Title :
MemX: Virtualization of Cluster-Wide Memory
Author :
Deshpande, Umesh ; Wang, Beilan ; Haque, Shafee ; Hines, Michael ; Gopalan, Kartik
Author_Institution :
Comput. Sci., State Univ. of New York, Binghamton, NY, USA
Abstract :
We present MemX -- a distributed system that virtualizes cluster-wide memory to support data-intensive and large memory workloads in virtual machines (VMs). MemX provides a number of benefits in virtualized settings: (1) VM workloads that access large datasets can perform low-latency I/O over virtualized cluster-wide memory; (2) VMs can transparently execute very large memory applications that require more memory than physical DRAM present in the host machine; (3) MemX reduces the effective memory usage of the cluster by de-duplicating pages that have identical content; (4) existing applications do not require any modifications to benefit from MemX such as the use of special APIs, libraries, recompilation, or relinking; and (5) MemX supports live migration of large-footprint VMs by eliminating the need to migrate part of their memory footprint resident on other nodes. Detailed evaluations of our MemX prototype show that large dataset applications and multiple concurrent VMs achieve significant performance improvements using MemX compared against virtualized local and iSCSI disks.
Keywords :
distributed processing; storage management; virtual machines; DRAM; MemX prototype; MemX virtual machine; VM workloads; cluster wide memory virtualization; distributed system; host machine; large memory workloads; Bridges; Driver circuits; Memory management; Protocols; Random access memory; Servers; Virtual machine monitors; Cluster; Gigabit Ethernet; Hypervisor; Memory; Virtualization;
Conference_Titel :
Parallel Processing (ICPP), 2010 39th International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
978-1-4244-7913-9
Electronic_ISBN :
0190-3918
DOI :
10.1109/ICPP.2010.74