Memory resource management in VMware ESX server
OSDI '02 Proceedings of the 5th symposium on Operating systems design and implementationCopyright restrictions prevent ACM from being able to make the PDFs for this conference available for downloading
Difference engine: harnessing memory redundancy in virtual machines
OSDI'08 Proceedings of the 8th USENIX conference on Operating systems design and implementation
Satori: enlightened page sharing
USENIX'09 Proceedings of the 2009 conference on USENIX Annual technical conference
An exact algorithm for energy-efficient acceleration of task trees on CPU/GPU architectures
Proceedings of the 4th Annual International Conference on Systems and Storage
Exploiting hardware heterogeneity within the same instance type of Amazon EC2
HotCloud'12 Proceedings of the 4th USENIX conference on Hot Topics in Cloud Ccomputing
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Heterogeneous multiprocessors that combine multiple CPUs and GPUs on a single die are posed to become commonplace in the market. As seen recently from the high performance computing community, leveraging a GPU can yield performance increases of several orders of magnitude. We propose using GPU acceleration to greatly speed up cloud management tasks in VMMs. This is only becoming possible now that the GPU is moving on-chip, since the latency across the PCIe bus was too great to make fast, informed decisions about the state of a system at any given point. We explore various examples of cloud management tasks that can greatly benefit from GPU acceleration. We also tackle tough questions of how to manage this hardware in a multi-tenant system. Finally, we present a case study that explores a common cloud operation, memory deduplication, and show that GPU acceleration can improve the performance of its hashing component by a factor of over 80.