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On the power consumption modeling for the simulation of Heterogeneous HPC clouds
| Content Provider | ACM Digital Library |
|---|---|
| Author | Gravvanis, George A. Giannoutakis, Konstantinos M. Makaratzis, Antonios T. Tzovaras, Dimitrios Filelis-Papadopoulos, Christos K. |
| Abstract | During the last years, except from the traditional CPU based hardware servers, hardware accelerators are widely used in various HPC application areas. More specifically, Graphics Processing Units (GPUs), Many Integrated Cores (MICs) and Field-Programmable Gate Arrays (FPGAs) have shown a great potential in HPC and have been widely mobilized in supercomputing. With the adoption of HPC from cloud environments, the realization of HPC-Clouds is evolving since many vendors provide HPC capabilities on their clouds. With the increase of the interest on clouds, there has been an analogous increase in cloud simulation frameworks. Cloud simulation frameworks offer a controllable environment for experimentation with various workloads and scenarios, while they provide several metrics such as server utilization and power consumption. For providing these metrics, cloud simulators propose mathematical models that estimate the behavior of the underlying hardware infrastructure. This paper focuses on the power consumption modeling of the main compute elements of heterogeneous HPC servers, i.e. CPU servers and pairs of CPU-accelerators. The modeling approaches of existing cloud simulators are examined and extended, while new models are proposed for estimating the power consumption of accelerators. |
| Starting Page | 1 |
| Ending Page | 6 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781450349369 |
| DOI | 10.1145/3068126.3068127 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2017-04-23 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Accelerators Simulation Field-programmable gate array Many integrated cores Modeling Graphics processing unit |
| Content Type | Text |
| Resource Type | Article |
