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[pull] master from ggml-org:master#523

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Aug 13, 2025
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[pull] master from ggml-org:master#523
pull[bot] merged 9 commits intosyther-labs:masterfrom
ggml-org:master

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Tak-RS and others added 9 commits August 13, 2025 08:54
…over RPC (macOS & others) (#15188)

* ggml-rpc: chunk send()/recv() to avoid EINVAL for very large tensors over RPC (macOS & others). Fixes #15055

* ggml-rpc: rename RPC_IO_CHUNK->MAX_CHUNK_SIZE, use std::min() for cap, switch to GGML_LOG_ERROR, handle 0-length send/recv

* rpc: drop n==0 special case in send_data(); retry in loop per review

* rpc: remove trailing whitespace in send_data()

---------

Co-authored-by: Shinnosuke Takagi <nosuke@nosukenoMacBook-Pro.local>
…vement 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
#15132 (comment)
* ci : add flake8 and pyright to copilot-setup-steps.yml

* add tools/server/tests/requirements.txt
* Changed the CI file to hw

* Changed the CI file to hw

* Added to sudoers for apt

* Removed the clone command and used checkout

* Added libcurl

* Added gcc-14

* Checking gcc --version

* added gcc-14 symlink

* added CC and C++ variables

* Added the gguf weight

* Changed the weights path

* Added system specification

* Removed white spaces

* ci: Replace Jenkins riscv native build Cloud-V pipeline with GitHub Actions workflow

Removed the legacy .devops/cloud-v-pipeline Jenkins CI configuration and introduced .github/workflows/build-riscv-native.yml for native RISC-V builds using GitHub Actions.

* removed trailing whitespaces

---------

Co-authored-by: Akif Ejaz <akifejaz40@gmail.com>
…e-draft parameters (#15191)

* Checkpoint from VS Code for coding agent session

* Initial plan

* Fix typo in --override-tensor-draft flag implementation

* Add null termination for speculative tensor buffer overrides

* Apply suggestions from code review

* Apply suggestions from code review

* Extract tensor override parsing logic to common function (addresses @slaren's feedback)

* Apply suggestions from code review

* Apply suggestions

---------

Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
Co-authored-by: Diego Devesa <slarengh@gmail.com>
* update `rope_multi`:

1. add `ggml_rope_multi_inplace`;
1. use `GGML_MROPE_SECTIONS` instead of 4.

* Apply suggestions from code review

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

---------

Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
@pull pull bot locked and limited conversation to collaborators Aug 13, 2025
@pull pull bot added the ⤵️ pull label Aug 13, 2025
@pull pull bot merged commit c24f4e2 into syther-labs:master Aug 13, 2025
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8 participants