Commit Graph
3 Commits
Author SHA1 Message Date
Oliver SimonsandGitHub 69db8a52e6 chore: Update .clang-format to use BinPackArguments=true (#15744)
This seems to correspond with what we want to do, see
[here](https://github.com/ggml-org/llama.cpp/pull/15715#discussion_r2315613796)
and [clang-format docs](https://clang.llvm.org/docs/ClangFormatStyleOptions.html#binpackarguments)
2025-09-03 01:40:37 +08:00
Oliver SimonsandGitHub 6028bf7435 CUDA: Optimize reduce_rows_f32 kernel, leading up to 25x perf improvement on kernel-level and 10% perf increase for Gemma3n (#15132)
* Factor out `reduce_rows_f32` from common.cuh

This increases iteration cycle speed by not having to recompile
every kernel all the time

* Hide memory-latency by loop unrolling in reduce_rows_f32

* Further optimizations to `reduce_rows_f32`

1. Increase threadblock size to better hide latency of memory requests.
   As a consequence of bigger threadblocks, do 2-step summation, using
   shared memory to communicate results between invocations
2. Use sum_temp array to reduce waits on sum
3. Adjust num_unroll to reflext bigger threadblock
4. Improve default block_dims, increase support for more block_dims

* Add perf tests for `reduce_rows_f32` kernel

* Add heuristic to toggle 128/512 threads based on sm count

Break even point was the minimum of the following multiples.

| GPU Model                     | Nrow SM Count Multiple |
| -----------                   | -----------            |
| RTX 4000 SFF ADA              | 2.0x                   |
| RTX 6000 ADA                  | 2.5x                   |
| RTX PRO 6000 Blackwell Max-Q  | 3.04x                  |
| RTX PRO 4500 Blackwell	| 3.15x                  |

* Ensure perf gains also for small ncols and large nrows

Alternative to this, one could have also made the number of unrollings
template-able, but that would require compiling the kernel multiple
times, increasing binary size unnecessarily

* Modify perf and unit-tests

* Apply auto-formatting by clang

* Fix CI build failure

See https://github.com/ggml-org/llama.cpp/actions/runs/16798370266/job/47573716079?pr=15132#step:7:486
Building with VS generator worked though.

* Remove sm_count property from `ggml_backend_cuda_context`

Requested by @JohannesGaessler, and should fix remaining CI issues as a
side-effect

* Add CUB-based implementation for GGML_OP_MEAN

Currently this branch is only executed for nrows==1

* Add heuristics to execute CUB branch only when it brings perf

Heuristics were determined on the following HW:

* RTX 4000 SFF ADA
* RTX 6000 ADA
* RTX PRO 6000 Blackwell Max-Q
* RTX PRO 4500 Blackwell

* Add unit-test for CUB-based mean

Tests should run with CUDA Graphs enabled per default on NVGPUs

* Rename `USE_CUB` to `GGML_CUDA_USE_CUB`

Suggested by @JohannesGaessler

* Unindent Preprocessor directives

See
https://github.com/ggml-org/llama.cpp/pull/15132#discussion_r2269213506
2025-08-13 10:04:46 +02:00
Oliver SimonsandGitHub e2b7621e7c ggml : remove invalid portPos specifiers from dot files (#14838)
Neither "g" nor "x" are valid portPos specifiers per the official
[graphviz documents](https://graphviz.org/docs/attr-types/portPos/):

> If a compass point is used, it must have the form "n","ne","e","se","s","sw","w","nw","c","_".

I tested locally for it to fall back to default portPos specifier if an
invalid portPos is specified. As a consequence, we can remove associated
code.
2025-07-25 14:29:57 +03:00