Control of complex, flexible structures requires substantial amounts of computational power to achieve precision performance in both space and time. This is due to the fact that such structures are inherently multiple...
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Control of complex, flexible structures requires substantial amounts of computational power to achieve precision performance in both space and time. This is due to the fact that such structures are inherently multiple input, multiple output systems whose complexities increase significantly with each additional input or output parameter. The other design difficulty is due to the requirement of realtime computation and data communication since such systems have to be controlled on the fly. Thus, general purpose computer architectures are simply insufficient in this scenario. This paper introduces the development of an embedded computing system that supports the implementation of control algorithms on a segmented reflector telescope testbed. Decentralized algorithms have been recognized and proven to provide promising performance of control, and are being used for primary mirror shaping and precision pointing control of this testbed. The system architecture of the testbed is featured with a suite of interconnected signal processors and high performance I/O devices to meet the computational requirements, and hence, allows real-time performance of the control algorithms. The system also supports fault-tolerance during processor failure or recovery by leveraging the technologies of decentralized control with its associative pipelined task mapping mechanism
Advances in communication for parallel programming have yielded one-sided messaging systems. The MPI bindings for Ruby have been augmented to include the remote memory access functions of MPI-2.
ISBN:
(纸本)0780321754
Advances in communication for parallel programming have yielded one-sided messaging systems. The MPI bindings for Ruby have been augmented to include the remote memory access functions of MPI-2.
A programmable Java distributed system, which adapts to available resources, has been developed to minimise the overall processing time of computationally intensive problems. The system exploits the free resources of ...
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MRNet is an infrastructure that provides scalable multicast and data aggregation functionality for distributed tools. While evaluating MRNet's performance and scalability, we learned several important lessons abou...
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ISBN:
(纸本)0769521320
MRNet is an infrastructure that provides scalable multicast and data aggregation functionality for distributed tools. While evaluating MRNet's performance and scalability, we learned several important lessons about benchmarking large-scale, distributed tools and middleware. First, automation is essential for a successful benchmarking effort, and should be leveraged whenever possible during the benchmarking process. Second, microbenchmarking is invaluable not only for establishing the performance of low-level functionality, but also for design verification and debugging. third, resource management systems need substantial improvements in their support for running tools and applications together. Finally, the most demanding experiments should be attempted early and often during a benchmarking effort to increase the chances of detecting problems with the tool and experimental methodology.
Administration of Grid resources is a time consuming and often tedious job. Most administrative requests are predictable, and in general, handling them requires knowledge of the local resources and the requester. In t...
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New parallel Normalized Explicit Preconditioned Conjugate Gradient - type methods are introduced for solving finite element systems on distributed memory MIMD systems. The performance and applicability of the proposed...
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The paper is devoted to scalability analysis of a typical linear algebra algorithm on heterogeneous clusters. We proof that traditional scalability metrics proposed for analysis of linear algebra algorithms is applica...
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ISBN:
(纸本)0769522106
The paper is devoted to scalability analysis of a typical linear algebra algorithm on heterogeneous clusters. We proof that traditional scalability metrics proposed for analysis of linear algebra algorithms is applicable on heterogeneous platform and investigate influence of three heterogeneous strategies computation distribution to Scalable Universal Matrix Multiplication Algorithm (SUMMA) scalability.
In this paper the possibility of including automatic optimization techniques in the design of parallel dynamic programming algorithms in heterogeneous systems is analyzed. The main idea is to automatically approach th...
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In the last few years, research advances in dynamic scheduling at application and runtime system levels have contributed to improving the performance of scientific applications in heterogeneous environments. This pape...
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To solve the graph partitioning problem, efficient heuristics have been developed that are also capable of distributing the computational load in parallel FEM computations. However, although a few parallel implementat...
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ISBN:
(纸本)0769521320
To solve the graph partitioning problem, efficient heuristics have been developed that are also capable of distributing the computational load in parallel FEM computations. However, although a few parallel implementations do exist, the involved algorithms are hard to parallelize due to their sequential nature. This paper presents a new approach to deal with the FEM graph partitioning problem. Applying diffusion as a growing mechanism, we are able to eliminate restrictions of former implementations based on the bubble framework and construct a relatively simple algorithm with a high degree of "natural" parallelism. We demonstrate that it computes solutions comparable to those of established heuristics. Its drawback is the long execution time if the parallelism is not exploited.
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