phiGEMM: CPU-GPU hybrid matrix-matrix multiplication library

gemm baseline code.

The repository targets the OpenCL gemm function performance optimization. It compares several libraries clBLAS, clBLAST, MIOpenGemm, Intel MKL(CPU) and cuBLAS(CUDA) on different matrix sizes/vendor's hardwares/OS. Out-of-the-box easy as MSVC, MinGW, Linux(CentOS) x86_64 binary provided. 在不同矩阵大小/硬件/操作系统下比较几个BLAS库的sgemm函数性能，提供binary，开盒即用。

My experiments with convolution

Fast Matrix Multiplication Implementation in C programming language. This matrix multiplication algorithm is similar to what Numpy uses to compute dot products.

Manually optimize the GEMM (GEneral Matrix Multiply) operation. There is a long way to go.

Implementations of DGEMM algorithm using different tricks to optimize the performance.

Case Studies for using Accera - the open source cross-platform compiler from Microsoft Research - to create high performance deep learning computations (i.e. GEMM, Convolution, etc.)

Generate optimized MatMul cuda kernel automatically using tvm auto schedule.

Implementations of SGEMM algorithm on Nvidia GPU using different tricks to optimize the performance.

My attempt of making a GEMM kernel...

row-major matmul optimization

Fast SpMM implementation on GPUs for GNN (IPDPS'23)

ConvLIB is a library of convolution kernels for multicore processors with ARM (NEON) or RISC-V architecture