Commit Graph

22 Commits

Author SHA1 Message Date
uvos 29c8fbe4e0 HIP: bump requirement to rocm 6.1 (#15296) 2025-08-13 20:44:30 +02:00
uvos b0493156fa HIP: disable sync warp shuffel operators from clr amd_warp_sync_functions.h (#15273) 2025-08-12 22:15:12 +02:00
Johannes Gäßler 1d72c84188 CUDA: GEMM for FP32/FP16/BF16 and ne11 <= 16 (#15131)
* CUDA: GEMM for FP32/FP16/BF16 and ne11 <= 16
2025-08-07 10:53:21 +02:00
Georgi Gerganov fd1234cb46 llama : add gpt-oss (#15091)
* oai moe

* compat with new checkpoint

* add attn sink impl

* add rope scaling yarn

* logits match with latest transformers code

* wip chat template

* rm trailing space

* use ggml_scale_bias

* rm redundant is_swa_all

* convert interleaved gate_up

* graph : fix activation function to match reference (#7)

* vocab : handle o200k_harmony special tokens

* ggml : add attention sinks support (#1)

* llama : add attn sinks

* ggml : add attn sinks

* cuda : add attn sinks

* vulkan : add support for sinks in softmax

remove unnecessary return

* ggml : add fused swiglu_oai op (#11)

* ggml : add fused swiglu_oai op

* Update ggml/src/ggml-cpu/ops.cpp

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

* update CUDA impl

* cont : metal impl

* add vulkan impl

* test-backend-ops : more test cases, clean up

* llama : remove unfused impl

* remove extra lines

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>

---------

Co-authored-by: slaren <slarengh@gmail.com>

* repack mxfp4 upon conversion

* clean up a bit

* enable thinking

* add quick hack to render only some special tokens

* fix bf16 conversion

* remove vocab hack

* webui ok

* support chat parsing for gpt-oss

* fix webui

* direct mapping mxfp4, FINALLY

* force using mxfp4

* properly use lazy tensor

* ggml : add mxfp4

ggml : use e8m0 conversion instead of powf

Co-authored-by: Diego Devesa <slarengh@gmail.com>

change kvalues_mxfp4 table to match e2m1 (#6)

metal : remove quantization for now (not used)

cuda : fix disabled CUDA graphs due to ffn moe bias

vulkan : add support for mxfp4

cont : add cm2 dequant

* ggml : add ggml_add_id (#13)

* ggml : add ggml_add_id

* add cuda impl

* llama : add weight support check for add_id

* perf opt

* add vulkan impl

* rename cuda files

* add metal impl

* allow in-place ggml_add_id

* llama : keep biases on CPU with --cpu-moe

* llama : fix compile error

ggml-ci

* cuda : add fallback for __nv_cvt_e8m0_to_bf16raw

ggml-ci

* cleanup

ggml-ci

* sycl : fix supports_op for MXFP4

ggml-ci

* fix Unknown reasoning format

* ggml-cpu : fix AVX build

ggml-ci

* fix hip build

ggml-ci

* cuda : add mxfp4 dequantization support for cuBLAS

ggml-ci

* ggml-cpu : fix mxfp4 fallback definitions for some architectures

ggml-ci

* cuda : fix version required for __nv_cvt_e8m0_to_bf16raw

---------

Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
Co-authored-by: slaren <slarengh@gmail.com>
2025-08-05 22:10:36 +03:00
uvos aa79524c51 HIP: remove the use of __HIP_PLATFORM_AMD__, explicitly support only AMD targets (#14945) 2025-07-29 20:23:04 +02:00
deepsek 66906cd82a HIP: Enable Matrix cores for MMQ Kernels, Enable stream-K for CDNA 3 (#14624)
This commit adds support for MFMA instructions to MMQ. CDNA1/GFX908 CDNA2/GFX90a and CDNA3/GFX942 are supported by the MFMA-enabled code path added by this commit. The code path and stream-k is only enabled on CDNA3 for now as it fails to outperform blas in all cases on the other devices.
Blas is currently only consistently outperformed on CDNA3 due to issues in the amd-provided blas libraries.
This commit also improves the awareness of MMQ towards different warp sizes and as a side effect improves the performance of all quant formats besides q4_0 and q4_1, which regress slightly, on GCN gpus.
2025-07-27 00:28:14 +02:00
R0CKSTAR 3f4fc97f1d musa: upgrade musa sdk to rc4.2.0 (#14498)
* musa: apply mublas API changes

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* musa: update musa version to 4.2.0

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* musa: restore MUSA graph settings in CMakeLists.txt

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* musa: disable mudnnMemcpyAsync by default

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* musa: switch back to non-mudnn images

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* minor changes

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* musa: restore rc in docker image tag

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2025-07-24 20:05:37 +01:00
Slobodan Josic 756aa1020a HIP : Add HIP 7.0+ compatibility for hipBLAS compute types (#14634) 2025-07-11 18:55:00 +02:00
David Huang 84778e9770 CUDA/HIP: Share the same unified memory allocation logic. (#12934)
Replace compile-time `GGML_HIP_UMA` with environment variable `GGML_CUDA_ENABLE_UNIFIED_MEMORY`. This unifies the usage on NVIDIA and AMD GPUs, and allows a single binary to be shared between integrated and dedicated GPUs.
2025-04-15 11:20:38 +02:00
Georgi Gerganov 1a1ab7e7a4 cuda : fix HIP and MUSA BF16 (#0)
ggml-ci
2025-04-07 18:44:17 +03:00
Slobodan Josic bd40678df7 HIP: Add support for RDNA4 targets (#12372) 2025-03-26 23:46:30 +01:00
Gaurav Garg 517b5ddbf0 CUDA: Improve flash decoding kernel GPU occupancy for BS=1 case (#12183)
- Find out active blocks per SM using cudaOccupancyMaxActiveBlocksPerMultiprocessor API. Use this value to determine the optimal parallel_blocks value.
- Prefer vector flash attention kernels over MMA kernel for BS=1

Fixes Issue: #12182
---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2025-03-19 20:52:06 +01:00
Gaurav Garg b1b132efcb cuda : enable CUDA Graph on CUDA Toolkit < 12.x (#12394)
* Enable CUDA Graph on CTK < 12.x

`cudaGraphExecUpdate` API was changed on 12.x. For this reason CUDA graph support was disabled on older CUDA toolkit. This change enables CUDA support in CTK version < 12.x by using older API if CTK < 12.x.

* Fix compilation errors with MUSA

* Disable CUDA Graph for MUSA
2025-03-17 20:25:13 +02:00
uvos 396856b400 CUDA/HIP: add support for selectable warp size to mmv (#11519)
CUDA/HIP: add support for selectable warp size to mmv
2025-02-02 22:40:09 +01:00
Johannes Gäßler 864a0b67a6 CUDA: use mma PTX instructions for FlashAttention (#11583)
* CUDA: use mma PTX instructions for FlashAttention

* __shfl_sync workaround for movmatrix

* add __shfl_sync to HIP

Co-authored-by: Diego Devesa <slarengh@gmail.com>
2025-02-02 19:31:09 +01:00
uvos 5f0db9522f hip : Add hipGraph and VMM support to ROCM (#11362)
* Add hipGraph support

* Enable VMM on rocm
2025-01-25 00:02:23 +01:00
Johannes Gäßler 46e3556e01 CUDA: add BF16 support (#11093)
* CUDA: add BF16 support
2025-01-06 02:33:52 +01:00
uvos 3ad5451f3b Add some minimal optimizations for CDNA (#10498)
* Add some minimal optimizations for CDNA

* ggml_cuda: set launch bounds also for GCN as it helps there too
2024-11-27 17:10:08 +01:00
R0CKSTAR c35e586ea5 musa: enable building fat binaries, enable unified memory, and disable Flash Attention on QY1 (MTT S80) (#9526)
* mtgpu: add mp_21 support

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: disable flash attention on qy1 (MTT S80); disable q3_k and mul_mat_batched_cublas

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: enable unified memory

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

* mtgpu: map cublasOperation_t to mublasOperation_t (sync code to latest)

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2024-09-22 16:55:49 +02:00
Georgi Gerganov d13edb17ed ggml : fix builds (#0)
ggml-ci
2024-09-20 21:15:05 +03:00
R0CKSTAR b34e023480 musa: remove Clang builtins mapping (#9421)
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2024-09-11 03:46:55 +02:00
R0CKSTAR 439b3fc75a cuda : organize vendor-specific headers into vendors directory (#8746)
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2024-07-29 14:56:12 +02:00