The flake.nix included references to llama-cpp.cachix.org cache with a comment
claiming it's 'Populated by the CI in ggml-org/llama.cpp', but:
1. No visible CI workflow populates this cache
2. The cache is empty for recent builds (tested b6150, etc.)
3. This misleads users into expecting pre-built binaries that don't exist
This change removes the non-functional cache references entirely, leaving only
the working cuda-maintainers cache that actually provides CUDA dependencies.
Users can still manually add the llama-cpp cache if it becomes functional in the future.
* 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>
* 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>
* 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
* 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>
* musa: fix failures in test-backend-ops for mul_mat_id op
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>
* Fix MinicpmV model converter and clip to avoid using hardcode.
* Code update for pr/14750
* Remove unused field, update script path in docs.
* Add version 5 for fallback code.
---------
Co-authored-by: lzhang <zhanglei@modelbest.cn>
This commit updates `llama_kv_cache_unified::find_slot` to log
information for all streams when debug is enabled.
The motivation for this change is that currently if a non-unified
kv-cache is used, then only one stream will be logged because the
code was currently uses `seq_to_stream[1]`.
This commit updates comments and error messages to use "decode" instead
of "eval" in perplexity.cpp.
The motivation for this is that `llama_eval` was renamed to
`llama_decode` a while ago, but the comments and error messages
still referred to "eval". This change ensures consistency and clarity.
* cuda: refactored ssm_scan to use CUB
* fixed compilation error when when not using CUB
* assign L to constant and use size_t instead of int
* deduplicated functions
* change min blocks per mp to 1
* Use cub load and store warp transpose
* suppress clang warning
uvos
Bas Nijholt
Sigbjørn Skjæret
Judd
Copilot
Aldehir Rojas
Ali Tariq
Georgi Gerganov
Oliver Simons
Tak-RS
Romain Biessy
rmatif
Aman Gupta
Chenguang Li
R0CKSTAR
hipudding
rainred
Xuan-Son Nguyen
Zagaj
Daniel Bevenius
Julien Denize
Charles Xu
David Zhao
Ed Addario
compilade
Johannes Gäßler
AN Long
Olivier Chafik
lhez
Jeff Bolz
RunningLeon