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 to classic strategies in hybrid configurations.
authors.affiliation: Department of Computer Science, University of Brasília, Brasília, DF, Brazil.
authors.forename: George
authors.initials: G
authors.lastname: Teodoro
authors.affiliation: Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA; Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
authors.forename: Tahsin
authors.initials: T
authors.lastname: Kurc
authors.affiliation: Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil.
authors.forename: Guilherme
authors.initials: G
authors.lastname: Andrade
authors.affiliation: Department of Biomedical Informatics, Emory University, Atlanta, GA, USA.
authors.forename: Jun
authors.initials: J
authors.lastname: Kong
authors.affiliation: Department of Computer Science, Federal University of Minas Gerais, Belo Horizonte, MG, Brazil.
authors.forename: Renato
authors.initials: R
authors.lastname: Ferreira
authors.affiliation: Department of Biomedical Informatics, Stony Brook University, Stony Brook, NY, USA; Scientific Data Group, Oak Ridge National Laboratory, Oak Ridge, TN, USA.
authors.forename: Joel
authors.initials: J
authors.lastname: Saltz
keywords: Cooperative Execution; GPGPU; Hybrid Systems; Image Analysis; Intel Xeon Phi