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Summary: Parallel I/O is a critical technique for moving data between compute and storage subsystems of supercomputers. With massive amounts of data produced or consumed by compute nodes, high‐performant parallel I/O is essential. I/O benchmarks play an important role in this process; however, there is a scarcity of I/O benchmarks representative of current workloads on HPC systems. Toward creating representative I/O kernels from real‐world applications, we have created h5bench , a set of I/O kernels that exercise hierarchical data format version 5 (HDF5) I/O on parallel file systems in numerous dimensions. Our focus on HDF5 is due to the parallel I/O library's heavy usage in various scientific applications running on supercomputing systems. The various tests benchmarked in the h5bench suite include I/O operations (read and write), data locality (arrays of basic data types and arrays of structures), array dimensionality (one‐dimensional arrays, two‐dimensional meshes, three‐dimensional cubes), I/O modes (synchronous and asynchronous). In this paper, we present the observed performance of h5bench executed along several of these dimensions on existing supercomputers (Cori and Summit) and pre‐exascale platforms (Perlmutter, Theta, and Polaris). h5bench measurements can be used to identify performance bottlenecks and their root causes and evaluate I/O optimizations. As the I/O patterns of h5bench are diverse and capture the I/O behaviors of various HPC applications, this study will be helpful to the broader supercomputing and I/O community. [ABSTRACT FROM AUTHOR]

User‐level file systems are usually adopted to bridge the gap between efficacy and efficiency of file system developments for new applications' I/O demands. And the widely known user‐space file system framework, FUSE, is commonly utilized to deployed user‐level file systems. This article first uses a popular stack‐able file system as a case study to exam how FUSE affects I/O performance. Based on the testing and analytical results, this article then presents SHC, an implementation method to implement a user‐level file system without FUSE intervention. Experimental results indicate that SHC improves write bandwidth by up to 5.6x compared with that of FUSE and present leading superiority on read cases. [ABSTRACT FROM AUTHOR]

Summary: An effective way to mitigate the lifetime and performance problems of NAND flash SSDs induced by garbage collection is separating the cold data and hot data. However, all existing solutions do this separation from the viewpoint of the hot data and thus suffer from expensive cost on monitoring the update behaviors of workloads. Different from the conventional wisdom, we propose to do the separation from the viewpoint of the cold data, which is rooted on the following two dedicated observations. First, the data migrated by garbage collection demonstrate a cold property compared with the other data. Second, it is inexpensive to separate the former data from the latter data. In the proposed method, named Isolation, we inexpensively separate the cold data via garbage collection. More specifically, through writing the data migrated by garbage collection (cold data) to dedicated blocks and writing the other data (hot data) to other blocks, the separation is done naturally. To evaluate Isolation, we conduct extensive trace‐driven simulations under seven typical workloads. The simulation results demonstrate the effectiveness and efficiency of Isolation. In most cases, Isolation can reduce the number of erasures and average I/O response time up to 47.3% and 80.1%, respectively. Existing approaches integrated with Isolation can further reduce the number of erasures and average I/O response time up to 7.8%‐18.5% and 10.7%‐41.4%, respectively. [ABSTRACT FROM AUTHOR]

SUMMARY We propose a new method for tiered storage and evaluate its characteristics. In this method, the fast tier is divided into two areas and the data in each area are managed on the basis of two I/O (input/output) measurement periods. When I/Os to these areas increase, the proposed method allocates the frequently accessed areas to a fast tier in advance, thereby improving storage I/O performance. We evaluate the proposed method by simulating storage I/Os and data migration between tiers. When I/O locality is high or frequently accessed areas rarely move, the proposed method is more effective and improves storage I/O performance by up to 44%. [ABSTRACT FROM AUTHOR]

Summary: This paper presents an energy efficiency and I/O performance analysis of low‐power architectures when compared to conventional architectures, with the goal of studying the viability of using them as storage servers. Our results show that despite the fact the power demand of the storage device amounts for a small fraction of the power demand of the whole system, significant increases in power demand are observed when accessing the storage device. We investigate the access pattern impact on power demand, looking at the whole system and at the storage device by itself, and compare all tested configurations regarding energy efficiency. Then we extrapolate the conclusions from this research to provide guidelines for when considering the replacement of traditional storage servers by low‐power alternatives. We show the choice depends on the expected workload, estimates of power demand of the systems, and factors limiting performance. These guidelines can be applied for other architectures than the ones used in this work. [ABSTRACT FROM AUTHOR]