Design tradeoffs for SSD performance
ATC'08 USENIX 2008 Annual Technical Conference on Annual Technical Conference
Proceedings of the 14th international conference on Architectural support for programming languages and operating systems
FlashSim: A Simulator for NAND Flash-Based Solid-State Drives
SIMUL '09 Proceedings of the 2009 First International Conference on Advances in System Simulation
Hot data identification for flash-based storage systems using multiple bloom filters
MSST '11 Proceedings of the 2011 IEEE 27th Symposium on Mass Storage Systems and Technologies
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Solid State Drives (SSDs) are a moving target for system designers: they are black boxes, their internals are undocumented, and their performance characteristics vary across models. There is no appropriate analytical model and experimenting with commercial SSDs is cumbersome, as it requires a careful experimental methodology to ensure repeatability. Worse, performance results obtained on a given SSD cannot be generalized. Overall, it is impossible to explore how a given algorithm, say a hash join or LSM-tree insertions, leverages the intrinsic parallelism of a modern SSD, or how a slight change in the internals of an SSD would impact its overall performance. In this paper, we propose a new SSD simulation framework, named EagleTree, which addresses these problems, and enables a principled study of SSD-Based algorithms. The demonstration scenario illustrates the design space for algorithms based on an SSD-based IO stack, and shows how researchers and practitioners can use EagleTree to perform tractable explorations of this complex design space.