一种自适应可重构通用浮点加速器的设计

余振波; 聂言硕; 宋宇鲲; 侯宁

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一种自适应可重构通用浮点加速器的设计

更新时间：2026-09-04

- 一种自适应可重构通用浮点加速器的设计
- Design of an adaptive reconfigurable general-purpose floating-point accelerator
- 微电子学与计算机 2021年38卷第1期页码：89-94
- 作者机构：
  
  1. 合肥工业大学电子科学与应用物理学院,安徽,合肥,230009
  2. 河南城建学院机构电气与控制工程学院,河南,平顶山,467041
- 作者简介：
- 基金信息：
  
  国家自然科学基金 61874156
- DOI：
  中图分类号：
- 纸质出版：2021
- 稿件说明：
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余振波, 聂言硕, 宋宇鲲, 侯宁. 一种自适应可重构通用浮点加速器的设计[J]. 微电子学与计算机, 2021, 38(1): 89-94.

YU Zhen-bo, NIE Yan-shuo, SONG Yu-kun, et al. Design of an adaptive reconfigurable general-purpose floating-point accelerator[J]. 2021, 38(1): 89-94.
余振波, 聂言硕, 宋宇鲲, 侯宁. 一种自适应可重构通用浮点加速器的设计[J]. 微电子学与计算机, 2021, 38(1): 89-94. DOI：

YU Zhen-bo, NIE Yan-shuo, SONG Yu-kun, et al. Design of an adaptive reconfigurable general-purpose floating-point accelerator[J]. 2021, 38(1): 89-94. DOI：

摘要

用加速器因其专业性过强往往缺乏一定的灵活性，在处理不同类型的应用时不可避免的导致能效比的下降.本文设计了一款自适应可重构浮点加速器，它可以根据计算任务需求和可重构计算资源使用情况，在运行时将计算任务映射到可重构计算资源，具有自适应可重构的能力.该浮点加速器整体采用“RISC-V+可重构浮点运算单元”的架构，可重构浮点运算单元由一系列粗粒度浮点运算器构成，负责具体的浮点计算.该设计在Xilinx Ultrascale XCVU440FPGA芯片上进行了原型验证，结果表明，该浮点加速器具有较广的应用面，运算效率高，算法适应性强.

Abstract

Application-specific accelerators often lack flexibility due to their professionalism

which inevitably leads to the decrease ofenergy efficiency during the execution of a wide range of applications. In this paper

an adaptive reconfigurable floating-point accelerator is designed

which can automatically map computing tasks to reconfigurable computing resources at runtime basing on computing task requirements and the status of reconfigurable computing resources. The floating-point accelerator uses the architecture of "RISC-V + Reconfigurable Floating-point Arithmetic Unit". The reconfigurable floating-point arithmetic unit consists of a series of coarse-grained floating-point arithmetic units

which are responsible for specific floating-point calculations.The design has been prototypical verified on the Xilinx Ultrascale XCVU440 FPGA chip

and the results show that the floating-point accelerator has wider applicability

high operation efficiency

and high algorithm adaptability.

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references

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