重新访问操作系统大容量存储假设可以提高性能和效率

R. Gezelter
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引用次数: 0

摘要

自1956年第一台IBM 350问世以来,随机存取大容量存储一直是计算的支柱。尽管在访问速度、传输性能、密度和可靠性方面取得了指数级的进步,但位置然后传输的接口范式仍然普遍存在。接口范例的一致性并不意味着实现保持不变,有许多改进:多个磁头、增量定位、记录技术和存储缓存。虽然多级存储缓存已经变得无处不在,但缓存并不是万灵药。通过减少物理介质访问,缓存有利于物理顺序使用和重复使用。但是,具有数百或数千个活跃访问文件的系统可能会使用仅使用一次的数据阻塞缓存,从而产生缓存污染。特别是自1990年以来,半导体的进步大大提高了处理能力和存储容量。固态大容量存储消除了旋转延迟,但仍然存在其他与实现相关的延迟。分层大容量存储提供了透明的假象,但与虚拟内存一样,由于级别之间的数据迁移而导致的延迟无法隐藏。在整个20世纪80年代,资源限制迫使I/O基础设施实现者选择最小资源实现;其他选择都是不可行的。可行性是强制性的;效率和性能是可取的。更好的资源环境允许在一定程度上增加处理和内存消耗的情况下提高效率和性能。我们将研究一种保留现有I/O API的方法,并使用最小的文化兼容扩展来实现更高的性能和效率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Revisiting Operating System Mass Storage Presumptions Enables Higher Performance and Efficiency
Random access mass storage has been a pillar of computing since the 1956 delivery of the first IBM 350. The interface paradigm of position then transfer is pervasive, despite exponential advances in access speeds, transfer performance, density, and reliability.Consistency in interface paradigm does not mean that implementations have remained static, there have been numerous improvements: multiple heads, incremental positioning, recording technologies, and storage caches. While multiple levels of storage caches have become ubiquitous, caches are not a panacea. Caches benefit physically sequential usage and repetitive use by reducing physical media accesses. However, systems with hundreds or thousands of actively accessed files can clog caches with data that is only used a single time, yielding cache pollution.Advances in semiconductors have vastly increased processing power and memory capacity, particularly since 1990. Solid state mass storage eliminates rotational delay, but can still have other implementation-related delays. Hierarchical mass storage provides the illusion of transparency, but as with virtual memory, delays attributable to data migration between levels cannot be concealed.Through the 1980s, resource limitations obliged I/O infrastructure implementors to choose minimum resource implementations; other choices were infeasible. Feasibility is mandatory; efficiency and performance are desirable. Better resourced environments allow higher efficiency and performance with some increase in processing and memory consumption.We will examine an approach that preserves the pre-existing I/O API, with minimal culturally-compatible extensions that enable higher performance and increased efficiency.
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