GPU-Accelerated Algorithms for Allocating Virtual Infrastructure in Cloud Data Centers

Abstract

Allocating IT resources to Virtual Infrastructures (VIs) (i.e. groups of VMs, virtual switches, and their network interconnections) is an NP-hard problem. Most allocation algorithms designed to run on CPUs face scalability issues when considering current cloud data centers comprising thousands of servers. This work offers and evaluates a set of allocation algorithms refactored for Graphic Processing Units (GPUs). Experimental results demonstrate their ability to handle three large-scale data center topologies.