Najmeh Nazari Bavarsad, Hosein Mohammadi Makrani, H. Sayadi, Lawrence Landis, S. Rafatirad, H. Homayoun
{"title":"HosNa: A DPC++ Benchmark Suite for Heterogeneous Architectures","authors":"Najmeh Nazari Bavarsad, Hosein Mohammadi Makrani, H. Sayadi, Lawrence Landis, S. Rafatirad, H. Homayoun","doi":"10.1109/ICCD53106.2021.00084","DOIUrl":null,"url":null,"abstract":"Most data centers equipped their general-purpose processors with hardware accelerators to reduce power consumption and improve utilization. Hardware accelerators offer highly energy-efficient computation for a wide range of applications; however, their programming is not as efficient as processors. To bridge the gap, Intel developed a cloud-based infrastructure called DevCloud that connects Intel® Xeon® Scalable Processors to GPUs and FPGAs to deliver high compute performance for emerging workloads. DevCloud assists developers with their compute-intensive tasks and provides access to precompiled software optimized for Intel® architecture. To reduce programming complexity and minimize the barriers to adopt new innovative hardware technology, Intel also provided a unified, cross-architecture programming model called oneAPI based on the Data-Parallel C++ (DPC++) language. In this paper, we introduce HosNa, the first DPC++ benchmark suite that can be used for the evaluation of the Intel FPGAs and DPC++ productivity. Moreover, we present the characterization of proposed benchmarks and the evaluation of implemented hardware accelerators in terms of speedup and latency.","PeriodicalId":154014,"journal":{"name":"2021 IEEE 39th International Conference on Computer Design (ICCD)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 IEEE 39th International Conference on Computer Design (ICCD)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCD53106.2021.00084","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 2
Abstract
Most data centers equipped their general-purpose processors with hardware accelerators to reduce power consumption and improve utilization. Hardware accelerators offer highly energy-efficient computation for a wide range of applications; however, their programming is not as efficient as processors. To bridge the gap, Intel developed a cloud-based infrastructure called DevCloud that connects Intel® Xeon® Scalable Processors to GPUs and FPGAs to deliver high compute performance for emerging workloads. DevCloud assists developers with their compute-intensive tasks and provides access to precompiled software optimized for Intel® architecture. To reduce programming complexity and minimize the barriers to adopt new innovative hardware technology, Intel also provided a unified, cross-architecture programming model called oneAPI based on the Data-Parallel C++ (DPC++) language. In this paper, we introduce HosNa, the first DPC++ benchmark suite that can be used for the evaluation of the Intel FPGAs and DPC++ productivity. Moreover, we present the characterization of proposed benchmarks and the evaluation of implemented hardware accelerators in terms of speedup and latency.