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LRW Does Not Exploit Spatial Locality

Figure 6: A comparison of LRW, CSCAN, and WOW using random write workload using the Full Backend for both RAID-10 and RAID-5. It can be seen that the throughput of LRW does not depend upon the NVS size, whereas throughput of WOW and CSCAN exhibit a logarithmic gain as a function of the size of NVS.
\begin{figure*}\begin{center}
{\small Random Write Workload (nearly 100\% miss),...
...,height=2.25in}
\epsfig{figure=data/r5profq20.eps,height=2.25in} } \end{figure*}

In Figure 6, we compare LRW, CSCAN, and WOW using random write workload (Section V-C) directed to Full Backend on RAID-5 and RAID-10. Since the workload has almost no temporal locality, the throughput of LRW remains constant as the NVS size increases. In contrast, WOW and CSCAN exhibit logarithmic gain in throughput as a function of the size of NVS by exploiting spatial locality (also see the related discussion in Section II-B). For RAID-10, at the lowest NVS size of 32 pages, WOW and CSCAN outperform LRW by 16%, while, quite dramatically, at the NVS size of 65,536 pages, WOW and CSCAN outperform LRW by 200%. Similarly, for RAID-5, at the lowest NVS size of 64 pages, WOW and CSCAN outperform LRW by 38%, while, quite dramatically, at the NVS size of 16,384 pages, WOW and CSCAN outperform LRW by 147%.

While, for brevity, we have shown results for a queue depth of 20. When we used a larger queue depth, performance of all three algorithms increased uniformly, producing virtually identical curves. Increasing queue depth beyond 128 in either RAID-10 or RAID-5 does not seem to help throughput significantly.


next up previous
Next: WOW is Good for Up: Results Previous: Results
Binny Gill 2005-10-17