DtCraft:用于计算密集型应用程序的分布式执行引擎

Tsung-Wei Huang, Chun-Xun Lin, Martin D. F. Wong
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引用次数: 8

摘要

近年来,数据驱动的分布式系统(如Hadoop MapReduce、Spark和Dryad)发展迅速。然而,包括大规模优化、建模和模拟在内的高性能或计算密集型应用程序的对应物仍处于萌芽阶段。在本文中,我们介绍了DtCraft,一个现代的基于c++的分布式执行引擎,它有效地支持一个新的强大的编程模型,用于构建高性能并行应用程序。用户不需要了解分布式计算,可以将重点放在高级开发上,而将诸如并发控制、工作负载分布和容错等困难的细节留给系统透明地处理。我们已经在微基准测试和大规模优化问题上对DtCraft进行了评估,并在计算机集群上显示了良好的性能。在一个特定的半导体设计问题中,与手工实现相比,我们使用40个节点实现了30倍的加速,减少了15倍的开发工作量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
DtCraft: A distributed execution engine for compute-intensive applications
Recent years have seen rapid growth in data-driven distributed systems such as Hadoop MapReduce, Spark, and Dryad. However, the counterparts for high-performance or compute-intensive applications including large-scale optimizations, modeling, and simulations are still nascent. In this paper, we introduce DtCraft, a modern C+,+,17-based distributed execution engine that efficiently supports a new powerful programming model for building high-performance parallel applications. Users need no understanding of distributed computing and can focus on high-level developments, leaving difficult details such as concurrency controls, workload distribution, and fault tolerance handled by our system transparently. We have evaluated DtCraft on both micro-benchmarks and large-scale optimization problems, and shown promising performance on computer clusters. In a particular semicondictor design problem, we achieved 30 x speedup with 40 nodes and 15 x less development efforts over hand-crafted implementation.
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