ABS
发表于 2025-3-21 16:44:17
书目名称Distributed Graph Analytics影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0281899<br><br> <br><br>书目名称Distributed Graph Analytics读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0281899<br><br> <br><br>
轻推
发表于 2025-3-21 22:44:14
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Radiation
发表于 2025-3-22 02:41:39
hms used in distributed graph analytics in a high level nota.This book brings together two important trends: graph algorithms and high-performance computing. Efficient and scalable execution of graph processing applications in data or network analysis requires innovations at multiple levels: algorit
faction
发表于 2025-3-22 08:23:54
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使习惯于
发表于 2025-3-22 09:09:41
https://doi.org/10.1057/9780230270688This chapter provides some insights into the issues in programming parallel algorithms. Parallelism, atomicity, push and pull types of computation, algorithms driven by topology or data, vertex based, edge based and worklist based computation, are some of the important considerations in designing parallel implementations.
色情
发表于 2025-3-22 16:03:11
https://doi.org/10.1057/9780230270688This chapter provides an overview of GPU architectures and CUDA programming. The performance of the same graph algorithms on multi-core CPU and GPU are usually very different. Intricacies of thread scheduling, barrier synchronization, warp based execution, memory hierarchy, and their effects on graph analytics are illustrated with simple examples.
色情
发表于 2025-3-22 20:34:38
https://doi.org/10.1057/9780230270688The domain-specific language . is presented in this chapter. The data types and statements of . that support easy programming of graph analytics applications are described. To drive home the point that . programs can be very efficient, code generation mechanisms used in the . compiler are delineated with examples.
沙发
发表于 2025-3-23 00:48:15
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CHAR
发表于 2025-3-23 04:08:48
Efficient Parallel Implementation of Graph Algorithms,This chapter provides some insights into the issues in programming parallel algorithms. Parallelism, atomicity, push and pull types of computation, algorithms driven by topology or data, vertex based, edge based and worklist based computation, are some of the important considerations in designing parallel implementations.
托运
发表于 2025-3-23 06:00:15
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