تقرير
Modeling Data Movement Performance on Heterogeneous Architectures
| العنوان: | Modeling Data Movement Performance on Heterogeneous Architectures |
|---|---|
| المؤلفون: | Bienz, Amanda, Olson, Luke N., Gropp, William D., Lockhart, Shelby |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science |
| مصطلحات موضوعية: | Computer Science - Distributed, Parallel, and Cluster Computing |
| الوصف: | The cost of data movement on parallel systems varies greatly with machine architecture, job partition, and nearby jobs. Performance models that accurately capture the cost of data movement provide a tool for analysis, allowing for communication bottlenecks to be pinpointed. Modern heterogeneous architectures yield increased variance in data movement as there are a number of viable paths for inter-GPU communication. In this paper, we present performance models for the various paths of inter-node communication on modern heterogeneous architectures, including the trade-off between GPUDirect communication and copying to CPUs. Furthermore, we present a novel optimization for inter-node communication based on these models, utilizing all available CPU cores per node. Finally, we show associated performance improvements for MPI collective operations. Comment: 7 pages, 6 Figures, Preprint |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2010.10378 |
| رقم الأكسشن: | edsarx.2010.10378 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |