生存环境
发表于 2025-3-25 06:25:26
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Deject
发表于 2025-3-25 08:05:28
Managing Your Workforce on a Computational Gridr real-life situations, the master has to decide on a target size and composition for the workforce, a recruiting strategy and a dismissal policy. It has to decide on who does what and how to deal with workers that do not complete their assigned task on time.
CRUMB
发表于 2025-3-25 14:58:23
Multiple Parallel Local Searches in Global Optimization of the simple multi-start local search strategy and the unified Bayesian global stopping criterion outperforms a number of leading global optimization algorithms, for both serial and parallel implementations. Results for parallel clusters of up to 128 machines are presented.
联邦
发表于 2025-3-25 18:21:33
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entice
发表于 2025-3-25 22:36:51
PVM and MPI: What Else Is Needed for Cluster Computing?puting has evolved from Crays and networks of workstations to Commodity-off-the-shelf (COTS) clusters. During this evolution, schedulers, monitors, and resource managers were added on top of PVM and MPI. This talk looks forward and predicts what software besides PVM and MPI will be needed to effecti
Apoptosis
发表于 2025-3-26 01:40:46
Managing Your Workforce on a Computational Grid time, the master of the application controls a collection of CPUs that has been allocated to the application by the resource manager of the grid. Effective management of this dynamic “workforce” of CPUs holds the key to ability of the application to meet its computational objectives. Like in simila
昏睡中
发表于 2025-3-26 07:16:59
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LAVE
发表于 2025-3-26 10:32:08
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sacrum
发表于 2025-3-26 13:30:22
A Benchmark for MPI Derived Datatypestatypes are covered by the benchmark, and varied along different dimensions. This is controlled bya set of predened patterns which can be instantiated bypa rameters given bythe user in a configurationsle. We classifythe patterns intofixed types, dynamic types, nested types, and special types. We sho
公理
发表于 2025-3-26 16:46:39
Working with MPI Benchmarking Suites on ccNUMA Architecturesbenchmarking suites which are mostly hidden to the user turned out as being of considerable influence on the benchmarking results for ccNUMA systems such as number and location of buffers, warm-up of the cache before running the benchmark, or procedure of measuring the time. In addition, we consider