Area-efficient memory scheduling for dynamically scheduled high-level synthesis
File(s)
Accepted version
Author(s)
He, Xuefei
Cheng, Jianyi
Constantinides, George
Type
Conference Paper
Abstract
In high-level synthesis, scheduling maps operations into clock cycles. It can either be done at compile time (statically) or run time (dynamically). There has been recent interests in dynamic scheduling as it can potentially achieve a better performance. The state-of-the-art dynamically scheduled HLS tool Dynamatic generates dataflow-style hardware in a netlist of pre-defined components connected using handshake signals. The memory operations are executed by a component named load-store queue (LSQ), which can achieve run-time out-of-order memory accesses for high performance. However, the additional logic for the LSQ leads to significant area overhead compared to static scheduling.
In this paper, we propose an area-efficient approach for scheduling memory operations at run time. We approximate the memory dependence distance to its minimal value and efficiently parallelise memory accesses in dynamically scheduled hardware. Over several benchmarks from related works, our results show that our approach achieves on average 0.2× of the area-delay
product compared to the original designs using LSQs.
In this paper, we propose an area-efficient approach for scheduling memory operations at run time. We approximate the memory dependence distance to its minimal value and efficiently parallelise memory accesses in dynamically scheduled hardware. Over several benchmarks from related works, our results show that our approach achieves on average 0.2× of the area-delay
product compared to the original designs using LSQs.
Date Issued
2022-12-15
Date Acceptance
2022-10-13
Citation
2022 International Conference on Field-Programmable Technology (ICFPT), 2022, pp.1-4
Publisher
IEEE
Start Page
1
End Page
4
Journal / Book Title
2022 International Conference on Field-Programmable Technology (ICFPT)
Copyright Statement
Copyright © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Source
IEEE International Conference on Field Programmable Technology (FPT 2022)
Publication Status
Published
Start Date
2022-12-05
Finish Date
2022-12-09
Coverage Spatial
Hong Kong SAR, China