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Titlebook: Algorithms and Architectures for Parallel Processing; 14th International C Xian-he Sun,Wenyu Qu,Lei Liu Conference proceedings 2014 Springe

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樓主: 他剪短
51#
發(fā)表于 2025-3-30 08:54:31 | 只看該作者
Utilizing Multiple Xeon Phi Coprocessors on One Compute Node,multiple Xeon Phi coprocessors that lie inside one compute node. Besides a standard MPI-OpenMP programming approach, which belongs to the symmetric usage mode, two offload-mode programming approaches are considered. The first offload approach is conventional and uses compiler pragmas, whereas the se
52#
發(fā)表于 2025-3-30 14:21:56 | 只看該作者
53#
發(fā)表于 2025-3-30 19:48:39 | 只看該作者
Service Scheduling Algorithm in Vehicle Embedded Middleware, hinders the development of vehicle electronics. First, in this paper, we proposed a SOA-based middleware for vehicular embedded system, which makes it possible for each ECU to dispatch and receive data on the bus by service, it will hide the underlying heterogeneity. Second, on the basis of the veh
54#
發(fā)表于 2025-3-30 23:09:09 | 只看該作者
55#
發(fā)表于 2025-3-31 04:47:33 | 只看該作者
Equi-join for Multiple Datasets Based on Time Cost Evaluation Model,ion, equi-join is an important operation. However, it is inefficient to perform equi-join operations in MapReduce when multiple datasets are involved in the join. In this paper, a time cost evaluation model is extended for an equi-join by considering the time cost of calculation. In addition, the su
56#
發(fā)表于 2025-3-31 08:48:58 | 只看該作者
57#
發(fā)表于 2025-3-31 09:30:37 | 只看該作者
Conpy: Concolic Execution Engine for Python Applications,rk, we propose a concolic execution engine for Python applications named Conpy. Conpy is easy to deploy since it is written in pure Python and it is not dependent on any third-party tools. Conpy is also easy to use. Anyone with basic knowledge of Python and concolic execution can quickly get start w
58#
發(fā)表于 2025-3-31 16:47:09 | 只看該作者
A Platform for Stock Market Simulation with Distributed Agent-Based Modeling,ters are limited by the computing capability as breakthroughs in financial research need much larger amount of agents. This paper introduces a platform for stock market simulation with ABM focusing on large scale parallel agents in a distributed computing environment such as Cluster and MPP. With th
59#
發(fā)表于 2025-3-31 17:30:19 | 只看該作者
60#
發(fā)表于 2025-3-31 23:15:28 | 只看該作者
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