{"title":"图编程模型:传感器信号处理的一种有效方法","authors":"Steve Kirsch","doi":"10.1109/HPEC.2012.6408662","DOIUrl":null,"url":null,"abstract":"The HPC community has struggled to find a parallel programming model or language that can efficiently expose algorithmic parallelism in a sequential program and automate the implementation of a highly efficient parallel program. A plethora of parallel programming languages have been developed along with sophisticated compilers and runtimes, but none of these approaches have been successful enough to became a defacto standard. Graph Programming Model has the capability and efficiencies to become that ubiquitous standard for the signal processing domain.","PeriodicalId":193020,"journal":{"name":"2012 IEEE Conference on High Performance Extreme Computing","volume":"116 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Graph programming model: An efficient approach for sensor signal processing\",\"authors\":\"Steve Kirsch\",\"doi\":\"10.1109/HPEC.2012.6408662\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The HPC community has struggled to find a parallel programming model or language that can efficiently expose algorithmic parallelism in a sequential program and automate the implementation of a highly efficient parallel program. A plethora of parallel programming languages have been developed along with sophisticated compilers and runtimes, but none of these approaches have been successful enough to became a defacto standard. Graph Programming Model has the capability and efficiencies to become that ubiquitous standard for the signal processing domain.\",\"PeriodicalId\":193020,\"journal\":{\"name\":\"2012 IEEE Conference on High Performance Extreme Computing\",\"volume\":\"116 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-09-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 IEEE Conference on High Performance Extreme Computing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/HPEC.2012.6408662\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 IEEE Conference on High Performance Extreme Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HPEC.2012.6408662","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Graph programming model: An efficient approach for sensor signal processing
The HPC community has struggled to find a parallel programming model or language that can efficiently expose algorithmic parallelism in a sequential program and automate the implementation of a highly efficient parallel program. A plethora of parallel programming languages have been developed along with sophisticated compilers and runtimes, but none of these approaches have been successful enough to became a defacto standard. Graph Programming Model has the capability and efficiencies to become that ubiquitous standard for the signal processing domain.