diff options
author | Johannes Gäßler <johannesg@5d6.de> | 2023-07-29 23:04:44 +0200 |
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committer | GitHub <noreply@github.com> | 2023-07-29 23:04:44 +0200 |
commit | 11f3ca06b8c66b0427aab0a472479da22553b472 (patch) | |
tree | 8e934ff0d93a78447d996b00561f7ff826c3533f /README.md | |
parent | 9baf9ef304f330009d5a93b7390280a0fd27c9a1 (diff) |
CUDA: Quantized matrix matrix multiplication (#2160)
* mmq implementation for non k-quants
* q6_K
* q2_K
* q3_k
* q4_K
* vdr
* q5_K
* faster q8_1 loading
* loop unrolling
* add __restrict__
* q2_K sc_high
* GGML_CUDA_MMQ_Y
* Updated Makefile
* Update Makefile
* DMMV_F16 -> F16
* Updated README, CMakeLists
* Fix CMakeLists.txt
* Fix CMakeLists.txt
* Fix multi GPU out-of-bounds
Diffstat (limited to 'README.md')
-rw-r--r-- | README.md | 6 |
1 files changed, 4 insertions, 2 deletions
@@ -402,10 +402,12 @@ Building the program with BLAS support may lead to some performance improvements | Option | Legal values | Default | Description | |-------------------------|------------------------|---------|-------------| + | LLAMA_CUDA_CUBLAS | Boolean | false | Use cuBLAS instead of custom CUDA kernels for prompt processing. Faster for all quantization formats except for q4_0 and q8_0, especially for k-quants. Increases VRAM usage (700 MiB for 7b, 970 MiB for 13b, 1430 MiB for 33b). | + | LLAMA_CUDA_MMQ_Y | Positive integer >= 32 | 64 | Tile size in y direction when using the custom CUDA kernels for prompt processing. Higher values can be faster depending on the amount of shared memory available. Power of 2 heavily recommended. | | LLAMA_CUDA_FORCE_DMMV | Boolean | false | Force the use of dequantization + matrix vector multiplication kernels instead of using kernels that do matrix vector multiplication on quantized data. By default the decision is made based on compute capability (MMVQ for 6.1/Pascal/GTX 1000 or higher). Does not affect k-quants. | | LLAMA_CUDA_DMMV_X | Positive integer >= 32 | 32 | Number of values in x direction processed by the CUDA dequantization + matrix vector multiplication kernel per iteration. Increasing this value can improve performance on fast GPUs. Power of 2 heavily recommended. Does not affect k-quants. | - | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. | - | LLAMA_CUDA_DMMV_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels. Can improve performance on relatively recent GPUs. | + | LLAMA_CUDA_MMV_Y | Positive integer | 1 | Block size in y direction for the CUDA mul mat vec kernels. Increasing this value can improve performance on fast GPUs. Power of 2 recommended. Does not affect k-quants. | + | LLAMA_CUDA_F16 | Boolean | false | If enabled, use half-precision floating point arithmetic for the CUDA dequantization + mul mat vec kernels and for the q4_1 and q5_1 matrix matrix multiplication kernels. Can improve performance on relatively recent GPUs. | | LLAMA_CUDA_KQUANTS_ITER | 1 or 2 | 2 | Number of values processed per iteration and per CUDA thread for Q2_K and Q6_K quantization formats. Setting this value to 1 can improve performance for slow GPUs. | - #### CLBlast |