SwePub - sökning: WFRF:(Dokulil Jirí)

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1.	Dokulil, Jirí, et al. (författare) High-level Support for Hybrid Parallel Execution of C++ Applications Targeting Intel® Xeon Phi™ Coprocessors 2013 Ingår i: Procedia Computer Science. - : Elsevier. - 1877-0509. ; , s. 2508-2511 Konferensbidrag (refereegranskat)abstract The introduction of Intel® Xeon Phi™ coprocessors opened up new possibilities in development of highly parallel applications. Even though the architecture allows developers to use familiar programming paradigms and techniques, high-level development of programs that utilize all available processors (host+coprocessors) in a system at the same time is a challenging task.In this paper we present a new high-level parallel library construct which makes it easy to apply a function to every member of an array in parallel. In addition, it supports the dynamic distribution of work between the host CPUs and one or more coprocessors. We describe associated runtime support and use a physical simulation example to demonstrate that our library can facilitate the creation of C++ applications that benefit significantly from hybrid execution. Experimental results show that a single optimized source code is sufficient to simultaneously exploit all of the host's CPU cores and coprocessors efficiently.

Dokulil, Jirí, et al. (författare)
High-level Support for Hybrid Parallel Execution of C++ Applications Targeting Intel® Xeon Phi™ Coprocessors
2013
Ingår i: Procedia Computer Science. - : Elsevier. - 1877-0509. ; , s. 2508-2511
Konferensbidrag (refereegranskat)abstract
- The introduction of Intel® Xeon Phi™ coprocessors opened up new possibilities in development of highly parallel applications. Even though the architecture allows developers to use familiar programming paradigms and techniques, high-level development of programs that utilize all available processors (host+coprocessors) in a system at the same time is a challenging task.In this paper we present a new high-level parallel library construct which makes it easy to apply a function to every member of an array in parallel. In addition, it supports the dynamic distribution of work between the host CPUs and one or more coprocessors. We describe associated runtime support and use a physical simulation example to demonstrate that our library can facilitate the creation of C++ applications that benefit significantly from hybrid execution. Experimental results show that a single optimized source code is sufficient to simultaneously exploit all of the host's CPU cores and coprocessors efficiently.

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