Benchmarking High Bandwidth Memory on FPGAs

TL;DR

This paper benchmarks High Bandwidth Memory (HBM) on FPGAs using a custom tool, revealing its performance potential and impact of usage patterns, and compares it with DDR4 to guide optimal memory selection.

Contribution

It introduces Shuhai, a benchmarking tool for HBM on FPGAs, providing detailed, accurate performance insights and enabling comparisons with other memory types.

Findings

HBM achieves up to 425GB/s bandwidth

Memory usage patterns significantly affect performance

Shuhai enables precise, deterministic benchmarking

Abstract

FPGAs are starting to be enhanced with High Bandwidth Memory (HBM) as a way to reduce the memory bandwidth bottleneck encountered in some applications and to give the FPGA more capacity to deal with application state. However, the performance characteristics of HBM are still not well specified, especially in the context of FPGAs. In this paper, we bridge the gap between nominal specifications and actual performance by benchmarkingHBM on a state-of-the-art FPGA, i.e., a Xilinx Alveo U280 featuring a two-stack HBM subsystem. To this end, we propose Shuhai, a benchmarking tool that allows us to demystify all the underlying details of HBM on an FPGA. FPGA-based benchmarking should also provide a more accurate picture of HBM than doing so on CPUs/GPUs, since CPUs/GPUs are noisier systems due to their complex control logic and cache hierarchy. Since the memory itself is complex, leveraging custom hardware logic to benchmark inside an FPGA provides more details as well as accurate and deterministic measurements. We observe that 1) HBM is able to provide up to 425GB/s memory bandwidth, and 2) how HBM is used has a significant impact on performance, which in turn demonstrates the importance of unveiling the performance characteristics of HBM so as to select the best approach. As a yardstick, we also applyShuhaito DDR4to show the differences between HBM and DDR4.Shuhai can be easily generalized to other FPGA boards or other generations of memory, e.g., HBM3, and DDR3. We will makeShuhaiopen-source, benefiting the community