Enabling GPU Virtualization in Cloud Environments
| Authors: | Iserte Agut, S., Clemente Castelló, F.J., Castelló Gimeno, A., Mayo Gual, R., Salvador Quintana Ortí, E. | |
| Conference: | 6th International Conference on Cloud Computing and Services Science--CLOSER 2016 | |
| Location and date: | Roma (Italia), April 2016 |  |
Abstract
The use of accelerators, such as graphics processing units (GPUs), to reduce the execution time of compute-intensive applications has become popular during the past few years. These devices increment the computational power of a node thanks to their parallel architecture. This trend has led cloud service providers as Amazon or middlewares such as OpenStack to add virtual machines (VMs) including GPUs to their facilities instances. To fulfill these needs, the guest hosts must be equipped with GPUs which, unfortunately, will be barely utilized if a non GPU-enabled VM is running in the host. The solution presented in this work is based on GPU virtualization and shareability in order to reach an equilibrium between service supply and the applications’ demand of accelerators. Concretely, we propose to decouple real GPUs from the nodes by using the virtualization technology rCUDA. With this software configuration, GPUs can be accessed from any VM avoiding the need of placing a physical GPUs in each guest host. Moreover, we study the viability of this approach using a public cloud service configuration, and we develop a module for OpenStack in order to add support for the virtualized devices and the logic to manage them. The results demonstrate this is a viable configuration which adds flexibility to current and well-known cloud solutions.