L. Gao, David Zaretsky, Gaurav Mittal, D. Schonfeld, P. Banerjee
{"title":"流架构中流描述符的自动生成","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":"{\"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}","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}
Automatic Generation of Stream Descriptors for Streaming Architectures
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.