TopSort: A High-Performance Two-Phase Sorting Accelerator Optimized on HBM-Based FPGAs

2022 IEEE 30th Annual International Symposium on Field-Programmable Custom Computing Machines (FCCM)(2023)

Cited 10|Views86
No score
Abstract
The emergence of high-bandwidth memory (HBM) brings new opportunities to boost the performance of sorting acceleration on FPGAs, which was conventionally bounded by the available off-chip memory bandwidth. However, it is nontrivial for designers to fully utilize this immense bandwidth. First, the existing sorter designs cannot be directly scaled at the increasing rate of available off-chip bandwidth, as the required on-chip resource usage grows at a much faster rate and would bound the sorting performance in turn. Second, designers need an in-depth understanding of HBM's characteristics to effectively utilize the HBM bandwidth. To tackle these challenges, we present TopSort, a novel two-phase sorting solution optimized for HBM-based FPGAs. In the first phase, 16 merge trees work in parallel to fully utilize 32 HBM channels' bandwidth. In the second phase, TopSort reuses the logic from phase one to form a wider merge tree to merge the partially sorted results from phase one. TopSort also adopts HBM-specific optimizations to reduce resource overhead and improve bandwidth utilization. TopSort can sort up to 4 GB data using all 32 HBM channels, with an overall sorting performance of 15.6 GB/s. TopSort is 6.7x and 2.7x faster than state-of-the-art CPU and FPGA sorters.
More
Translated text
Key words
Field programmable gate arrays,Bandwidth,Sorting,Hardware,Throughput,System-on-chip,Optimization,merge sort,hardware acceleration,high-bandwidth memory,memory-centric design,FPGA,floorplan
AI Read Science
Must-Reading Tree
Example
Generate MRT to find the research sequence of this paper
Chat Paper
Summary is being generated by the instructions you defined