Parallel conjugate gradient algorithms for solving the Neutron Diffusion Equation on SUPERNUM

Böhm, A. P. Wim; Brehm, Jürgen; Finnemann, H.

doi:10.1145/109025.109071

Cited by 3 publications

(1 citation statement)

References 6 publications

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“…We have already gained experience using our tools in several different environments. SUPRENUM [ST88,BBF91] is a loosely coupled parallel architecture consisting of up to 256 processing nodes. Each node has a CPU, 8 MBytes of memory and several coprocessors (among them a vector processing unit).…”

Section: Monitoring Program Behavior On Suprenummentioning

confidence: 99%

Distributed performance monitoring: methods, tools, and applications

Hofmann

Klar

Mohr

et al. 1994

IEEE Trans. Parallel Distrib. Syst.

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A method for analyzing the functional behavior and the performance of programs in distributed systems is presented. We use hybrid monitoring, a technique which combines advantages of both software monitoring and hardware monitoring. The paper contains a description of a hardware monitor and a software package (ZM4/SIMPLE) which make our concepts available to programmers, assisting them in debugging and tuning of their code. A short survey of related monitor systems highlights the distinguishing features of our implementation. As an application of our monitoring and evaluation system, the analysis of a parallel ray tracing program running on the SUPRENUM multiprocessor is described. It is shown that monitoring and modeling both rely on a common abstraction of a system's dynamic behavior and therefore can be integrated to one comprehensive methodology. This methodology is supported by a set of tools.

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Section: Monitoring Program Behavior On Suprenummentioning

confidence: 99%

Distributed performance monitoring: methods, tools, and applications

Hofmann

Klar

Mohr

et al. 1994

IEEE Trans. Parallel Distrib. Syst.

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Monitoring program behaviour on SUPRENUM

Siegle

Hofmann²

1992

Proceedings of the 19th Annual International Symposium on Computer Architecture - ISCA '92

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Monitoring program behaviour on SUPRENUM

SiegleMarkus¹,

HofmannRichard²

1992

SIGARCH Comput. Archit. News

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It is often very difficult for programmers of parallel computers to understand how their parallel programs behave at execution time, because there is not enough insight into the interactions between concurrent activities in the parallel machine. Programmers do not only wish to obtain statistical information that can be supplied by profiling, for example. They need to have detailed knowledge about the functional behaviour of their programs. Considering performance aspects, they need timing information as well. Monitoring is a technique well suited to obtain information about both functional behaviour and timing. Global time information is essential for determining the chronological order of events on different nodes of a multiprocessor or of a distributed system, and for determining the duration of time intervals between events from different nodes. A major problem on multiprocessors is the absence of a global clock with high resolution. This problem can be overcome if a monitor system capable of supplying globally valid time stamps is used. In this paper, the behaviour and performance of a parallel program on the SUPRENUM multiprocessor is studied. The method used for gaining insight into the runtime behaviour of a parallel program is hybrid monitoring, a technique that combines advantages of both software monitoring and hardware monitoring. A novel interface makes it possible to measure program activities on SUPRENUM. The SUPRENUM system and the ZM4 hardware monitor are briefly described. The example program under study is a parallel ray tracer. We show that hybrid monitoring is an excellent method to provide programmers with valuable information for debugging and tuning of parallel programs.

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Parallel conjugate gradient algorithms for solving the Neutron Diffusion Equation on SUPERNUM

Cited by 3 publications

References 6 publications

Distributed performance monitoring: methods, tools, and applications

Distributed performance monitoring: methods, tools, and applications

Monitoring program behaviour on SUPRENUM

Monitoring program behaviour on SUPRENUM

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