EagleTree：探索基于SSD的算法的设计空间
EagleTree: Exploring the Design Space of SSD-Based Algorithms
摘要：
固态硬盘（SSD）是系统设计人员的移动目标：它们是黑盒子，其内部没有文档，并且其性能特征因型号而异。没有合适的分析模型，并且使用商用SSD进行实验很麻烦，因为它需要仔细的实验方法来确保可重复性。更糟糕的是，在给定的SSD上获得的性能结果无法推广。总的来说，不可能探索给定算法（例如哈希连接或LSM树插入）如何利用现代SSD的内在并行性，或者SSD内部的微小变化如何影响其整体性能。在本文中，我们提出了一个新的SSD模拟框架，命名为树，它解决了这些问题，并使基于SSD的算法的原则性研究。演示场景说明了基于SSD的IO堆栈的算法的设计空间，并展示了研究人员和从业人员如何使用MapleTree来对这个复杂的设计空间进行易于处理的探索。
英文摘要：
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.
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