A heterogeneous accelerator platform for multi-subject voxel-based brain network analysis

Yu Wang, Mo Xu, Ling Ren, Xiaorui Zhang, Di Wu, Yong He, Ningyi Xu, Huazhong Yang

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The research on understanding the human brain has attracted more and more attention. A promising method is to model the brain as a network based on modern imaging technologies and then to apply graph theory algorithms for analysis. In this work, we examine the computing bottleneck of this method, and propose a CPU-GPU heterogeneous platform to accelerate the process. We construct a statistical brain network from a sample of 198 people and get characteristics such as nodal degree and modularity. This is the first study of voxel-based brain networks on large samples. We also illustrate that domain-specific hardware platform can have a significant impact on neuroscience studies.

Original languageEnglish (US)
Title of host publication2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011
Pages339-344
Number of pages6
DOIs
StatePublished - 2011
Externally publishedYes
Event2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011 - San Jose, CA, United States
Duration: Nov 7 2011Nov 10 2011

Publication series

NameIEEE/ACM International Conference on Computer-Aided Design, Digest of Technical Papers, ICCAD
ISSN (Print)1092-3152

Other

Other2011 IEEE/ACM International Conference on Computer-Aided Design, ICCAD 2011
CountryUnited States
CitySan Jose, CA
Period11/7/1111/10/11

Keywords

  • GPU Acceleration
  • Heterogeneous Platform
  • Human Connectome
  • Voxel-based Brain Network Analysis

ASJC Scopus subject areas

  • Software
  • Computer Science Applications
  • Computer Graphics and Computer-Aided Design

Fingerprint Dive into the research topics of 'A heterogeneous accelerator platform for multi-subject voxel-based brain network analysis'. Together they form a unique fingerprint.

Cite this