NDLI: $${\mathrm{DS}}_{\mathrm{spirit}}$$ : a data dependence and stride reference patterns profiling infrastructure

Content Provider	Springer Nature Link
Author	Yu, Hairong Li, Guohui Shu, LihChyun
Copyright Year	2016
Abstract	Despite the widespread use of multi-core processors in modern computer systems, developing software tools so as to make best use of available computing resources has never been more urgent. This is because a considerable amount of spurious dependence and cache misses lurking in general-purpose applications restricts seriously the extraction of potential parallelism on the nowadays prevalent multi-core machines. Existing tools are limited in their ability to thoroughly detect data dependence and provide prefetched objects simultaneously. Further, some of the tools are unable to profile large-scale applications. To address this problem, we propose a novel profiler, called $${\mathrm{DS}}_{\mathrm{spirit}}$$ , that performs both data dependence and stride reference profiling. Data dependence profiling employs a hash-based scheme to detect actual data dependence while filtering out useless dependence via timestamps. Stride reference profiling employs value profiling to profile the stride pattern for each dynamic load and select the profitable loads as prefetched objects for compilers. To demonstrate the effectiveness of $${\mathrm{DS}}_{\mathrm{spirit}}$$ , we have evaluated it using several SPEC CPU2006, MPI2007 and OMP2012 benchmarks on an Intel i7-4700 machine. Experimental results show that $${\mathrm{DS}}_{\mathrm{spirit}}$$ produces accurate profiling results, including expected data dependence and prefetched objects, which in turn contributes to more opportunities for extracting parallelism.
Starting Page	770
Ending Page	788
Page Count	19
File Format	PDF
ISSN	09208542
Journal	The Journal of Supercomputing
Volume Number	72
Issue Number	2
e-ISSN	15730484
Language	English
Publisher	Springer US
Publisher Date	2016-01-16
Publisher Place	New York
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Profiler Profiling-based approach Stride reference patterns Data dependence profiling Programming Languages, Compilers, Interpreters Processor Architectures Computer Science
Content Type	Text
Resource Type	Article
Subject	Theoretical Computer Science Information Systems Hardware and Architecture Software

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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