FPGA-based lossless compressors of floating-point data streams to enhance memory bandwidth

Abstract

This paper presents an FPGA-based lossless compressor which directly compresses floating-point data streams to enhance the actual memory bandwidth of lattice Boltzmann method (LBM) accelerators. We show that the compression algorithms based on the 1D polynomial prediction are suitable for high-throughput hardware design. Moreover we show that integer operations provide comparable prediction performance to a floating-point predictor, while an integer predictor is expected to have smaller circuits than a floating-point one. We evaluate the compression ratio, the operating frequency and the resource consumption of the compressors with integer-based predictors through their prototype implementation using ALTERA Stratix III FPGA. We demonstrate that the implemented compressors dominate only 0.15 to 0.23 % of the entire logic resources and operate at 95 to 174 MHz to provide the compression ratio of up to 3.5, which means that we can enhance the memory bandwidth by a factor of 3.5 on average.