Temp1 #22
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Temp1 #22
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apicalshark
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Nov 22, 2024
apicalshark
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- I have read the contributing guidelines
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* Samplers sequence: simplified and input field. * Removed unused function * Modify and use `settings-modal-short-input` * rename "name" --> "label" --------- Co-authored-by: Xuan Son Nguyen <son@huggingface.co>
ggml-ci
* metal : add kernel arg structs (wip) * metal : fattn args ggml-ci * metal : cont + avoid potential int overflow [no ci] * metal : mul mat struct (wip) * cont : mul mat vec * cont : pass by reference * cont : args is first argument * cont : use char ptr * cont : shmem style * cont : thread counters style * cont : mul mm id ggml-ci * cont : int safety + register optimizations ggml-ci * metal : GGML_OP_CONCAT ggml-ci * metal : GGML_OP_ADD, GGML_OP_SUB, GGML_OP_MUL, GGML_OP_DIV * metal : GGML_OP_REPEAT * metal : GGML_OP_CPY * metal : GGML_OP_RMS_NORM * metal : GGML_OP_NORM * metal : add TODOs for rest of ops * ggml : add ggml-metal-impl.h ggml-ci
* Vulkan: Fix device info output format specifiers * Vulkan: Use zu printf specifier for size_t instead of ld
Flake lock file updates:
• Updated input 'nixpkgs':
'github:NixOS/nixpkgs/4aa36568d413aca0ea84a1684d2d46f55dbabad7?narHash=sha256-Zwl8YgTVJTEum%2BL%2B0zVAWvXAGbWAuXHax3KzuejaDyo%3D' (2024-11-05)
→ 'github:NixOS/nixpkgs/5e4fbfb6b3de1aa2872b76d49fafc942626e2add?narHash=sha256-OZiZ3m8SCMfh3B6bfGC/Bm4x3qc1m2SVEAlkV6iY7Yg%3D' (2024-11-15)
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
Seems like this isn't working for vulkan-over-metal when the array is sized by a spec constant. Maybe a spirv-cross limitation?
* vulkan: Optimize soft_max Large soft_max could already saturate memory, but small/medium sizes were pretty slow. The bulk of the gains for them comes from using a smaller workgroup size, and making the workgroup size match the subgroup size also makes the barriers much cheaper. Cache some values in locals to avoid refetching/recomputing. And stamp out a few "template instantiations" so smaller cases will fully unroll. Add a missing early return for OOB rows. This happens when there are more than 512 rows and the dispatch is 512 x H. * vulkan: Further soft_max optimizations Restore the workgroup size of 512 case, use it for >1024. Use unrollable loops for more iteration counts.
…anov#10266) * Add option to set the SYCL architecture for all targets * Convert GGML_SYCL_HIP_TARGET to the more generic GGML_SYCL_ARCH option * Document that setting GGML_SYCL_ARCH can improve the performance
Co-authored-by: arthw <14088817+arthw@users.noreply.github.com>
) * vulkan: Use pipeline_robustness to disable robustness in mul_mat_vec. Add some early returns for nonexistent rows in mul_mat_vec shaders. These can only be hit when dispatching a 2D grid of workgroups. Fix the logic for the 2D grid of workgroups to round up. Enable the pipeline robustness extension if it's available, and use it to disable robustness for these pipelines. The instructions to do the bounds checking contend for the same ALU resources as the bit twiddling dequant instructions. * vulkan: Add GLSL structure aliases for quant types to allow larger loads In Vulkan it's not possible to cast pointer types, so instead you have to declare an aliased binding for the memory with a different type. This commit adds aliases for the quant formats using 16b ints, and in a few places where the struct size is a multiple of 4 also using 32b ints. Currently only q4_k's aliases are used, but others will be used in subsequent commits. * vulkan: use larger loads in q5_k and q6_k shaders. Similar to the optimization I did in q4_k recently, this vectorizes some loads and reduces the number of bit twiddling instructions. * vulkan: use larger K step per iteration in mul_mat_vec. Add vec4 dequantization functions, and use them to do K=8 per iteration in mul_mat_vec. This uses 16b loads for the quant values and 128b loads for B which helps reduce the load on the memory system. The K_PER_ITER==2 logic is still there, just for F16/F32, and really only because they support unaligned sizes. Tweak the num_iters/unrolling logic to be simpler and catch a couple missed unrolling opportunities.
* cmake pkg: find accelerate, openmp, memkind libs * cmake pkg: find BLAS libs * try BLAS_LIBRARIES instead * Add BLAS link opts * Add more link deps. and set GGML_ vars
* cuda : optimize argmax * remove unused parameter ggml-ci * fixup : use full warps ggml-ci * Apply suggestions from code review Co-authored-by: Johannes Gäßler <johannesg@5d6.de> * fix ub * ggml : check ne00 <= INT32_MAX in argmax and argsort --------- Co-authored-by: Johannes Gäßler <johannesg@5d6.de>
…0216) * CANN Support Ascend310P to accelerate F32 and F16 Model * Add compile option soc type macro ASCEND_310P to ggml-cann lib * Remove unused code * Remove the ascend soc_type hard code compile option in CMakelist.txt
* GitHub: ask for more info in issues [no ci] * refactor issue templates to be component-specific * more understandable issue description * add dropdown for llama.cpp module
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