Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.
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Updated
Sep 8, 2024 - Cuda
Several optimization methods of half-precision general matrix multiplication (HGEMM) using tensor core with WMMA API and MMA PTX instruction.
Multiple GEMM operators are constructed with cutlass to support LLM inference.
Several common methods of matrix multiplication are implemented on CPU and Nvidia GPU using C++11 and CUDA.
Use tensor core to calculate back-to-back HGEMM (half-precision general matrix multiplication) with MMA PTX instruction.
A high-performance INT8 Matrix Multiplication Accelerator implemented in pure Verilog, optimized for Edge AI inference on Xilinx Kria KV260 (Zynq UltraScale+ MPSoC).
c lib for calculating matrices
Systolic array PE for matrix multiply — SVA formal verification, OpenLane synthesis
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