Paper Info
Title
Extending Skel to Support the Development and Optimization of Next Generation I/O Systems
Abstract
As the memory and storage hierarchy get deeper and more complex, it is important to have new benchmarks and evaluation tools that allow us to explore the emerging middleware solutions to use this hierarchy. Skel is a tool aimed at automating and refining this process of studying HPC I/O performance. It works by generating application I/O kernel/benchmarks as determined by a domain-specific model. This paper provides some techniques for extending Skel to address new situations and to answer new research questions. For example, we document use cases as diverse as using Skel to troubleshoot I/O performance issues for remote users, refining an I/O system model, and facilitating the development and testing of a mechanism for runtime monitoring and performance analytics. We also discuss data oriented extensions to Skel to support the study of compression techniques for Exascale scientific data management.
Year
DOI
Venue
2017
10.1109/CLUSTER.2017.30
2017 IEEE International Conference on Cluster Computing (CLUSTER)
Keywords
Field
DocType
I/O benchmarking,Mini Applications,Generative Programming,High Performance I/O,Scientific Data Management,I/O performance,Skel,Adios,Runtime performance monitoring,Runtime performance analytics,Data Compression
Middleware,Troubleshooting,Data modeling,Use case,Computer science,Parallel computing,Input/output,Analytics,Data management,System model,Distributed computing
Conference
ISSN
ISBN
Citations 
1552-5244
978-1-5386-2327-5
0
PageRank 
References 
Authors
0.34
14
12
Name
Order
Citations
PageRank
Jeremy Logan115416.72
Jong Youl Choi230926.54
Matthew Wolf357539.27
George Ostrouchov414218.13
Lipeng Wan553.79
Norbert Podhorszki6104683.84
William F. Godoy7131.53
S. Klasky88212.77
Erich Lohrmann900.68
Greg Eisenhauer1086667.45
Chad Wood1132.09
Kevin A. Huck1211914.53