Paper Info
Title
Application Performance Analysis And Efficient Execution On Systems With Multi-Core Cpus, Gpus And Mics: A Case Study With Microscopy Image Analysis
Abstract
We carry out a comparative performance study of multi-core CPUs, GPUs and Intel Xeon Phi (Many Integrated Core (MIC)) with a microscopy image analysis application. We experimentally evaluate the performance of computing devices on core operations of the application. We correlate the observed performance with the characteristics of computing devices and data access patterns, computation complexities, and parallelization forms of the operations. The results show a significant variability in the performance of operations with respect to the device used. The performances of operations with regular data access are comparable or sometimes better on a MIC than that on a GPU. GPUs are more efficient than MICs for operations that access data irregularly, because of the lower bandwidth of the MIC for random data accesses. We propose new performance-aware scheduling strategies that consider variabilities in operation speedups. Our scheduling strategies significantly improve application performance compared with classic strategies in hybrid configurations.
Year
DOI
Venue
2017
10.1177/1094342015594519
INTERNATIONAL JOURNAL OF HIGH PERFORMANCE COMPUTING APPLICATIONS
Keywords
DocType
Volume
Hybrid systems, GPGPU, Intel Xeon Phi, cooperative execution, image analysis
Journal
31
Issue
ISSN
Citations 
1
1094-3420
2
PageRank 
References 
Authors
0.37
23
6
Name
Order
Citations
PageRank
George Teodoro120.37
Tahsin M. Kurç21423149.77
Guilherme Andrade3151.59
Jun Kong423729.70
Renato Ferreira5121.54
Joel H. Saltz64046569.91