Abstract

Loop optimization, made of a sequence of loop transformations, plays an important role in performance improvement in data centric applications. Programs using flash memory are no exception to this, but, under certain conditions careless applications of specific loop transformations might cause unexpected results, due to the characteristics of flash memory and underlying management systems. In this article, we analyze how loop transformations affect the performance in flash translation layers (FTLs). First, we choose four loop structures which have distinct reference patterns and propose a cost model for each structure, reflecting the properties of flash memory. Then, using these cost models, we investigate how loop transformations affect the block associative sector translation (BAST)'s and fully associative sector translation (FAST)'s internal operations and analyze the performance effect of loop transformations experimentally. As a result, we find that some of the major loop transformations cause unexpected performance effects in those major FTLs under certain conditions.

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