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Writing parallel programs that work

<!--HTML--><p align="justify"> Serial algorithms typically run inefficiently on parallel machines. This may sound like an obvious statement, but it is the root cause of why parallel programming is considered to be difficult. The current state of the computer industry is still...

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Detalles Bibliográficos
Autor principal: Petersen, Paul
Lenguaje:eng
Publicado: 2012
Materias:
Acceso en línea:http://cds.cern.ch/record/1455090
Descripción
Sumario:<!--HTML--><p align="justify"> Serial algorithms typically run inefficiently on parallel machines. This may sound like an obvious statement, but it is the root cause of why parallel programming is considered to be difficult. The current state of the computer industry is still that almost all programs in existence are serial. This talk will describe the techniques used in the Intel Parallel Studio to provide a developer with the tools necessary to understand the behaviors and limitations of the existing serial programs. Once the limitations are known the developer can refactor the algorithms and reanalyze the resulting programs with the tools in the Intel Parallel Studio to create parallel programs that work.</p> <h4> About the speaker</h4> <p align="justify"> Paul Petersen is a Sr. Principal Engineer in the Software and Solutions Group (SSG) at Intel. He received a Ph.D. degree in Computer Science from the University of Illinois in 1993. After UIUC, he was employed at Kuck and Associates, Inc. (KAI) working on auto-parallelizing compiler (KAP), and was involved in the early definition and implementations of OpenMP. While at KAI, he developed the Assure line of parallelization/correctness products, for Fortran, C++ and Java. In 2000, Intel Corporation acquired KAI, and he joined the software tools group. At Intel, he worked with the tools group to create the Thread Checker products, which evolved into the Inspector and Advisor components of the Intel&reg; Parallel Studio. &nbsp;Inspector uses dynamic binary instrumentation to detect memory and concurrency bugs, and Advisor uses similar techniques along with performance measurement and modeling to assist developers in transforming existing serial applications to be ready for parallel execution.</p>