L. Gao, David Zaretsky, Gaurav Mittal, D. Schonfeld, P. Banerjee
{"title":"Automatic Generation of Stream Descriptors for Streaming Architectures","authors":"L. Gao, David Zaretsky, Gaurav Mittal, D. Schonfeld, P. Banerjee","doi":"10.1109/ICPP.2010.38","DOIUrl":null,"url":null,"abstract":"We describe a novel approach for automatically generating streaming architectures from software programs. While existing systems require user-defined stream models, our method automatically identifies producer-consumer streaming relationships and translates them into streaming architectures. Data streams between producer-consumer kernels are represented using a combination of stream descriptors and CFGs, which are categorized into four stream types. A bridge module is generated based on the stream type in the streaming architecture to facilitate data streaming between each producer-consumer pair. Several optimizations are also developed to improve throughput and parallelism. We demonstrate our results on a FPGA based platform. The automatically generated streaming architectures show 1.5-3x speedups over the non-streaming designs by employing spatial and temporal data independence to increase parallelism.","PeriodicalId":180554,"journal":{"name":"2010 39th International Conference on Parallel Processing","volume":"56 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 39th International Conference on Parallel Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICPP.2010.38","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
Abstract
We describe a novel approach for automatically generating streaming architectures from software programs. While existing systems require user-defined stream models, our method automatically identifies producer-consumer streaming relationships and translates them into streaming architectures. Data streams between producer-consumer kernels are represented using a combination of stream descriptors and CFGs, which are categorized into four stream types. A bridge module is generated based on the stream type in the streaming architecture to facilitate data streaming between each producer-consumer pair. Several optimizations are also developed to improve throughput and parallelism. We demonstrate our results on a FPGA based platform. The automatically generated streaming architectures show 1.5-3x speedups over the non-streaming designs by employing spatial and temporal data independence to increase parallelism.