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Titlebook: Algorithms and Architectures for Parallel Processing, Part II; 11th International C Yang Xiang,Alfredo Cuzzocrea,Wanlei Zhou Conference pro

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樓主: energy
11#
發(fā)表于 2025-3-23 10:33:49 | 只看該作者
Der Jahresabschlu? in Industriebetriebentural representation for their problem domains..Software Transactional Memory (STM) has been proposed as a new concurrency control mechanism that simplifies concurrent programming. Yet, most STM implementations have no special representation for arrays. This results, on many STMs, in inefficient int
12#
發(fā)表于 2025-3-23 14:59:08 | 只看該作者
13#
發(fā)表于 2025-3-23 19:00:00 | 只看該作者
14#
發(fā)表于 2025-3-23 22:47:26 | 只看該作者
https://doi.org/10.1007/978-3-663-20149-6able for scientific studies. Multiple Replications in Parallel (MRIP) is a distributed scenario of sequential quantitative stochastic simulation which offers significant speedup of simulation if it is executed on multiple computers of a local area network. We report results of running MRIP simulatio
15#
發(fā)表于 2025-3-24 02:47:53 | 只看該作者
16#
發(fā)表于 2025-3-24 07:07:19 | 只看該作者
17#
發(fā)表于 2025-3-24 13:46:02 | 只看該作者
https://doi.org/10.1007/978-3-663-13592-0etermined. For this purpose, different computational approaches have been introduced. Genetic algorithms can be used to search the vast space of all possible conformations of a protein in order to find its native structure. A framework for design of such algorithms that is both generic, easy to use
18#
發(fā)表于 2025-3-24 18:25:24 | 只看該作者
,Der Jahresabschlu? nach dem Kontenplan,mission. Vehicle is extremely personal device; therefore personal information, so called privacy has to be protected. In this paper, we analyze identity and location privacy threatening factors, problems, and solutions based on network model. To analyze solution’s effectiveness, we define four attac
19#
發(fā)表于 2025-3-24 22:51:57 | 只看該作者
20#
發(fā)表于 2025-3-24 23:33:38 | 只看該作者
https://doi.org/10.1007/978-3-322-98996-3 platform. In particular, we extend our simulations to larger and more complex SNP systems using an NVIDIA Tesla C1060 GPU. The C1060 is manufactured for high performance computing and massively parallel computations, matching the maximally parallel nature of SNP systems. Using our GPU accelerated s
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