Paralelización de un esferizador geométrico

En este artículo se describe la paralelización de un esferizador geométrico utilizado en un detector jerárquico de colisiones. La paralelización se basa en la computación par alela con la utilización de la her r amienta PVM (Parallel Virtual Machine). Se discute la estrategia utilizada junto a la implementación. Finalmente, se muestran resultados experimentales y se discuten los resultados obtenidos

Performance evaluation of Fast Ethernet, ATM and Myrinet under PVM

Congestion in network switches can limit the communication traffic between Parallel Virtual Machine (PVM) nodes in a parallel computation. The research introduces a new benchmark to evaluate the performance of PVM in various networking environments. The benchmark is used to achieve a better understanding of performance limitations in parallel computing that are imposed by the choice of the network. The networks considered here are Fast Ethernet, Asynchronous Transfer Mode (ATM) OC-3c (155Mb/s) and Myrinet. Together, they represent an interesting range of alternatives for parallel cluster computing. A characterization of network delays and throughput and a comparison of the expected costs of the three environments are developed to provide a basis for an informed decision on the networking methods and topology for a parallel database that is being considered for FBI\u27s National DNA Indexing System (NDIS)[17]. This network is used for communications among the nodes of the parallel machine; thus the security requirements defined for the FBI\u27s Criminal Justice Information Services Division Wide Area Network (CJIS-WAN) [12] are not a concern

Performance Prediction of PVM Programs

As workstation clusters gain popularity as a parallel computing platform,there is an increasing need for performance tools that support these platforms. Performance prediction is important for performance analysis of scalable parallel applications. Although there are several performance tools available that work with PVM programs,none are capable of performance prediction. We have developed the APACHE (Automated PVM Application Characterization Environment) performance prediction system for PVM programs running on workstation clusters. We review the system implementation and present some experimental results obtained with the system. 1

Performance Prediction of PVM Programs

Introduction In general, a parallel computer is a computer that has multiple processors connected by a communication network and is capable of using all its processors simultaneously to solve a single problem [34]. Parallel computers have the computational power necessary to solve many of computational science's "grand challenge" problems [27, 34]. However, it can be quite difficult to write programs that perform well on parallel machines. The research proposed here is concerned with performance prediction as a programming and performance debugging tool for parallel computers. 1.1 Parallel Programming Paradigms To solve a problem on a parallel computer, the programmer divides the problem into pieces which are then distributed across the processors of the machine. The problem may be divided according to its functions (control or task parallelism) or its data (data parallelism). Fo