Tools for High Performance Computing: Proceedings of the 2nd by Terry Dontje, Don Kerr, Daniel Lacher, Pak Lui, Ethan

By Terry Dontje, Don Kerr, Daniel Lacher, Pak Lui, Ethan Mallove, Karen Norteman (auth.), Michael Resch, Rainer Keller, Valentin Himmler, Bettina Krammer, Alexander Schulz (eds.)

With the appearance of multi-core processors, enforcing parallel programming tools in software improvement is really precious in an effort to in achieving reliable functionality. quickly, 8-core and doubtless 16-core processors should be to be had, even for computer machines. To help software builders within the numerous initiatives all in favour of this procedure, a number of diversified instruments must be at his or her disposal. This workshop will supply the clients an outline of the present instruments within the sector of built-in improvement environments for clusters, numerous parallel debuggers, and new-style functionality research instruments, in addition to an replace at the cutting-edge of long term learn instruments, that have complex to an business point. The lawsuits of the 2d Parallel instruments Workshop consultant contributors via offering a technical review to assist them opt for which software fits the necessities for the advance job handy. also, in the course of the hands-on periods, the workshop will allow the person to instantly install the tools.

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We describe the actual checks, classes of errors being found, how memory buffers internally are being handled, show errors actually found in user’s code and the performance implications of this instrumentation. 1 Introduction Parallel programming with the distributed memory paradigm using the Message Passing Interface MPI [4] is often considered as an error-prone process. Great effort has been put into parallelizing libraries and applications using MPI. However when it comes to maintaining the software, optimizing for new hardware or even porting the code to other platforms and other MPI implementations, the developers will face additional difficulties [1].

Hockstein, V. R. Basili: The ASC-Alliance Projects: A Case Study of Large-Scale Parallel Scientific Code Development. IEEE Computer, Vol. 41, No. 3, March 2008, pp. 50–58 9. P. Kacsuk, J. C. Cunha, G. D´ozsa, J. Lourenc¸o, et. : A Graphical Development and Debugging Environment for Parallel Programs. Parallel Computing Vol. 22, No. 13, February 1997, pp. 1747–1770 10. P. H. Luckey, R. M. Pittman: Improving Software Quality Utilizing an Integrated CASE Environment. Proceedings of the IEEE National Aerospace and Electronics Conference, May 1991, pp.

This would require a homogeneous environment, which is per definition unrealistic in the grid world. In reality not only the grid itself is heterogeneous, but the users, who develop and debug the applications, also have different operating systems with different libraries running on machines with different architectures. Furthermore specific libraries, like for MPI, are usually not installed on a desktop machine. As a result locally compiled binaries may not be executable on the remote machine.

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