{"title":"DtCraft:用于计算密集型应用程序的分布式执行引擎","authors":"Tsung-Wei Huang, Chun-Xun Lin, Martin D. F. Wong","doi":"10.1109/ICCAD.2017.8203853","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":126686,"journal":{"name":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2017-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"DtCraft: A distributed execution engine for compute-intensive applications\",\"authors\":\"Tsung-Wei Huang, Chun-Xun Lin, Martin D. F. Wong\",\"doi\":\"10.1109/ICCAD.2017.8203853\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":126686,\"journal\":{\"name\":\"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)\",\"volume\":\"123 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCAD.2017.8203853\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2017 IEEE/ACM International Conference on Computer-Aided Design (ICCAD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCAD.2017.8203853","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.