Paper Info
Title
Revealing Potential Performance Improvements by Utilizing Hybrid Work-Sharing for Resource-Intensive Seismic Applications
Abstract
Heterogeneous system architectures are becoming more and more of a commodity in the scientific community. While it remains challenging to fully exploit such architectures, the benefits in performance and hybrid speed-up, by using a host processor and accelerators in parallel in a non-monolithic matter, are significant. Hereby, the energy efficiency is becoming an increasingly critical challenge for future high-performance computing (HPC) systems, which do want to exceed the Exascale barrier with several competing architecture concepts ranging from high-performance CPUs, combined with GPUs acting as floating-point accelerators, to computationally weak CPUs, paired with dedicated and highly-perform ant FPGA-based accelerators. In this paper, we realize and evaluate a hybrid computing approach based on a two-dimensional seismic streaming algorithm with several heterogeneous system architectures, including conventional HPC approaches based on powerful CPUs and GPUs. Furthermore, we elaborate the effort on an embedded system platform claiming to be a "mini supercomputer" [1]. Several CPU and accelerator combinations are utilized in a manual work-sharing manner with the aim of achieving significant performance speed-ups and a detailed energy-efficiency study. Based on roofline models and experimental evaluations, the paper provides an insight into the fact that hybrid computing is mostly unconditionally beneficial for balanced systems regarding the performance as well as the energy efficiency, aiding the programmer in the decision whether or not costly, manually tuned, homogeneous implementations are worthwhile.
Year
DOI
Venue
2015
10.1109/PDP.2015.28
PDP
Keywords
DocType
ISSN
field programmable gate arrays,instruction sets,computational modeling,benchmark testing,computer architecture,floating point arithmetic,parallel processing
Conference
1066-6192
Citations 
PageRank 
References 
2
0.37
11
Authors
3
Name
Order
Citations
PageRank
Patrick Siegl131.08
Rainer Buchty214318.44
Mladen Berekovic335243.38