Address Assignment Sensitive Variable Partitioning and scheduling for DSPS with multiple memory banks

Chun Jason Xue, Tiantian Liu, Zili Shao, Jingtong Hu, Zhiping Jia, Weijia Jia, Edwin H.M. Sha

Research output: Chapter in book / Conference proceedingConference article published in proceeding or bookAcademic researchpeer-review

13 Citations (Scopus)

Abstract

Multiple memory banks design is employed in many high performance DSP processors. This architectural feature supports higher memory bandwidth by allowing multiple data memory access to be executed in parallel. Dedicated address generation units (AGUs) are commonly presented in DSPs to perform address arithmetic in parallel to the main datapath. Address assignment, optimization of memory layout of program variables to reduce address arithmetic instruction, has been studied extensively on single memory architecture. Make effective use of AGUs on multiple memory banks is a great challenge to compiler design and has not been studied previously. In this paper, we exploit address assignment with variable partitioning for scheduling on DSP architectures with multiple memory banks and AGUs. Our approach is built on novel graph models which capture both parallelism and serialism demands. An efficient scheduling algorithm, Address Assignment Sensitive Variable Partitioning (AASVP), is proposed to best leverage both multiple memory banks and AGUs. Experimental results show significant improvement compare to existing methods.
Original languageEnglish
Title of host publication2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
Pages1453-1456
Number of pages4
DOIs
Publication statusPublished - 16 Sep 2008
Event2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP - Las Vegas, NV, United States
Duration: 31 Mar 20084 Apr 2008

Conference

Conference2008 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP
CountryUnited States
CityLas Vegas, NV
Period31/03/084/04/08

Keywords

  • Design automation
  • Memory management
  • Program compilers
  • Scheduling

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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