A case study of parallel I/O for biological sequence search on Linux clusters

Zhu, Yan; Jiang, Hong; Qin, Xiao; Swanson,

doi:10.1109/clustr.2003.1253329

Cited by 3 publications

References 20 publications

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Client cache for PVFS2

Camacho

Nieto

Anguita

et al. 2010

2010 First International Conference on Parallel, Distributed and Grid Computing (PDGC 2010)

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Engineering and scientific applications usually require to manage large quantities of data with different programs. The I/O demands of these applications get higher as they get larger because processor and memory speed increase. In order to improve performance and make programming much easier these applications can use parallel file systems. The relation between performance and easiness of programming can be additionally improved by using caches in clients. PVFS is a free parallel file system developed by a multi-institution team of parallel I/O, networking and storage experts. This work proposes a cache in the second version of PVFS in order to improve performance of data-intensive applications with several programs and to improve performance in a parallel program without modifying it to take advantage of the several cores in a processor. We analyze the performance of the cache implementation.

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Client cache for PVFS2

Camacho

Nieto

Anguita

et al. 2010

2010 First International Conference on Parallel, Distributed and Grid Computing (PDGC 2010)

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Fault tolerant PVFS2 based on data replication

Nieto

Camacho

Anguita

et al. 2010

2010 First International Conference on Parallel, Distributed and Grid Computing (PDGC 2010)

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An Energy-Oriented Evaluation of Buffer Cache Algorithms Using Parallel I/O Workloads

Yue

Zhu

Cai

2008

IEEE Trans. Parallel Distrib. Syst.

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Power consumption is an important issue for cluster supercomputers as it directly affects running cost and cooling requirements. This paper investigates the memory energy efficiency of high-end data servers used for supercomputers. Emerging memory technologies allow memory devices to dynamically adjust their power states and enable free rides by overlapping multiple DMA transfers from different I/O buses to the same memory device. To achieve maximum energy saving, the memory management on data servers needs to judiciously utilize these energy-aware devices. As we explore different management schemes under five real-world parallel I/O workloads, we find that the memory energy behavior is determined by a complex interaction among four important factors: 1) cache hit rates that may directly translate performance gain into energy saving, 2) cache populating schemes that perform buffer allocation and affect access locality at the chip level, 3) request clustering that aims to temporally align memory transfers from different buses into the same memory chips, and 4) access patterns in workloads that affect the first three factors.

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A case study of parallel I/O for biological sequence search on Linux clusters

Cited by 3 publications

References 20 publications

Client cache for PVFS2

Client cache for PVFS2

Fault tolerant PVFS2 based on data replication

An Energy-Oriented Evaluation of Buffer Cache Algorithms Using Parallel I/O Workloads

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