A Model for Matrix Multiplication Performance on FPGAs

Computations involving matrices form the kernel of a large spectrum of computationally demanding applications for which FPGAs have been utilized as accelerators. Their performance is related to their underlying architectural and system parameters such as computational resources, memory and I/O bandwidth. A simple analytic model that gives an estimate of the performance of FPGA-based sparse matrix-vector and matrix-matrix multiplication is presented, dense matrix multiplication being a special case. The efficiency of existing implementations are compared to the model and performance trends for future technologies examined.