Commit Graph

1329 Commits

Author SHA1 Message Date
bssrdf f931ad883f WIP 2025-10-21 17:12:50 -04:00
bssrdf f0a480cc22 WIP 2025-10-21 15:43:35 -04:00
bssrdf 6a1f8b4d57 change padding size back to 4 2025-10-15 14:21:04 -04:00
bssrdf ac77b8d0e0 change padding size to 1; added padding to input smem 2025-10-15 14:07:24 -04:00
bssrdf 3f99818925 unroll some loops 2025-10-15 12:46:46 -04:00
bssrdf b70cca2ea3 add support for both NCHW and NHWC layouts 2025-10-14 14:24:35 -04:00
bssrdf 3e2f722d11 fixed missing dilation 2025-10-14 11:12:55 -04:00
bssrdf 2237722056 added block variants; to be debugged 2025-10-14 11:02:10 -04:00
bssrdf 16b0f0ae3c work in progress 2025-10-13 18:41:30 -04:00
bssrdf 0ca43582e8 reorder register tile loop 2025-10-08 13:52:56 -04:00
bssrdf 53a2ccbe12 minor update and add direct conv in benchmarking 2025-09-24 21:48:20 -04:00
bssrdf 2ec76aa8f3 Merge branch 'master' into conv2d-implicit 2025-09-10 22:04:20 -04:00
Oliver Simons 00681dfc16
CUDA: Add `fastdiv` to `k_bin_bcast*`, giving 1-3% E2E performance (#15872)
* Add fastdiv and fastmodulo to k_bin_bcast kernel

* Address review comments

* `prod_` instead of `prod` suffix

* Add test case for `k_bin_bcast_unravel` in CUDA backend
2025-09-10 22:04:03 +02:00
bssrdf 735886b099 merged with upstream master 2025-09-10 12:28:59 -04:00
Daniel Bevenius 9de447d94e
ggml-cpu : fix padding in ggml_timestep_embedding (#15917)
This commit fixes the zero padding for odd dimensions in
ggml_compute_forward_timestep_embedding_f32.
The motivation for this is that currently if an odd dimension is used,
the padding check incorrectly uses the dimension value for indexing.
For example, with dim=15:

Elements 0-6 are set to cosine values
Elements 7-13 are set to sine values
Element 14 is left uninitialized (contains garbage)
Element 15 is correctly set to zero

This fix changes embed_data[dim] to embed_data[2 * half] so that
element 14 (the first unused element) is properly set to zero as well
as the last element.

Resolves: https://github.com/ggml-org/ggml/issues/1324
2025-09-10 17:31:40 +02:00
Georgi Gerganov 0f0a3c2851
metal : make the backend async (#15906)
* metal : make the backend async

ggml-ci

* cont : add comments, extend op offload, clean up

ggml-ci

* metal : fix batch size for MUL_MAT_ID

* metal : remove deprecated ggml_backend_metal_buffer_from_ptr

* metal : create only metal buffers, no wrapping of host memory

ggml-ci

* metal : restore .alloc_buffer for buffer_from_ptr_type

ggml-ci

* metal : remove broken implementation of GGML_OP_SET

ggml-ci

* metal : clean-up loose ends, ready for tests

ggml-ci

* metal : support both private and shared buffers

ggml-ci

* metal : enable private buffers + add global device queue

* metal : disable host buffer to prevent races

ggml-ci

* metal : avoid extra copy during set_tensor

ggml-ci

* metal : use separate buffer types for shread and private Metal buffers

ggml-ci

* metal : simplify synchronization logic

ggml-ci

* metal : fix build

ggml-ci

* metal : do not implement cpy_tensor

ggml-ci

* metal : separate implementations for shared and private buffers

ggml-ci
2025-09-10 17:52:35 +03:00
Chenguang Li 10d8b2b6b0
CANN: Add ROPE sin/cos cache for reuse (#15912)
* CANN: Add ROPE sin/cos cache for reuse

Introduce sin/cos caching mechanism in ROPE to avoid redundant
computation across layers. The cache is built on the first layer
per device and reused by subsequent layers if parameters match.

- Added sin_cache / cos_cache pointers and position_length tracking
- Introduced cache validity flags and properties:
  (ext_factor, theta_scale, freq_scale, attn_factor, is_neox)
- Accelerates ROPE by eliminating repeated sin/cos generation

This change reduces overhead in multi-layer scenarios while
preserving correctness by verifying parameter consistency.

Co-authored-by: hipudding <huafengchun@gmail.com>

* fix typo

Signed-off-by: noemotiovon <757486878@qq.com>

---------

Signed-off-by: noemotiovon <757486878@qq.com>
Co-authored-by: hipudding <huafengchun@gmail.com>
2025-09-10 18:42:00 +08:00
Chenguang Li 28b5f190ef
CANN: implement LRU cache for ACL graphs (#15814)
* CANN: implement LRU cache for ACL graphs in CANN backend

- Introduce ggml_cann_graph_lru_cache to store multiple ggml_cann_graph objects.
- Graphs are loaded on demand and evicted using LRU policy when capacity is exceeded.
- Updated push, move_to_front, and clear methods to manage cached graphs efficiently.
- Ensures reuse of graphs, reducing graph reconstruction overhead in CANN backend.

* fix typo

* The LRU cache capacity can be configured via an env variable

Signed-off-by: noemotiovon <757486878@qq.com>

* refactory acl graph

* refactory && fix review comments

Signed-off-by: noemotiovon <757486878@qq.com>

---------

Signed-off-by: noemotiovon <757486878@qq.com>
2025-09-10 15:29:12 +08:00
Ruben Ortlam ae355f6f71
vulkan: throw the oom error instead of no memory type found (#15905) 2025-09-09 22:26:03 +02:00
Jeff Bolz 4f63cd705c
vulkan: Fix OOB accesses in soft_max_back (#15861) 2025-09-09 14:41:15 +02:00
Johannes Gäßler 17bc5a815f
HIP: use v_dot2_f32_f16 instruction for FA (#15884) 2025-09-09 14:04:43 +02:00
lksj92hs ed54e32558
Workaround for subgroup arithmetic failing on MoltenVK with AMD GPUs (issue 15846) (#15886) 2025-09-09 14:01:15 +02:00
Aman Gupta a972faebed
CUDA: Add mul_mat_id support for the mmf kernel (#15767)
* CUDA: Add mul_mat_id support the mmf

Add support for mul_mat_id for bs < 16

* Review: use warp_size, fix should_use_mmf condition

* Launch one block per expert, stride along n_expert_used

* templatize mul_mat_id

* Pad shmem to 16 bytes, add helper function mul_mat_f_switch_ids

* Reduce compile times by dividing mmf into f16, bf16 and f32 variants

* Divide mmf by ncols_dst

* Add missing files

* Fix MUSA/HIP builds
2025-09-09 14:38:02 +08:00
Johannes Gäßler 550cf726e1
CUDA: fix GET_ROWS for large tensors (#15882) 2025-09-09 08:11:01 +02:00
Jeff Bolz e68aa10d8f
vulkan: sort graph to allow more parallel execution (#15850)
* vulkan: sort graph to allow more parallel execution

Add a backend proc to allow the backend to modify the graph. The
vulkan implementation looks at which nodes depend on each other
and greedily reorders them to group together nodes that don't
depend on each other. It only reorders the nodes, doesn't change
the contents of any of them.

With #15489, this reduces the number of synchronizations needed.

* call optimize_graph per-split
2025-09-09 02:10:07 +08:00
Aman Gupta 0a16bf52e6
CUDA: generate_cu_files.py - add missing mxfp4 (#15880) 2025-09-09 01:23:46 +08:00
Georgi Gerganov b0d52998b9
cuda : fix supports_op condition for get_rows when number of blocks is too large (#15868)
* cuda : fix supports_op condition for get_rows when src1->ne2 > 1

ggml-ci

* ggml : add comment about ggml_get_rows

ggml-ci

* cuda : add FIXME [no ci]

* cuda : update support condition

ggml-ci
2025-09-08 13:56:51 +03:00
Georgi Gerganov f28d4f4ac9
metal : refactor + optimize (#15857)
* metal : refactor

ggml-ci

* cont : refactor FA-vec kernel

* cont : print metal library load time

* minor : warn to debug + bettern kernel names

ggml-ci

* metal : optimize mul_mv q8_0

ggml-ci

* metal : simplify FA pipeline creation functions

ggml-ci

* metal : improve naming consistency

* metal : safer function constants offsets

ggml-ci

* metal : comments

ggml-ci
2025-09-08 13:34:56 +03:00
Xuan-Son Nguyen 9fcb29f22f
ggml: allow casting between f32 and i32 (#15783)
* ggml: allow casting between f32 and i32

* fix cuda

* add vulkan

* fix CPU non-cont

* add non-cont test case

* add note

* extend test number range

* correct note

* add cont version for vulkan
2025-09-08 12:33:01 +02:00
Sigbjørn Skjæret 5ef22d281d
CUDA: non-contiguous src0 not supported for PAD (#15869) 2025-09-08 12:55:44 +03:00
Chenguang Li 85ca66a746
CANN: Stream sync between devices for acl_graph (#15809)
* CANN: Switch to stream synchronization

Switch to stream synchronization because events are not effective.

Co-authored-by: hipudding <huafengchun@gmail.com>

* CANN: add Comments

---------

Co-authored-by: hipudding <huafengchun@gmail.com>
2025-09-08 10:03:29 +08:00
Jeff Bolz 3976dfbe00
vulkan: support im2col_3d (#15795) 2025-09-07 13:50:26 -05:00
Aaron Teo d36e61c580
ggml-cpu: clean up s390x SIMD (#15855)
* ggml-cpu: clean up s390x simd

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
(cherry picked from commit 0da4b6aa07)
Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

* ggml-cpu: fix hsum data types

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>

---------

Signed-off-by: Aaron Teo <aaron.teo1@ibm.com>
2025-09-08 02:18:28 +08:00
Jeff Bolz c97b5e5854
vulkan: Support pad_ext (#15794) 2025-09-07 19:00:49 +02:00
Jeff Bolz 267e99867f
vulkan: Use larger loads in scalar/coopmat1 matmul (#15729)
I think glslang will translate an access like x[i][1].z to
OpAccessChain ... x, i, 1, 2
OpLoad float16_t ...

rather than loading all of x[i] in a single OpLoad. Change the
code to explicitly load the vector/matrix.
2025-09-07 18:53:07 +02:00
Daniel Bevenius 3b15924d71
ggml WebGPU: remove userdata from request adapter callback (#15527)
* ggml WebGPU: remove userdata from request adapter callback

This commit removes the `userdata` parameter from the WebGPU request
adapter callback in `ggml-webgpu.cpp`. Instead, the lambda function
captures the `webgpu_context` directly.

The motivation for this change is to simplify the code and improve
readability.

* inline the callback lambda into the RequestAdapter call

This commit removes the callback lambda variable and inlines it directly
into the RequestAdapter call.
2025-09-07 11:19:45 +03:00
Johannes Gäßler 79bc429262
CUDA: faster tile FA (Pascal/AMD), headsize 256 (#15769) 2025-09-07 00:26:28 +02:00
bssrdf 83a3b7d6a9 Refactor conv2d_implicit_kernel for improved bitwise operations; add test for implicit convolution 2025-09-06 17:26:19 -04:00
Charles Xu c4df49a42d
kleidiai: generalize compute_forward_kv_cache to compute_forward_fp16 (#15817) 2025-09-06 22:08:43 +08:00
Johannes Gäßler 01806e7771
ggml-cpu: document use of "free" memory [no ci] (#15834) 2025-09-06 13:28:44 +02:00
Aaron Teo 186415d595
ggml-cpu: drop support for nnpa intrinsics (#15821) 2025-09-06 11:27:28 +08:00
Johannes Gäßler 5143fa895e
CUDA: fastdiv, launch bounds for mmvq + q8_1 quant (#15802)
* CUDA: fastdiv, launch bounds for mmvq + q8_1 quant
2025-09-05 16:07:02 +02:00
bssrdf 4b0f9d571f Refactor conv2d_implicit_kernel for improved readability and consistency; update parameter comments and remove unused code 2025-09-05 08:29:57 -04:00
Erik Scholz a81283820a
gguf: gguf_writer refactor (#15691)
* gguf: split gguf writer into base and buf impl
* gguf: templated gguf write out
* gguf: file based writer (avoid writing everything to memory first!)
* examples(llama2c): fix log not being the same level and compiler nits
2025-09-05 11:34:28 +02:00
bssrdf 5ffe97be9c Fix boundary check in conv2d_implicit_kernel to include channel limits 2025-09-04 15:32:29 -04:00
Gabe Goodhart 856ed0947f
metal : Add template specialization for mul_mm_id w/ ne20 == 10 (#15799)
Branch: GGMLMetalNE20

Signed-off-by: Gabe Goodhart <ghart@us.ibm.com>
2025-09-04 18:53:22 +03:00
Chenguang Li c1c354e44c
CANN: Refactor ND to NZ workspace to be per-device (#15763)
* CANN:Refactor ND to NZ workspace to be per-device in Ascend backend

- Replaced the previous single global ND→NZ workspace with a per-device
  cache using unordered_map keyed by device ID.
- Functions `release_nz_workspace`, `relloc_nz_workspace`, and
  `get_nz_workspace` now manage workspace independently for each device,
  preventing memory conflicts in multi-device / pipeline parallel scenarios.
- This change fixes potential precision issues caused by workspace
  overwrites when multiple devices perform ND→NZ conversions concurrently.

Co-authored-by: hipudding <huafengchun@gmail.com>

* refactor

Signed-off-by: noemotiovon <757486878@qq.com>

* rename

Signed-off-by: noemotiovon <757486878@qq.com>

* fix review comments

Signed-off-by: noemotiovon <757486878@qq.com>

---------

Signed-off-by: noemotiovon <757486878@qq.com>
Co-authored-by: hipudding <huafengchun@gmail.com>
2025-09-04 20:20:14 +08:00
leejet 0a1b3982cd
ggml: add ops for WAN video model (cuda && cpu) (#15669)
* add conv3d support

* add ggml_pad_ext for cpu & cuda backend

* cuda/cpu: add im2col_3d support

* cuda: make im2col a little faster

* fix cuda pad/scale/im2col3d

* make im2col_3d faster

* gguf: support loading tensors which n_dims > GGML_MAX_DIMS

* fix cuda get_rows

* avoid ggml_conv_3d conflict

* correct GGML_OP_COUNT assertion

* avoid build failure

* avoid build failure on MacOS

* cuda: remove unnecessary MIN define

* fix cpu im2col_3d

* adjust the code style

* cuda: use simpler loop in get_rows

* add test_im2col_3d to test-backend-ops

* test-backend-ops.cpp: remove trailing whitespace

* cpu: im2col_3d support non continuous src

Co-authored-by: Jeff Bolz <jbolz@nvidia.com>

* fix test_im2col_3d

* remove unused variables

* cuda: get_rows: dfloat2 -> float2

* add test_pad_ext to test-backend-ops.cpp

* add gguf_init_from_file_ext impl

* Revert "gguf: support loading tensors which n_dims > GGML_MAX_DIMS"

This reverts commit d8377a0a37.

* Revert "add gguf_init_from_file_ext impl"

This reverts commit d9f1d13208.

* update ggml_backend_vk_device_supports_op

* fix ggml_backend_vk_device_supports_op

* update other backend supports op for ggml_pad_ext

* metal/opencl/sycl/vulkan: fix GGML_OP_PAD check in supports_op

---------

Co-authored-by: Jeff Bolz <jbolz@nvidia.com>
2025-09-04 10:38:49 +02:00
hipudding 5421f63ab0
CANN: Fix precision issue on 310I DUO multi-devices (#15784) 2025-09-04 15:12:30 +08:00
rmatif 820bc98531
opencl: add hs=40 to FA (#15758) 2025-09-03 23:30:28 -07:00