{"title":"集成gpu的计算框架方面","authors":"Grigore Lupescu, N. Tapus","doi":"10.1109/roedunet51892.2020.9324851","DOIUrl":null,"url":null,"abstract":"The integrated GPU is nowadays found in many consumer and industrial System on Chips, and poses unique challenges to program (thermal, power, shared resources etc.). The goal of this work is to identify several key aspects in a compute framework (basic design, execution models, data communication, fault tolerance and latency), which handle the integrated GPU limitations and provide a proper abstraction.","PeriodicalId":140521,"journal":{"name":"2020 19th RoEduNet Conference: Networking in Education and Research (RoEduNet)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-12-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Compute framework aspects for integrated GPUs\",\"authors\":\"Grigore Lupescu, N. Tapus\",\"doi\":\"10.1109/roedunet51892.2020.9324851\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The integrated GPU is nowadays found in many consumer and industrial System on Chips, and poses unique challenges to program (thermal, power, shared resources etc.). The goal of this work is to identify several key aspects in a compute framework (basic design, execution models, data communication, fault tolerance and latency), which handle the integrated GPU limitations and provide a proper abstraction.\",\"PeriodicalId\":140521,\"journal\":{\"name\":\"2020 19th RoEduNet Conference: Networking in Education and Research (RoEduNet)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-12-11\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2020 19th RoEduNet Conference: Networking in Education and Research (RoEduNet)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/roedunet51892.2020.9324851\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2020 19th RoEduNet Conference: Networking in Education and Research (RoEduNet)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/roedunet51892.2020.9324851","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The integrated GPU is nowadays found in many consumer and industrial System on Chips, and poses unique challenges to program (thermal, power, shared resources etc.). The goal of this work is to identify several key aspects in a compute framework (basic design, execution models, data communication, fault tolerance and latency), which handle the integrated GPU limitations and provide a proper abstraction.