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Abstract
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.
Original language | English |
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Journal | Proceedings of the VLDB Endowment |
Volume | 6 |
Issue number | 12 |
Pages (from-to) | 1290-1293 |
ISSN | 2150-8097 |
Publication status | Published - 2013 |
Keywords
- Solid State Drives
- SSD simulation
- performance modeling
- algorithm parallelism
- experimental methodology
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Dive into the research topics of 'EagleTree: Exploring the Design Space of SSD-Based Algorithms'. Together they form a unique fingerprint.Projects
- 1 Finished
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CLyDE: Improving Database Systems Performance on Flash Devices through Cross-Layer Optimizations
Bonnet, P. (PI), Bjørling, M. (CoI) & Dayan, N. (CoI)
Independent Research Fund Denmark
01/10/2011 → 31/07/2015
Project: Research