Nswap2L: Transparently Managing Heterogeneous Cluster Storage Resources For Fast Swapping

Document Type

Conference Proceeding

Publication Date

2016

Published In

Proceedings Of The Second International Symposium On Memory Systems

Abstract

To support data intensive cluster computing, it is increasingly important that node virtual memory (VM) systems make effective use of available fast storage devices for swap or temporary file space. Nswap2L is a novel system that transparently manages a heterogeneous set of storage options commonly found in clusters, including node RAM, disk, flash SSD, PCM, or network storage devices. Nswap2L implements a two-level device driver interface. At the top level, it appears to node operating systems (OSs) as a single, fast, random access device that can be added as a swap partition on cluster nodes. It transparently manages the underlying heterogeneous storage devices, including its own implementation of Network RAM, to which swapped out data are stored. It implements data placement, migration, and prefetching policies that choose which underlying physical devices store swapped-out page data. Its policies incorporate information about device capacity, system load, and the strengths of different physical storage media. By moving device-specific knowledge into Nswap2L, VM policies in the OS can be based solely on typical application access patterns and not on characteristics of underlying physical storage media. Nswap2L's policy decisions are abstracted from the OS, freeing the OS from having to implement specialized policies for different combinations of cluster storage---Nswap2L requires no changes to the OS's VM system. Results of our benchmark tests show that data-intensive applications perform up to 6 times faster on Nswap2L-enabled clusters, and show that our two-level device driver design adds minimal I/O latency to the underlying devices that Nswap2L manages. In addition, we found that even though Nswap2L's Network RAM is faster than any other backing store, its prefetching policy that distributes data over multiple devices results in increased I/O parallelism and can lead to better performance than swapping only to a single underlying device.

Keywords

cluster systems, backing storage, network RAM, flash

Published By

ACM

Conference

MEMSYS2016

Conference Dates

October 3-6, 2016

Conference Location

Alexandria, VA

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