Type of Document Thesis Author Hines, Michael R. Author's Email Address firstname.lastname@example.org URN etd-04082005-204120 Title Anemone: An Adaptive Network Memory Engine Degree Master of Science Department Computer Science, Department of Advisory Committee
Advisor Name Title Kartik Gopalan Committee Chair An-I Andy Wang Committee Member Zhenhai Duan Committee Member Keywords
- Kernel Programming
- Distributed Networks
- Remote Memory
Date of Defense 2005-04-07 Availability unrestricted AbstractMemory hungry applications consistently keep their memory requirement curves ahead
of the growth of DRAM capacity in modern computer systems. Such applications quickly
start paging to swap space on the local disk, which brings down their performance, an
old and ongoing battle between the disk and RAM in the memory hierarchy. This thesis
presents a practical low-cost solution to this important performance problem. We give the
design, implementation and evaluation of Anemone - an Adaptive NEtwork MemOry engiNE.
Anemone pools together the memory resources of many machines in a clustered network of
computers. It then presents an interface to client machines in order to use the collective
memory pool in a virtualized manner, providing potentially unlimited amounts of memory
to memory-hungry high-performance applications.
Using real applications like the ns-2 simulator, the ray-tracing program POV-ray, and
quicksort, disk-based page-fault latencies average 6.5 milliseconds whereas Anemone provides
an average of latency of 700.2 microseconds, 9.2 times faster than using the disk. In contrast
to the disk-based paging, our results indicate that Anemone reduces the execution time
of single memory-bound processes by half. Additionally, Anemone reduces the execution
times of multiple, concurrent memory-bound processes by a factor of 10 on the average.
Another key advantage of Anemone is that this performance improvement is achieved with
no modifications to the client’s operating system nor the memory-bound applications due to
the use of a novel NFS-based low-latency remote paging mechanism.
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