03:00 |
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sumrows.cu
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CUDA: add mean operation (#14313)
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2025-06-22 12:39:54 +08:00 |
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sumrows.cuh
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CUDA: add mean operation (#14313)
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2025-06-22 12:39:54 +08:00 |
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tsembd.cu
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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tsembd.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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unary.cu
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cuda : add ELU support (#14657)
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2025-07-13 11:33:16 +02:00 |
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unary.cuh
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cuda : add ELU support (#14657)
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2025-07-13 11:33:16 +02:00 |
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upscale.cu
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CUDA: add bilinear interpolation for upscale (#14563)
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2025-07-08 10:11:18 +08:00 |
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upscale.cuh
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llama : reorganize source code + improve CMake (#8006)
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2024-06-26 18:33:02 +03:00 |
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vecdotq.cuh
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CUDA: noncont MMVQ + batched bs1 MUL_MAT_ID (#13014)
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2025-04-22 21:27:40 +02:00 |
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wkv.cu
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llama: Add support for RWKV v7 architecture (#12412)
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2025-03-18 07:27:50 +08:00 |
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wkv.cuh
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llama: Add support for RWKV v7 architecture (#12412)
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2025-03-18 07:27:50 +08:00 |
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