Analysis of high-performance floating-point arithmetic on FPGAs

Abstract

Summary form only given. FPGAs are increasingly being used in the high performance and scientific computing community to implement floating-point based hardware accelerators. We analyze the floating-point multiplier and adder/subtractor units by considering the number of pipeline stages of the units as a parameter and use throughput/area as the metric. We achieve throughput rates of more than 240 Mhz (200 Mhz) for single (double) precision operations by deeply pipelining the units. To illustrate the impact of the floating-point units on a kernel, we implement a matrix multiplication kernel based on our floating-point units and show that a state-of-the-art FPGA device is capable of achieving about 15 GFLOPS (8 GFLOPS) for the single (double) precision floating-point based matrix multiplication. We also show that FPGAs are capable of achieving up to 6x improvement (for single precision) in terms of the GFLOPS/W (performance per unit power) metric over that of general purpose processors. We then discuss the impact of floating-point units on the design of an energy efficient architecture for the matrix multiply kernel.