Paper Info
Title
Biological Sequence Comparison on Hybrid Platforms with Dynamic Workload Adjustment
Abstract
This paper proposes and evaluates a strategy to run Biological Sequence Comparison applications on hybrid platforms composed of GPUs and multicores with SIMD extensions. Our strategy provides multiple task allocation policies and the user can choose the one which is more appropriate to his/her problem. We also propose a workload adjustment mechanism that tackles situations that arise when slow nodes receive the last tasks. The results obtained comparing query sequences to 5 public genomic databases in a platform composed of 4 GPUs and 2 multicores show that we are able to reduce the execution time with hybrid platforms, when compared to the GPU-only solution. We also show that our workload adjustment technique can provide significant performance gains in our target platforms.
Year
DOI
Venue
2013
10.1109/IPDPSW.2013.28
IPDPS Workshops
Keywords
Field
DocType
gpu-only solution,public genomic databases,execution time,last task,workload adjustment mechanism,simd extension,hybrid platform,dynamic workload adjustment,hybrid platforms,multiple task allocation policy,biological sequence comparison application,workload adjustment technique,bioinformatics,parallel processing,databases,database management systems,smith waterman,sequences,biology,genomics,field programmable gate arrays,task analysis,multicore processing,resource management
Task analysis,Computer science,Workload,Parallel computing,Parallel processing,SIMD,Smith–Waterman algorithm,Execution time
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
2
Name
Order
Citations
PageRank
Fernando Machado Mendonca1112.00
Alba Cristina Magalhaes Alves De Melo225333.90