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Two camps of file systems exist: parallel file systems designed for conventional high performance computing (HPC) and distributed file systems designed for newly emerged data-intensive applications. Addressing the big data challenge requires an approach that utilizes both high performance computing and data-intensive computing power. Thus, HPC applications may need to interact with distributed file...
The I/O bottleneck issue has been acknowledged as one of main performance issues of high performance computing (HPC) systems for data-intensive scientific applications, and has attracted intensive studies in recent years. With the enlarging gap between the computing bandwidth and I/O bandwidth in projected next-generation HPC systems, this issue will become even worse. In this paper, we present a...
The performance gap between computing power and the I/O system is ever increasing, and in the meantime more and more High Performance Computing (HPC) applications are becoming data intensive. This study describes an I/O data replication scheme, named Pattern-Direct and Layout-Aware (PDLA) data replication scheme, to alleviate this performance gap. The basic idea of PDLA is replicating identified data...
Parallel file systems have been developed in recent years to ease the I/O bottleneck of high-end computing system. These advanced file systems offer several data layout strategies in order to meet the performance goals of specific I/O workloads. However, while a layout policy may perform well on some I/O workload, it may not perform as well for another. Peak I/O performance is rarely achieved due...
Improving energy efficiency is a primary concern in high performance computing system design. Because I/O accesses account for a large portion of the execution time for data intensive applications, energy-aware parallel I/O subsystems are critical for addressing challenges related to HPC energy efficiency. In this paper, we present an energy-conscious parallel I/O middleware approach that combines...
Many scientific applications spend a significant portion of their execution time in accessing data from files. Various optimization techniques exist to improve data access performance, such as data prefetching and data layout optimization. However, optimization process is usually a difficult task due to the complexity involved in understanding I/O behavior. Tools that can help simplify the optimization...
Recent technological advances are putting increased pressure on CPU scheduling. On one hand, processors have more cores. On the other hand, I/O systems have become more complex. Intensive research has been conducted on multi/many-core scheduling, however, most of the studies follow the conventional approach and focus on the utilization and load balance of the cores. In this study, we focus on increasing...
Parallel applications can benefit greatly from massive computational capability, but their performance suffers from large latency of I/O accesses. The poor I/O performance has been attributed as a critical cause of the low sustained performance of parallel computing systems. In this study, we propose a data layout-aware optimization strategy to promote a better integration of the parallel I/O middleware...
Energy efficiency and parallel I/O performance have become two critical measures in high performance computing (HPC). However, there is little empirical data that characterize the energy-performance behaviors of parallel I/O workload. In this paper, we present a methodology to profile the performance, energy, and energy efficiency of parallel I/O access patterns and report our findings on the impacting...
Parallel I/O prefetching is considered to be effective in improving I/O performance. However, the effectiveness depends on determining patterns among future I/O accesses swiftly and fetching data in time, which is difficult to achieve in general. In this study, we propose an I/O signature-based prefetching strategy. The idea is to use a predetermined I/O signature of an application to guide prefetching...
Parallel applications can benefit greatly from massive computational capability, but their performance usually suffers due to large latency in I/O accesses. Conventional I/O prefetching techniques are conservative and are limited by low accuracy and coverage. As the processor performance has been increasing rapidly and the computing power is virtually free, we introduce a novel speculative approach...
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