Titlebook: Euro-Par 2011 Parallel Processing; 17th International E Emmanuel Jeannot,Raymond Namyst,Jean Roman Conference proceedings 2011 Springer-Ver

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Introduction. While multicore and manycore processors alleviate several problems that are related to single-core processors - known as memory wall, power wall, or instruction-level parallelism wall - they raise the issue of the programmability wall. The multicore and manycore programmability wall calls for new

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Ledger

Friction

A Generic Parallel Collection Frameworktables and trees. These data structures have a range of predefined operations which include mapping, filtering or finding elements. Such bulk operations traverse the collection and process the elements sequentially. Their implementation relies on iterators, which are not applicable to parallel opera

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Progress Guarantees When Composing Lock-Free Objects at least one operation, from a set of concurrently executed operations, finishes after a finite number of steps regardless of the state of the other operations. Lock-free data objects provide progress guarantees on the object level. In this paper, we first examine the progress guarantees provided b

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Engineering a Multi-core Radix Sortmaking use of write-combining yields a per-pass throughput corresponding to at least 89% of the system’s peak memory bandwidth. Our implementation outperforms Intel’s recently published radix sort by a factor of 1.64. It also compares favorably to the reported performance of an algorithm for Fermi?G

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敵意

A Novel Shared-Memory Thread-Pool Implementation for Hybrid Parallel CFD Solversce Computing (HPC) clusters with several thousands of cores using MPI-based domain decomposition. In order to make more efficient use of current multi-core CPUs and to prepare TAU for the many-core era, a shared-memory parallelization has been added to one of TAU’s solver to obtain a hybrid parallel

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A Fully Empirical Autotuned Dense QR Factorization for Multicore Architecturesehaviour of algorithms hard to forecast and model. In this paper, we tackle the issue of tuning a dense QR factorization on multicore architectures using a fully empirical approach.We exhibit a few strong empirical properties that enable us to efficiently prune the search space. Our method is automa

STIT

Accelerating Code on Multi-cores with FastFlowthis paper a new FastFlow programming methodology aimed at supporting parallelization of existing sequential code via offloading onto a dynamically created software accelerator is presented. The new methodology has been validated using a set of simple micro-benchmarks and some real applications.