📚Modern CUDA Learn Notes with PyTorch: 200+ Tensor/CUDA Cores Kernels, ⚡️flash-attn-mma, ⚡️hgemm with WMMA, MMA and CuTe API (Achieve 98%~100% TFLOPS of cuBLAS/FA2 🎉🎉).

Several optimization methods of half-precision general matrix vector multiplication (HGEMV) using CUDA core.

An implementation of SGEMV with performance comparable to cuBLAS.

Matilda is a library to repeatedly multiply a constant matrix with a variable vector

Highly optimized DGEMV on CPU with both serial and parallel performance better than MKL and OpenBLAS.