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template-instances
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ggml: CUDA: add head size 72 for flash-attn (#16962)
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2025-11-03 14:29:11 +01:00 |
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vendors
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CUDA: add stream-based concurrency (#16991)
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2025-11-30 08:17:55 +08:00 |
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CMakeLists.txt
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CUDA: skip fusion for repeating adds in bias (#17080)
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2025-11-08 16:58:05 +08:00 |
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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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…
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add-id.cu
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musa: fix build warnings (#15258)
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2025-08-20 10:17:37 +08:00 |
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add-id.cuh
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llama : add gpt-oss (#15091)
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2025-08-05 22:10:36 +03:00 |
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arange.cu
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…
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arange.cuh
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…
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argmax.cu
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…
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argmax.cuh
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argsort.cu
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cuda : add error checking for cudaMemcpyAsync in argsort (#17599)
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2025-11-30 08:16:28 +08:00 |
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argsort.cuh
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binbcast.cu
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ggml: fix CUDA grid launch condition for large block_nums.y in binbcast (#16742)
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2025-10-24 21:39:37 +02:00 |
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binbcast.cuh
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CUDA: fuse adds, fuse add with rms norm (#15631)
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2025-08-29 11:35:58 +08:00 |
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clamp.cu
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…
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clamp.cuh
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…
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common.cuh
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ggml-cuda: reorder only relevant nodes (#17639)
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2025-12-02 12:36:31 +08:00 |
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concat.cu
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…
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concat.cuh
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…
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conv-transpose-1d.cu
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musa: add GGML_UNUSED_VARS (#15446)
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2025-08-21 11:06:05 +08:00 |
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conv-transpose-1d.cuh
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…
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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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conv2d.cu
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CUDA: fix build error from ambiguous __half conversions in conv2d (#15690)
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2025-09-01 06:55:06 +05:30 |
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conv2d.cuh
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CUDA: add conv2d (#15635)
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2025-08-28 20:33:03 +02:00 |
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convert.cu
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musa: add GGML_UNUSED_VARS (#15446)
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2025-08-21 11:06:05 +08:00 |
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convert.cuh
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HIP: RDNA4 tensor core support for MMF (#17077)
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2025-11-22 00:03:24 +01:00 |
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count-equal.cu
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…
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count-equal.cuh
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…
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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 : support non-contiguous i32 to i32 copy (#17326)
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2025-11-23 11:13:34 +01:00 |
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cpy.cu
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[MUSA] enable fp16/fast_fp16/bf16_mma on PH1 (#17551)
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2025-11-28 14:08:29 +01:00 |
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cpy.cuh
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cuda : remove legacy copy-op pointer indirection code (#16485)
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2025-10-14 11:53:49 +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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dequantize.cuh
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CUDA: replace GGML_CUDA_F16 with CUDA arch checks (#15433)
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2025-08-20 16:58:49 +02:00 |
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diagmask.cu
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…
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diagmask.cuh
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fattn-common.cuh
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CUDA: no FP16 arithmetic for vector FA kernel (#17558)
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2025-11-28 10:29:09 +01:00 |
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fattn-mma-f16.cuh
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musa: add GGML_UNUSED_VARS (#15446)
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2025-08-21 11:06:05 +08:00 |
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fattn-tile.cu
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ggml: CUDA: add head size 72 for flash-attn (#16962)
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2025-11-03 14:29:11 +01:00 |
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fattn-tile.cuh
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[MUSA] enable fp16/fast_fp16/bf16_mma on PH1 (#17551)
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2025-11-28 14:08:29 +01:00 |
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fattn-vec.cuh
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[MUSA] enable fp16/fast_fp16/bf16_mma on PH1 (#17551)
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2025-11-28 14:08:29 +01:00 |
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fattn-wmma-f16.cu
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HIP: Disable ROCWMMA fattn on CDNA when compiled against ROCWMMA 2.0.0 (#16221)
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2025-10-01 23:09:25 +02:00 |
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fattn-wmma-f16.cuh
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CUDA: faster tile FA, add oob checks, more HSs (#16492)
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2025-10-11 20:54:32 +02:00 |
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fattn.cu
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ggml: CUDA: add head size 72 for flash-attn (#16962)
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2025-11-03 14:29:11 +01:00 |
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fattn.cuh
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CUDA: refactor FA support/selection code (#15454)
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2025-08-20 23:14:14 +02:00 |
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getrows.cu
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CUDA: fix GET_ROWS for large tensors (#15882)
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2025-09-09 08:11:01 +02:00 |
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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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ggml-cuda: reorder only relevant nodes (#17639)
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2025-12-02 12:36:31 +08:00 |
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gla.cu
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…
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gla.cuh
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im2col.cu
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CUDA: fix im2col_3d to respect non-contiguous inputs (views) (#15956)
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2025-09-16 00:28:31 +02:00 |
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im2col.cuh
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ggml: add ops for WAN video model (cuda && cpu) (#15669)
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2025-09-04 10:38:49 +02:00 |
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mean.cu
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cuda : fix GGML_CUDA_GRAPHS=OFF (#15300)
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2025-08-14 13:22:07 +03:00 |
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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] enable fp16/fast_fp16/bf16_mma on PH1 (#17551)
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2025-11-28 14:08:29 +01:00 |
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mmf.cu
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HIP: enable mul_mat_f for RDNA4 (#17437)
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2025-11-28 08:24:30 +01:00 |
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mmf.cuh
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HIP: RDNA4 tensor core support for MMF (#17077)
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2025-11-22 00:03:24 +01:00 |
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mmid.cu
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CUDA: add fp kernel for larger batch size MoE (#16512)
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2025-10-14 13:15:15 +02:00 |
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mmid.cuh
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CUDA: add fp kernel for larger batch size MoE (#16512)
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2025-10-14 13:15:15 +02:00 |
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mmq.cu
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HIP: WMMA-MMQ kernels for RDNA 4 (#17156)
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2025-11-24 20:00:10 +01:00 |
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mmq.cuh
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HIP: Patch failed testcase in WMMA-MMQ kernels for RDNA 4 (#17502)
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2025-11-26 11:18:48 +01:00 |
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mmvf.cu
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CUDA: fix should_use_mmvf for ne11 == 1 (#17085)
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2025-11-07 20:53:14 +01:00 |
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mmvf.cuh
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CUDA: fix crash on uneven context without FA (#16988)
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2025-11-06 14:05:47 +01:00 |
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mmvq.cu
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CUDA: Remove unneded bias/gate dims in fused mmvq (#16858)
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2025-11-01 13:13:26 +08:00 |
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mmvq.cuh
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CUDA: General GEMV fusion (#16715)
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2025-10-26 19:28:04 +08:00 |
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norm.cu
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CUDA: Optimize `rms_norm_f32` kernel and its fused variants, giving 1-6% perf E2E (#15715)
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2025-09-03 19:59:16 +02:00 |
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norm.cuh
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CUDA: fuse adds, fuse add with rms norm (#15631)
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2025-08-29 11:35:58 +08:00 |
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opt-step-adamw.cu
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…
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opt-step-adamw.cuh
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…
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opt-step-sgd.cu
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finetune: SGD optimizer, more CLI args (#13873)
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2025-08-14 12:03:57 +02:00 |
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opt-step-sgd.cuh
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finetune: SGD optimizer, more CLI args (#13873)
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2025-08-14 12:03:57 +02:00 |
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out-prod.cu
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…
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out-prod.cuh
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…
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pad.cu
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ggml: add ops for WAN video model (cuda && cpu) (#15669)
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2025-09-04 10:38:49 +02:00 |
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pad.cuh
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…
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pad_reflect_1d.cu
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musa: fix build warnings (#15611)
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2025-09-26 02:56:10 +02:00 |
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pad_reflect_1d.cuh
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cuda : add Pad Reflect 1D support (#14659)
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2025-08-22 13:06:29 +02:00 |
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pool2d.cu
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…
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pool2d.cuh
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…
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quantize.cu
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CUDA: fastdiv, launch bounds for mmvq + q8_1 quant (#15802)
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2025-09-05 16:07:02 +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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reduce_rows.cuh
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musa: fix build warnings (#15258)
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2025-08-20 10:17:37 +08:00 |
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roll.cu
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CUDA: add roll (#14919)
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2025-07-29 14:45:18 +08:00 |
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roll.cuh
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CUDA: add roll (#14919)
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2025-07-29 14:45:18 +08:00 |
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rope.cu
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CUDA: fuse rope + set_rows (#16884)
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2025-11-13 08:50:01 +08:00 |
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rope.cuh
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CUDA: fuse rope + set_rows (#16884)
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2025-11-13 08:50:01 +08:00 |
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scale.cu
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ggml: add ops for WAN video model (cuda && cpu) (#15669)
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2025-09-04 10:38:49 +02:00 |
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scale.cuh
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…
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set-rows.cu
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CUDA: use fastdiv in set-rows (#16834)
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2025-10-29 21:11:53 +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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set.cu
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cuda: add SET operation support (#16804)
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2025-10-28 20:10:28 +01:00 |
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set.cuh
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cuda: add SET operation support (#16804)
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2025-10-28 20:10:28 +01:00 |
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softcap.cu
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cuda : add softcap fusion (#14907)
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2025-07-29 14:22:03 +02:00 |
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softcap.cuh
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cuda : add softcap fusion (#14907)
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2025-07-29 14:22:03 +02:00 |
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softmax.cu
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llama : add gpt-oss (#15091)
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2025-08-05 22:10:36 +03:00 |
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softmax.cuh
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…
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solve_tri.cu
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SOLVE_TRI CUDA kernel for small matrices (#17457)
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2025-11-28 12:15:32 +08:00 |
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solve_tri.cuh
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SOLVE_TRI CUDA kernel for small matrices (#17457)
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2025-11-28 12:15:32 +08:00 |
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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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…
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ssm-scan.cu
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ggml : fix SSM_SCAN for n_groups > 1 (#15625)
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2025-08-28 10:11:36 -04:00 |
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ssm-scan.cuh
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sum.cu
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CUDA: Optimize `reduce_rows_f32` kernel, leading up to 25x perf improvement on kernel-level and 10% perf increase for Gemma3n (#15132)
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2025-08-13 10:04:46 +02:00 |
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sum.cuh
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…
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sumrows.cu
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CUDA: Optimize `reduce_rows_f32` kernel, leading up to 25x perf improvement on kernel-level and 10% perf increase for Gemma3n (#15132)
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2025-08-13 10:04:46 +02:00 |
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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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topk-moe.cu
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CUDA: support for weight clamp in top-k norm (#16702)
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2025-10-27 09:06:16 +08:00 |
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topk-moe.cuh
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CUDA: support for weight clamp in top-k norm (#16702)
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2025-10-27 09:06:16 +08:00 |
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tsembd.cu
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ggml : fix padding in timestep embedding kernels (#15932)
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2025-09-16 15:25:57 +02:00 |
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tsembd.cuh
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unary.cu
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ggml : add ops SOFTPLUS, EXPM1, TRI, SOLVE_TRI, CUMSUM (#17063)
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2025-11-13 20:54:47 +02:00 |
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unary.cuh
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ggml : add ops SOFTPLUS, EXPM1, TRI, SOLVE_TRI, CUMSUM (#17063)
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2025-11-13 20:54:47 +02:00 |
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upscale.cu
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model: LFM2-VL fixes (#17577)
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2025-11-30 21:57:31 +01:00 |
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upscale.cuh
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vecdotq.cuh
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CUDA: Accelerate MXFP4 table lookup using `__byte_perm` (#15451)
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2025-08-25 23:21:22 +02:00 |
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wkv.cu
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wkv.cuh
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