Computer Engineering Commons^™

High-Performance Matrix Multiplication On Intel And Fgpa Platforms, Gang Li

Theses

Matrix multiplication is at the core of high-performance numerical computation. Software methods of accelerating matrix multiplication fall into two categories. One is based on calculation simplification. The other one is based on increasing the memory access efficiency. Also matrix multiplication can be accelerated using vector processors. In this investigation, various matrix multiplication algorithms and the vector-based hardware acceleration method are analyzed and compared in terms of performance and memory requirements. Results are shown for Intel and Xilinx FPGA platforms. They show that when the CPU is fast, Goto's algorithm runs faster than Strassen's algorithm because the data access speed is …