GPU as a Service: providing GPU-acceleration to federated cloud systems

Current data centers leverage virtual machines (VMs) in order to efficiently use hardware resources. VMs allow reducing equipment acquisition costs as well as decreasing overall energy consumption. However, although VMs have noticeably evolved to make a smart use of the underlying hardware, the use of GPUs (Graphics Processing Units) for General Purpose computing (GPGPU) is still not efficiently supported. This concern might be addressed by remote GPU virtualization solutions, which may provide VMs with GPUs located in a remote node, detached from the host where the VMs are being executed. This chapter presents an in-depth analysis about how to provide GPU access to applications running inside VMs. This analysis is complemented with experimental results which show that the use of remote GPU virtualization is an effective mechanism to provide GPU access to applications with negligible overheads. Finally, the approach is presented in the context of cloud federations for providing GPGPU as a Service.