This special issue contains 6 selected papers whose preliminary versions appeared in the Proceedings of the 23rd annualacmsymposium on parallelism in algorithms and architectures (SPAA), held June 2011, in San Jose,...
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This special issue contains 6 selected papers whose preliminary versions appeared in the Proceedings of the 23rd annualacmsymposium on parallelism in algorithms and architectures (SPAA), held June 2011, in San Jose, California, USA. These papers were selected by the special issue co-editors from 35 papers that were presented at the conference. The authors were invited to submit full versions of their papers, which were then fully refereed according to the usual standards of Theory of Computing Systems. The selected papers are representative of the breadth and depth of the research in parallelism in algorithms and architectures that was presented at SPAA 2011.
The proceedings contain 7 papers from the symposium on parallelism in algorithms and architectures, SPAA 2003: 15th annualsymposium on parallelism in algorithms and architectures. The topics discussed include: a prac...
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The proceedings contain 7 papers from the symposium on parallelism in algorithms and architectures, SPAA 2003: 15th annualsymposium on parallelism in algorithms and architectures. The topics discussed include: a practical algorithm for constructing oblivious routing schemes;novel architectures for P2P applications: the continuous-discrete approach;quantifying instruction criticality for shared memory multiprocessors;relaxing the problem-size bound for out-of-core columnsort;the complexity of verifying memory coherence;a near optimal scheduler for switch-memory-switch routers;and on local algorithms for topology control and routing in ad hoc networks.
As the gap between the cost of communication (i.e., data movement) and computation continues to grow, the importance of pursuing algorithms which minimize communication also increases. Toward this end, we seek asympto...
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ISBN:
(纸本)9781450307437
As the gap between the cost of communication (i.e., data movement) and computation continues to grow, the importance of pursuing algorithms which minimize communication also increases. Toward this end, we seek asymptotic communication lower bounds for general memory models and classes of algorithms. Recent work [2] has established lower bounds for a wide set of linear algebra algorithms on a sequential machine and on a parallel machine with identical processors. This work extends these previous bounds to a heterogeneous model in which processors access data and perform floating point operations at differing speeds. We also present an algorithm for dense matrix multiplication which attains the lower bound.
Energy consumption by computer systems has emerged as an important concern However, the energy consumed in executing an algorithm cannot be inferred from its performance alone it must be modeled explicitly This paper ...
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ISBN:
(纸本)9781450300797
Energy consumption by computer systems has emerged as an important concern However, the energy consumed in executing an algorithm cannot be inferred from its performance alone it must be modeled explicitly This paper analyzes energy consumption of parallel algorithms executed on shared memory multicore processors Specifically, we develop a methodology to evaluate how energy consumption of a given parallel algorithm changes as the number of cores and their frequency is varied We use this analysis to establish the optimal number of cores to minimize the energy consumed by the execution of a parallel algorithm for a specific problem size while satisfying a given performance requirement We study the sensitivity of our analysis to changes in parameters such as the ratio of the power consumed by a computation step versus the power consumed in accessing memory The results show that the relation between the problem size and the optimal number of cores is relatively unaffected for a wide range of these parameters.
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