Accelerating full-system simulation and app analysis through focused multi-granularity profiling

Tzu Hsiang Su, Wei Shan Wu, Chen Te Chou, Yuan Chun Cheng, Meng Ting Tsai, Tien-Fu Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

Faced with the rapid divergence of hardware used on embedded devices, there is a need for a tool that can efficiently assist with hardware/software co-design and architecture verification. Speeding up those ESL phases greatly reduces the length of development periods. To address this issue, our work implements a novel multi-granularity tracer for Android's simulator to provide ESL hardware design performance analysis and verification. In addition, we propose a flexible ESL module interface for system hardware designers to explore new hardware components via simple modules. Our work also enables software developers to identify performance bottleneck and assess software performance of new hardware components. Our case studies and experimental results show that our multi-granularity Android tracer can strip away irrelevant information to shave time off the architecture development period.

Original languageEnglish
Title of host publicationESLsyn 2014 - Proceedings of the 2014 Electronic System Level Synthesis Conference, Co-located with 51st DAC
PublisherIEEE Computer Society
ISBN (Print)9791092279030
DOIs
StatePublished - 2014
Event4th Electronic System Level Synthesis Conference, ESLsyn 2014 - San Francisco, CA, United States
Duration: 31 May 20141 Jun 2014

Publication series

NameProceedings of the electronic system level synthesis conference
ISSN (Print)2117-4628

Conference

Conference4th Electronic System Level Synthesis Conference, ESLsyn 2014
Country/TerritoryUnited States
CitySan Francisco, CA
Period31/05/141/06/14

Keywords

  • Android
  • QEMU
  • system behavior
  • vertical tracing
  • virtual machine

Fingerprint

Dive into the research topics of 'Accelerating full-system simulation and app analysis through focused multi-granularity profiling'. Together they form a unique fingerprint.

Cite this