Commit Graph

52 Commits

Author SHA1 Message Date
Johannes Gäßler 4eac5b4509
CUDA: refactor mma data loading for AMD (#22051)
* CUDA: refactor mma data loading for AMD

* fix CDNA MMQ occupancy

* fix CDNA3 mma

* fix RDNA3 compile
2026-04-19 18:26:59 +02:00
Pasha Khosravi 7e72b38bc1
cuda: Q1_0 initial backend (#21629)
* [cuda] initial Q1_0 backend

* remove unused code, fix AMD MMA guard

* attempt to support dp4a

* Apply suggestions from code review

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2026-04-15 18:38:38 +02:00
andyluo7 d132f22fc9
HIP: add CDNA4 (gfx950) architecture support for MI350X/MI355X (#21570)
Add AMD Instinct MI350X/MI355X (gfx950, CDNA4) support:

- vendors/hip.h: Add CDNA4 preprocessor define for __gfx950__
- common.cuh: Add GGML_CUDA_CC_CDNA4 and GGML_CUDA_CC_IS_CDNA4 macros
- mma.cuh: Route CDNA4 to compatible MFMA instructions:
  * f32 matmul: mfma_f32_16x16x4f32 (xf32 variant unavailable on gfx950)
  * bf16 matmul: mfma_f32_16x16x16bf16_1k (same as CDNA3)
  * int8 matmul: mfma_i32_16x16x32_i8/32x32x16 (same as CDNA3)
- mmq.cuh: Include CDNA4 in stream-k kernel dispatch

CDNA4 is largely compatible with CDNA3 except:
- No xf32 MFMA (mfma_f32_16x16x8_xf32) — routes to f32 path
- Different FP8 format (e4m3fn vs e4m3_fnuz) — not changed here

Tested on AMD Instinct MI355X (gfx950), ROCm 7.0.1:
- Build: compiles cleanly with -DAMDGPU_TARGETS=gfx950
- llama-bench (Qwen2.5-1.5B Q4_K_M, single GPU):
  * f16+FA: 40,013 tok/s prefill, 254 tok/s decode
  * q8_0+FA: functional
- Flash attention: works correctly
- MMQ: works correctly with stream-k dispatch

Co-authored-by: Andy Luo <andyluo7@users.noreply.github.com>
2026-04-09 21:13:32 +02:00
iacopPBK 66c4f9ded0
ggml-cuda: ds_read_b128 for q4_0 and q4_1 mmq kernels (#21168)
* ds_read_b128 for q4_0 and q4_1 mmq kernels

     Current for loop generates ds_read_b32 instructions with hip compiler, the new solution generates ds_read_b128 instructions for the same operation, saving some LDS bandwidth. Tested on MI50 and RX6800XT, its faster on both.

* Vectorized lds load update: used ggml_cuda_get_max_cpy_bytes and ggml_cuda_memcpy_1 functions for generic implementation

* Explicit for loop in mmq, renamed vec into tmp

* Fixed max_cpy usage in the loading loop

* Fixed typo in q4_1 kernel

* Update ggml/src/ggml-cuda/mmq.cuh

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Update ggml/src/ggml-cuda/mmq.cuh

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Update ggml/src/ggml-cuda/mmq.cuh

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Renoved trailing white line 500

* Update mmq.cuh removed other whitelines

* Remove trailing whitespaces

---------

Co-authored-by: iacopPBK <iacopPBK@users.noreply.github.com>
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
Co-authored-by: iacopPBK <iacop@deneb.com>
2026-04-07 21:47:42 +02:00
Michael Wand 84f82e846c
ggml-cuda: Add generic NVFP4 MMQ kernel (#21074)
* Introduced NVFP4 generic MMQ kernel

* Added extra FP8 guard, hope to solve ci HIP failure

* Rename tiles and use HIP_FP8_AVAILABLE

* Removed remaning FP8 straggler and added const int

* Const

* Removed DECL_MMQ_CASE artifact

* Removed newline

* Removed space after else

* Changed HIP FP8 NVFP4 conversion gate

* Added new line to bottom of mmq.cu 270

* Removed extra spaces

* Removed single space in front of else on line 814

* Added NVFP4 to generate cu script so HIP can see it, further tightened logic

* Include generated mmq-instance-nvfp4.cu

* Added NVFP4 mmq to HIP Check ignore list

* Update ggml/src/ggml-cuda/mmq.cuh

Changed to Q3_K tile to read MMQ_MMA_TILE_X_K_NVFP4

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Update ggml/src/ggml-cuda/mmq.cuh

Changed to Q3_K tile to read MMQ_MMA_TILE_X_K_NVFP4 in tile assert

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Update ggml/src/ggml-cuda/mmq.cuh

Added function name ending for end if

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

* Added function names to closing endif

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>

---------

Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
2026-04-01 12:04:58 +02:00
David Friehs 27b93cbd15
cuda: optimize iq2xxs/iq2xs/iq3xxs dequantization (#19624)
* cuda: optimize iq2xxs/iq2xs/iq3xxs dequantization

- load all 8 int8 for a grid position in one load
- calculate signs via popcnt instead of fetching from ksigns table
- broadcast signs to drop individual shift/mask

* cuda: iq2xxs: simplify sum scaling

express `(sum * scale + sum / 2) / 4` as `(sum * (scale * 2 + 1)) / 8`
express `((aux32 >> 28) * 2 + 1)` as `(aux32 >> 27 | 1)`

saves 3 registers for mul_mat_vec_q (152 -> 149) according to nsight
AFAICT no overflow can occur here as iq2xxs values are far too small

* uint -> uint32_t

error: identifier "uint" is undefined
2026-02-15 22:38:42 +05:30
Oliver Simons 1f1e57f2bf
CUDA: Fix loop unrolling for BW in mul_mat_q_stream_k_fixup (#19053)
By providing stride_* variables as size_t (i.e., 64-bit) the compiler can
correctly unroll the [two for-loops](557515be1e/ggml/src/ggml-cuda/mmq.cuh (L3789-L3816))
on BW. This gives some perf for prefill/pp phase on BW, while not affecting
other SMs:

| GPU                                                     | Model                 | Test   |   t/s master |   t/s osimons/fix_bw_mmq_fixup_kernel |   Speedup |
|:--------------------------------------------------------|:----------------------|:-------|-------------:|--------------------------------------:|----------:|
| NVIDIA RTX 6000 Ada Generation                          | gpt-oss 20B MXFP4 MoE | pp8096 |      8404.05 |                               8375.79 |      1.00 |
| NVIDIA RTX 6000 Ada Generation                          | llama 3B Q4_K_M       | pp8096 |     16148.93 |                              16019.60 |      0.99 |
| NVIDIA RTX 6000 Ada Generation                          | llama 8B Q4_0         | pp8096 |      8008.29 |                               7978.80 |      1.00 |
| NVIDIA RTX 6000 Ada Generation                          | nemotron_h 9B BF16    | pp8096 |      4263.16 |                               4248.53 |      1.00 |
| NVIDIA RTX 6000 Ada Generation                          | nemotron_h 9B Q4_K_M  | pp8096 |      5165.11 |                               5157.43 |      1.00 |
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | gpt-oss 20B MXFP4 MoE | pp8096 |     12582.80 |                              12758.37 |      1.01 |
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | llama 3B Q4_K_M       | pp8096 |     16879.10 |                              17619.47 |      1.04 |
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | llama 8B Q4_0         | pp8096 |     10649.90 |                              10982.65 |      1.03 |
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | nemotron_h 9B BF16    | pp8096 |      7717.73 |                               7716.22 |      1.00 |
| NVIDIA RTX PRO 6000 Blackwell Max-Q Workstation Edition | nemotron_h 9B Q4_K_M  | pp8096 |      7301.90 |                               7370.38 |      1.01 |
2026-02-03 11:33:14 +01:00
uvos 4ffc47cb20
HIP: Use mmq on MFMA devices for MUL_MAT_ID in cases where a lot of splits would be generated (#18202) 2025-12-28 20:12:55 +01:00
Aman Gupta c8a2417d7b
CUDA: experimental native mxfp4 support for blackwell (#17906)
* CUDA: experimental native mxfp4 support for blackwell

* optimize load_tiles

* optimize quantize_mxfp4

* cleanup

* first pass review: formatting

* use interleaved layout for mma

* mmq: add assert for size

* use __nv_fp4x4_e2m1

* use iter_k as 512, cleanup

* Use 1200 as blackwell instead of 1000

* address review comments

* mmq: fix stride

* quantize.cu: use reference impl of e8m0 scale

* address review comments

* add 120f-virtual + minor fixes

---------

Co-authored-by: Aman Gupta <aman>
2025-12-24 22:28:26 +08:00
yulo acec774ef6
HIP: Refactor mma for RDNA and CDNA (#17990)
* mma.cuh for rdna4

* mma for rdna3

* mmq for rdna4

* mmq for rdna3

* align i-major and j-major

* cdna

* fix cuda error

* add missing tile of mfma

* fix j-major wrong ne on CDNA

* fix gramma and empty spaces

---------

Co-authored-by: zhang hui <you@example.com>
2025-12-17 09:34:54 +01:00
Jiacheng (Jason) Chen 668ed76574
HIP: enable WMMA-MMQ INT kernels for RDNA 3 (#17576)
* enabled wmma instructions for most quantizations other than q2k

* fixed the last q2_k test case failure

* address comments: fix out of bound write for RDNA4, add comments after #endif

* clean up rebase: fix ne error in half2

* fix the EditorConfig CI
2025-12-05 09:17:37 +01:00
Jiacheng (Jason) Chen 3e18dba9fd
HIP: Patch failed testcase in WMMA-MMQ kernels for RDNA 4 (#17502)
* patch failed test case MUL_MAT(type_a=q4_0,type_b=f32,m=576,n=512,k=576,bs=[1,1],nr=[1,1],per=[0,1,2,3],k_v=0,o=1) for enabling WMMA on RDNA4

* Quick clean up on mma.cuh to add ggml_cuda_memcpy_1 back in for half2 and bfloat162
2025-11-26 11:18:48 +01:00
Jiacheng (Jason) Chen 0543f928a3
HIP: WMMA-MMQ kernels for RDNA 4 (#17156)
* first commit naive test to enable mmq for RDNA4

* adding appropriate WMMA instructions

* git rebase on top of master: fixing the correctness of the mat mul operations, updating layout mappings for RDNA4

* clean up merge conflicts

* add comments and code clean up

* PR clean up, addressed comments

* enable MMQ fallback on RDNA4

* addressed comments: add guards in load generic, separate wmma branch for use_mmq function

* Revert build-xcframework.sh

* Formating: remove trailing whitespace

* revert CMake files

* clean up after rebase: remove duplicated change, revert cmake files

* clean up after rebase: revert changes from build-xcframework.sh

* clean up: remove extra space line in mma.cuh

* Revert "clean up: remove extra space line in mma.cuh"

This reverts commit b39ed57c45.
2025-11-24 20:00:10 +01:00
Johannes Gäßler e14e842e87
CUDA: fix MMQ stream-k fixup ne1 indices (#17089) 2025-11-08 08:26:18 +01:00
Johannes Gäßler 5eff6ec9b1
CUDA: MoE helper in device code, better tile sizes (#15525)
* CUDA: MoE helper in device code, better tile sizes

* reduce superfluous CUDA blocks
2025-08-25 17:23:40 +02:00
R0CKSTAR 8ad038c0fd
musa: add GGML_UNUSED_VARS (#15446)
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2025-08-21 11:06:05 +08:00
R0CKSTAR a094f38143
musa: fix build warnings (#15258)
* musa: fix build warnings

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

* fix warning: comparison of integers of different signs: 'const int' and 'unsigned int' [-Wsign-compare]

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

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2025-08-20 10:17:37 +08:00
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
Johannes Gäßler 9c35706b98
CUDA: fix MMQ nwarps for AMD with warp_size==32 (#15014) 2025-08-01 20:47:32 +02:00
uvos ad4a700117
HIP: enable mfma mmq on gfx908 and gfx90a for select datatypes and shapes (#14949) 2025-07-30 17:38:06 +02:00
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
Aman Gupta 55c2646b45
CUDA: add dynamic shared mem to softmax, refactor general usage (#14497) 2025-07-03 07:45:11 +08:00
R0CKSTAR 1f73301b63
cuda : remove nrows_x in mul_mat_q_process_tile (#13325)
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2025-05-07 09:48:23 +02:00
Johannes Gäßler 15a28ec8c7
CUDA: fix --split-mode row for MMQ (#13323) 2025-05-06 08:36:46 +02:00
Johannes Gäßler 93c4e23905
CUDA: fix race condition in MMQ stream-k fixup (#13299) 2025-05-04 14:16:39 +02:00
Johannes Gäßler 8afbd96818
CUDA: fix race condition in MMQ ids_dst (#13294) 2025-05-04 13:58:38 +02:00
Johannes Gäßler e1e8e0991f
CUDA: batched+noncont MMQ, refactor bs>1 MoE code (#13199) 2025-04-30 23:12:59 +02:00
Johannes Gäßler b10d8bfdb1
CUDA: use switch statements in constexpr functions (#13095) 2025-04-24 15:57:10 +02:00
R0CKSTAR 492d7f1ff7
musa: fix all warnings, re-enable `-DLLAMA_FATAL_WARNINGS=ON` in ci and update doc (#12611)
* musa: fix all warnings

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

* musa: enable -DLLAMA_FATAL_WARNINGS=ON in run.sh

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

* musa: update ci doc (install ccache)

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

* fix Windows build issue

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

* Address review comments

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

* Address review comments

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

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2025-03-30 10:59:38 +02:00
Slobodan Josic bd40678df7
HIP: Add support for RDNA4 targets (#12372) 2025-03-26 23:46:30 +01:00
R0CKSTAR 7ea75035b6
CUDA: Fix clang warnings (#12540)
Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2025-03-24 11:28:34 +01:00
R0CKSTAR fac63a3d78
musa: refine compute capability (#12493)
* musa: refine compute capability

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

* Address review comments

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

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
2025-03-22 10:11:37 +01:00
Johannes Gäßler 9c42b1718c
CUDA: fix logic for V100 + GGML_CUDA_FORCE_MMQ (#12098) 2025-02-28 09:26:43 +01:00
Johannes Gäßler 73e2ed3ce3
CUDA: use async data loading for FlashAttention (#11894)
* CUDA: use async data loading for FlashAttention

---------

Co-authored-by: Diego Devesa <slarengh@gmail.com>
2025-02-17 14:03:24 +01:00
Johannes Gäßler b9ab0a4d0b
CUDA: use arch list for compatibility check (#11775)
* CUDA: use arch list for feature availability check

---------

Co-authored-by: Diego Devesa <slarengh@gmail.com>
2025-02-11 00:17:22 +01:00
uvos 4d0598e144
HIP: add GGML_CUDA_CC_IS_* for amd familys as increasing cc archtectures for amd gpus are not supersets of eatch other (#11601)
This fixes a bug where RDNA1 gpus other than gfx1010 where not handled correctly
2025-02-02 22:08:05 +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
Andreas Kieslinger 750cb3e246
CUDA: rename macros to avoid conflicts with WinAPI (#10736)
* Renames NVIDIA GPU-architecture flags to avoid name clashes with WinAPI. (e.g. CC_PASCAL, GPU architecture or WinAPI pascal compiler flag?)

* Reverts erroneous rename in SYCL-code.

* Renames GGML_CUDA_MIN_CC_DP4A to GGML_CUDA_CC_DP4A.

* Renames the rest of the compute capability macros for consistency.
2024-12-10 18:23:24 +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
Diego Devesa ae8de6d50a
ggml : build backends as libraries (#10256)
* ggml : build backends as libraries

---------

Signed-off-by: Xiaodong Ye <xiaodong.ye@mthreads.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: R0CKSTAR <xiaodong.ye@mthreads.com>
2024-11-14 18:04:35 +01:00
Johannes Gäßler 5af118efda
CUDA: fix --split-mode row race condition (#9413) 2024-09-11 10:22:40 +02:00
slaren 2b1f616b20
ggml : reduce hash table reset cost (#8698)
* ggml : reduce hash table reset cost

* fix unreachable code warnings after GGML_ASSERT(false)

* GGML_ASSERT(false) -> GGML_ABORT("fatal error")

* GGML_ABORT use format string
2024-07-27 04:41:55 +02:00
Johannes Gäßler 69c487f4ed
CUDA: MMQ code deduplication + iquant support (#8495)
* CUDA: MMQ code deduplication + iquant support

* 1 less parallel job for CI build
2024-07-20 22:25:26 +02:00
Johannes Gäßler 808aba3916
CUDA: optimize and refactor MMQ (#8416)
* CUDA: optimize and refactor MMQ

* explicit q8_1 memory layouts, add documentation
2024-07-11 16:47:47 +02:00
Johannes Gäßler 8e558309dc
CUDA: MMQ support for iq4_nl, iq4_xs (#8278) 2024-07-05 09:06:31 +02:00
Daniele 0a423800ff
CUDA: revert part of the RDNA1 optimizations (#8309)
The change on the launch_bounds was causing a small performance drop in perplexity of 25 t/s
2024-07-05 09:06:09 +02:00
Johannes Gäßler bcefa03bc0
CUDA: fix MMQ stream-k rounding if ne00 % 128 != 0 (#8311) 2024-07-05 09:05:34 +02:00
Daniele d23287f122
Define and optimize RDNA1 (#8085) 2024-07-04 01:02:58 +02:00