Alex Skaletsky, Konstantin Levit-Gurevich, Michael Berezalsky, Yulia Kuznetcova, Hila Yakov
{"title":"Flexible Binary Instrumentation Framework to Profile Code Running on Intel GPUs","authors":"Alex Skaletsky, Konstantin Levit-Gurevich, Michael Berezalsky, Yulia Kuznetcova, Hila Yakov","doi":"10.1109/ispass55109.2022.00011","DOIUrl":null,"url":null,"abstract":"Functional and performance profiling of workloads is critical in developing software and hardware. Binary Instrumentation Technology has played a key role in this task for many years in the world of x86 architecture. However, such capabilities have not been available until recently for graphics devices, especially in the Intel Graphics Processing Unit world. The GTPin framework is the only tool that supports profiling graphics and GP-GPU kernels running on extremely parallel Intel GPU devices. GTPin supports a wide range of capabilities for software and hardware developers. With GTPin, you can profile real-world graphics and compute applications at a level of performance close to real hardware. Such an ability is critical in accelerating hardware and software readiness.","PeriodicalId":115391,"journal":{"name":"2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","volume":"239 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE International Symposium on Performance Analysis of Systems and Software (ISPASS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ispass55109.2022.00011","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
Functional and performance profiling of workloads is critical in developing software and hardware. Binary Instrumentation Technology has played a key role in this task for many years in the world of x86 architecture. However, such capabilities have not been available until recently for graphics devices, especially in the Intel Graphics Processing Unit world. The GTPin framework is the only tool that supports profiling graphics and GP-GPU kernels running on extremely parallel Intel GPU devices. GTPin supports a wide range of capabilities for software and hardware developers. With GTPin, you can profile real-world graphics and compute applications at a level of performance close to real hardware. Such an ability is critical in accelerating hardware and software readiness.