大小的block, 根据MMult_4x4_7.c (https://github.com/flame/how-to-optimize-gemm/blob/master/src/MMult_4x4_7.c)和 MMult_4x4_8.c (https://github.com/flame/how-to-optimize-gemm/blob/master/src/MMult_4x4_8.c)代码,可以看出MMult_4x4_8.c使用了偏移量完成内存对齐。 这样我们就可以参考工程...
how-to-optimize-gemm English |简体中文 News 2023/08 aarch64 add cmake and mperf, try-DMPERF_ENABLE=ON! Introduction row-major matmul optimization tutorial backendarmv7aarch64aarch64-int8cudacuda-int4vulkanx86 support✔️✔️✔️✔️-✔️✅ ...
This project integrates a custom CUDA-based matrix multiplication kernel into a PyTorch deep learning model, leveraging GPU acceleration for matrix operations. The goal is to compare the performance of this custom kernel with PyTorch's built-in matrix mu
The WMMA instruction optimizes the scheduling of data movement and peak math operations with minimal VGPR access by providing source data reuse and intermediate destination data forwarding operations without interruption. The regular patterns experienced in matrix operations enable WMMA instructions to reduce...
MindSpore supports heterogeneous computing power. In addition to Huawei's self-developed Da Vinci-based Ascend NPU, it also supports the operation of CPU (eg MKLDNN) and GPU (eg CUDA kernels) operators. (Note: MindSpore supports the entire network to run on different hardware platforms, and do...
知道tpoisonooo/how-to-optimize-gemm 怎么编译、运行,顺手点个 star 吧 我们看最终效果吧,第一版/最新版本/cuBLAS 大比拼: 橙色是最初版本;蓝色是 cuBLAS;绿色是最新 环境说明: 可以看到小抄还是很给力的,学到最后可以超过 cuBLAS～ 核心小抄: MegEngine Bot:CUDA 矩阵乘法终极优化指南,没源码,前 8 版实现都...
How to optimize GEMM on CPU 教程讲解。(https:///apache/tvm/blob/main/gallery/how_to/optimize_operators/opt_gemm.py) 并细致梳理每一种优化方法的作用以及它们在IR中的表示。 Optimizing Operators with Schedule Templates and AutoTVM 教程讲解。(https:///apache/tvm/blob/main/gallery/tutorial/autotvm...