Formal Definitions and Performance Comparison of Consistency Models for Parallel File Systems
CoRR(2024)
摘要
The semantics of HPC storage systems are defined by the consistency models to
which they abide. Storage consistency models have been less studied than their
counterparts in memory systems, with the exception of the POSIX standard and
its strict consistency model. The use of POSIX consistency imposes a
performance penalty that becomes more significant as the scale of parallel file
systems increases and the access time to storage devices, such as node-local
solid storage devices, decreases. While some efforts have been made to adopt
relaxed storage consistency models, these models are often defined informally
and ambiguously as by-products of a particular implementation. In this work, we
establish a connection between memory consistency models and storage
consistency models and revisit the key design choices of storage consistency
models from a high-level perspective. Further, we propose a formal and unified
framework for defining storage consistency models and a layered implementation
that can be used to easily evaluate their relative performance for different
I/O workloads. Finally, we conduct a comprehensive performance comparison of
two relaxed consistency models on a range of commonly-seen parallel I/O
workloads, such as checkpoint/restart of scientific applications and random
reads of deep learning applications. We demonstrate that for certain I/O
scenarios, a weaker consistency model can significantly improve the I/O
performance. For instance, in small random reads that typically found in deep
learning applications, session consistency achieved an 5x improvement in I/O
bandwidth compared to commit consistency, even at small scales.
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关键词
Consistency model,parallel i/o,parallel file system,storage consistency
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