{"title":"Modeling Gather and Scatter with Hardware Performance Counters for Xeon Phi","authors":"James Lin, Akira Nukada, S. Matsuoka","doi":"10.1109/CCGrid.2015.59","DOIUrl":null,"url":null,"abstract":"Intel Initial Many-Core Instructions (IMCI) for Xeon Phi introduces hardware-implemented Gather and Scatter (G/S) load/store contents of SIMD registers from/to non-contiguous memory locations. However, they can be one of key performance bottlenecks for Xeon Phi. Modelling G/S can provide insights to the performance on Xeon Phi, however, the existing solution needs a hand-written assembly implementation. Therefore, we modeled G/S with hardware performance counters which can be profiled by the tools like PAPI. We profiled Address Generation Interlock (AGI) events as the number of G/S, estimated the average latency of G/S with VPU_DATA_READ, and combined them to model the total latencies of G/S. We applied our model to the 3D 7-point stencil and the result showed G/S spent nearly 40% of total kernel time. We also validated the model by implementing a G/S- free version with intrinsics. The contribution of the work is a performance model for G/S built with hardware counters. We believe the model can be generally applicable to CPU as well.","PeriodicalId":6664,"journal":{"name":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","volume":"40 1","pages":"713-716"},"PeriodicalIF":0.0000,"publicationDate":"2015-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 15th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CCGrid.2015.59","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
Intel Initial Many-Core Instructions (IMCI) for Xeon Phi introduces hardware-implemented Gather and Scatter (G/S) load/store contents of SIMD registers from/to non-contiguous memory locations. However, they can be one of key performance bottlenecks for Xeon Phi. Modelling G/S can provide insights to the performance on Xeon Phi, however, the existing solution needs a hand-written assembly implementation. Therefore, we modeled G/S with hardware performance counters which can be profiled by the tools like PAPI. We profiled Address Generation Interlock (AGI) events as the number of G/S, estimated the average latency of G/S with VPU_DATA_READ, and combined them to model the total latencies of G/S. We applied our model to the 3D 7-point stencil and the result showed G/S spent nearly 40% of total kernel time. We also validated the model by implementing a G/S- free version with intrinsics. The contribution of the work is a performance model for G/S built with hardware counters. We believe the model can be generally applicable to CPU as well.