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Titlebook: Recent Advances in the Message Passing Interface; 18th European MPI Us Yiannis Cotronis,Anthony Danalis,Jack Dongarra Conference proceeding

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41#
發(fā)表于 2025-3-28 16:55:16 | 只看該作者
Design and Evaluation of Nonblocking Collective I/O Operations,associated with developing nonblocking collective I/O operations, in order to help hiding the costs of I/O operations. We also present an implementation based on the libNBC library, and evaluate the benefits of nonblocking collective I/O over a PVFS2 file system for a micro-benchmark and a parallel
42#
發(fā)表于 2025-3-28 18:47:24 | 只看該作者
43#
發(fā)表于 2025-3-28 23:36:52 | 只看該作者
A uGNI-Based MPICH2 Nemesis Network Module for the Cray XE,r developing Network Modules (Netmods) for interfacing the Nemesis subsystem to various high speed network protocols. Cray has developed a user-level Generic Network Interface (uGNI) for interfacing MPI implementations to the internal high speed network of Cray XE and follow-on computer systems. Thi
44#
發(fā)表于 2025-3-29 03:20:08 | 只看該作者
45#
發(fā)表于 2025-3-29 08:47:59 | 只看該作者
46#
發(fā)表于 2025-3-29 14:29:37 | 只看該作者
Scalable Memory Use in MPI: A Case Study with MPICH2,hers believe that existing MPI implementations, if used unchanged, will themselves consume a large fraction of the available system memory at exascale. To investigate and address this issue, we undertook a study of the memory consumed by the MPICH2 implementation of MPI, with a focus on identifying
47#
發(fā)表于 2025-3-29 16:50:35 | 只看該作者
Performance Expectations and Guidelines for MPI Derived Datatypes,on. This paper formulates . for derived datatypes. Such guidelines make performance expectations for derived datatypes explicit and suggest relevant optimizations to MPI implementers. We also identify self-consistent guidelines that are too strict to enforce, because they entail NP-hard optimization
48#
發(fā)表于 2025-3-29 22:32:53 | 只看該作者
49#
發(fā)表于 2025-3-30 03:11:09 | 只看該作者
50#
發(fā)表于 2025-3-30 06:47:12 | 只看該作者
Achieving Exascale Computing through Hardware/Software Co-design,em software and algorithmic innovation is needed as well. Since both architectures and software are expected to evolve significantly there is a potential to use the co-design methodology that has been developed by the embedded computing community. A new co-design methodology for high performance computing is needed.
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