{"title":"GpuTejas: A parallel simulator for GPU architectures","authors":"Geetika Malhotra, Seep Goel, S. Sarangi","doi":"10.1109/HiPC.2014.7116897","DOIUrl":null,"url":null,"abstract":"In this paper, we introduce a new Java-based parallel GPGPU simulator, GpuTejas. GpuTejas is a fast trace driven simulator, which uses relaxed synchronization, and non-blocking data structures to derive its speedups. Secondly, it introduces a novel scheduling and partitioning scheme for parallelizing a GPU simulator. We evaluate the performance of our simulator with a set of Rodinia benchmarks. We demonstrate a mean speedup of 17.33x with 64 threads over sequential execution, and a speedup of 429X over the widely used simulator GPGPU-Sim. We validated our timing and simulation model by comparing our results with a native system (NVIDIA Tesla M2070). As compared to the sequential version of GpuTejas, the parallel version has an error limited to <;7.67% for our suite of benchmarks, which is similar to the numbers reported by competing parallel simulators.","PeriodicalId":337777,"journal":{"name":"2014 21st International Conference on High Performance Computing (HiPC)","volume":"74 8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"22","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 21st International Conference on High Performance Computing (HiPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/HiPC.2014.7116897","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 22
Abstract
In this paper, we introduce a new Java-based parallel GPGPU simulator, GpuTejas. GpuTejas is a fast trace driven simulator, which uses relaxed synchronization, and non-blocking data structures to derive its speedups. Secondly, it introduces a novel scheduling and partitioning scheme for parallelizing a GPU simulator. We evaluate the performance of our simulator with a set of Rodinia benchmarks. We demonstrate a mean speedup of 17.33x with 64 threads over sequential execution, and a speedup of 429X over the widely used simulator GPGPU-Sim. We validated our timing and simulation model by comparing our results with a native system (NVIDIA Tesla M2070). As compared to the sequential version of GpuTejas, the parallel version has an error limited to <;7.67% for our suite of benchmarks, which is similar to the numbers reported by competing parallel simulators.
本文介绍了一种新的基于java的并行GPGPU模拟器GpuTejas。GpuTejas是一种快速跟踪驱动模拟器，它使用宽松的同步和非阻塞数据结构来获得其速度。其次，介绍了一种新的GPU模拟器并行化调度和分区方案。我们用一组Rodinia基准来评估模拟器的性能。我们演示了64线程顺序执行的平均加速速度为17.33x，在广泛使用的模拟器GPGPU-Sim上的加速速度为429X。我们通过将我们的结果与本地系统(NVIDIA Tesla M2070)进行比较来验证我们的时序和仿真模型。与连续版本的GpuTejas相比，在我们的基准测试套件中，并行版本的误差限制在< 7.67%，这与竞争的并行模拟器报告的数字相似。
京公网安备 11010802042870号
京ICP备2023020795号-1
分享
求助内容：
应助结果提醒方式：
扫码关注我们
