* Allow reshuffled arguments in tagged argument parser format tool calls.
* Remove shuffle just keep the optional parsers in any order
* Remove unnecessary import
* ggml-cuda: add mem check for fusion
* Replace NaNs with -FLT_MAX
* fix typo
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
This patch addresses an Internal Compiler Error (Segmentation fault)
observed with gcc 15 by replacing the intrinsic + cast by doing
a cat on the data first and then calling the intrinsic. This bypasses the
buggy compiler path while maintaining identical instruction selection.
Performance Verification:
Assembly analysis on RHEL 9 (GCC 15.1.1) confirms that both the original
code and this fix generate the identical Power10 prefixed load instruction:
`plxv 40, 2(14)`
This ensures zero performance regression while unblocking builds on
newer toolchains.
Reproduced on:
- Alpine Linux + GCC 15.2.0-r2
- RHEL 9 + GCC 15.1.1 (gcc-toolset-15)
Signed-off-by: Shalini Salomi Bodapati <Shalini.Salomi.Bodapati@ibm.com>
* CUDA: use shared mem for ssm_conv
* fuse silu + ssm_conv
* fuse unary + mul
* enable for fp16
* formatting
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* hexagon: add fp16 support for binary ops: add,sub,mul,div
* hexagon: fix test-backend-ops failures for fp16 binary ops on older arches (<v79)
* hexagon: decide on n_threads (aka n_jobs) early to avoid overallocating scratchpad
* snapdragon: fix readme link
---------
Co-authored-by: Max Krasnyansky <maxk@qti.qualcomm.com>
* models : add llm_build_delta_net_base
* cont : keep qwen35 and qwen35moe graphs intact
* cont : add comments [no ci]
* add kimi linear to delta-net-base
* removed unnecessary ggml_cont from g_exp_t
* removed ggml_cont from g_diff_exp_t. moved ggml_cont for o to kimi-linear.cpp
* removed unnecessary diag mask
* cont : simplify
* cont : avoid graph splits
* scale q after mul instead of beginning
* scale q after mul instead of beginning
* identical ppl
* cont : fix scale and decay mask
* minor : remove TODO
* block implementation for kda
* remove space at the end of line 101
* concat+pad
* pad+binary row concat
* chunk size 16 for kda
* removed minor differences to master
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Adds CPU-to-CUDA copy capability to
ggml_backend_cuda_cpy_tensor_async()
* Adds function to relax sync requirements between input copies on
supported backends (CUDA for now)
* Exchanges synchronous copy with async copy function.
* Adds macro guards to allow compilation in non-CUDA builds
* Reworked backend detection in ggml-backend.cpp to avoid linking
conflicts
* Relax requirement of checks in async CUDA copies from backend and buffer type to just buffer type, to avoid linking issues
* Minor cleanup
* Makes opt-in to relax use of explicit syncs more general. Backends like
vulkan which require a synchronization between HtoD copies and graph
execution could also adopt this change now.
* Reintroduces stricter check for CPU->CUDA backend async copy via
GGML_DEVICE_TYPE_CPU.
* Corrects initialization of ggml_backend_sync_mode in
ggml_backend_sched_split initialization
* Simplifies synchronizations to adhere to `saaasg` pattern.
* Apply suggestion from @ggerganov (src->buffer to buf_src)
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* Apply suggestion from @ggerganov (src->buffer to buf_src) v2
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
---------
Co-authored-by: Georgi Gerganov <ggerganov@gmail.com>
* model : fix Qwen3.5 model type detection
* Update src/llama-model.cpp
whoops, my bad
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
---------
Co-authored-by: Sigbjørn Skjæret <sigbjorn.skjaeret@scala.com>
* Enable tmate debugging for investigating thread safety issue
* Refactor wait and submit to operate on vector<wgpu::FutureWaitInfo>, and fix wait to delete only the future that is completed.
* Cleanup
* Remove clear change and run clang-format
* Cleanup
Many models have vocabulary sizes, and thus tensor shapes, with more
than 5 digits (ex: Gemma 3's vocab size is 262,208).
I already fixed this for `llama_format_tensor_shape` but missed it for
`llama_format_tensor_shape` until now. Oops.
* Set C locale for consistent float formatting across all binaries.
* Add C locale setting to all tools binaries
Add std::setlocale(LC_NUMERIC, "C") to all 16 binaries in the tools/
directory to ensure consistent floating-point formatting.
* Apply suggestion from @JohannesGaessler
---------
Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
* ggml-webgpu: fix workgroup dispatch limit for large batch sizes
WebGPU limits workgroup sizes to 65535 per dimension. Large MUL_MAT
operations with batch sizes exceedeing this limi would fail.
* add compute_2d_workgroups() helper to split total workgroup ID across
X/Y dimensions
* update mul_mat_reg_tile.wgsl to reconstruct linear workgroup ID from 2D
dispatch
* update mul_mat_subgroup_matrix.wgsl to reconstruct linear workgroup ID
from 2D dispatch
* update mul_mat.wgsl to compute global index from 2D workgroup
coordinates
* refactor all three mul_mat dispatch paths to use the shared helper
* ggml-webgpu: add bounds checking for over-dispatched workgroups
2D workgroup dispatch can over-dispatch when total workgroups don't
divide evenly into the 65535 per-dimension limit. Extra workgroups
would compute invalid batch indices, causing memory corruption.
* add batch_idx bound check to mul_mat_reg_tile.wgsl and
mul_mat_subgroup_matrix.wgsl to prevent over-dispatched workgroups
from accessing invalid memory
* fixes test failures with large batch sizes (eg., bs=[128, 1024])
* ggml-webgpu: add back TODO for spliting large sizes into batches
* Optimize 2d workgroup provisioning
* Set some parameters that increase speed
---------
Co-authored-by: Reese Levine <reeselevine1@gmail.com>
* Allow webgpu_buf_pool to resize if needed, remove inflight_threads, and replace inflight_threads with num_kernels for submission
* Run clang-format
* Keep track of num batched kernels that have not been submitted yet
* Run clang-format
* Increase buf pool max size
* Increase param buf pool init size
* Remove webgpu buf pool resizing
* Merge with master
* Add buffer pool growth
* Move buffer pool growth outside of lock
* Reduce max pool size to 32
* Run clang-format
* Only resize param buf pool
* ggml-webgpu: Add binary op support for overlapping and non-contiguous.
* Add newline to binary.wgsl
* Append the test of binary op for src overlapping to test_bin_bcast.
* Remove unnecessary newline.
* vulkan: fix and enable cpy_tensor_async function
* use transfer_queue for async transfers on AMD, synchronize with timeline semaphore
* update offload_op logic
* fix missing transfer submission
* disable async transfer queue on AMD GCN
* revert op batch size change
* fix cpy_tensor_async checks
Piotr Wilkin (ilintar)
Bartowski
Todor Boinovski
Tom Vaucourt
Max Krasnyansky
Aman Gupta
Aaron Teo
shalinib-ibm
Tim Neumann
Aleksander Grygier
Johannes Gäßler
Georgi Gerganov
Roj234
lhez
YardenTal44
ymcki
Andreas Kieslinger
Eric Zhang
Sigbjørn Skjæret
Marcel Petrick
Nikhil Jain
Masashi Yoshimura
Adrien Gallouët
ddh0
SamareshSingh
standby24x7
Mickael Desgranges
Charles Xu
shaofeiqi
Abhijit Ramesh
Ruben Ortlam
oobabooga
Dmitry Atamanov