Noncontiguous I/O accesses through MPI-IO

Ching, Avery; Choudhary, Alok; Coloma, Kenin; Liao, Wei-keng; Ross, Robert; Gropp, William

doi:10.1109/ccgrid.2003.1199358

Cited by 56 publications

(37 citation statements)

References 16 publications

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“…Datatype I/O [5] and list I/O [6] are the two other techniques that allow users to access multiple non-contiguous data using a single I/O routine. Datatype I/O is used to access data with certain regularity, while list I/O is designed to handle more general cases.…”

Section: A Modifying Request Streams For Greater Spatial Localitymentioning

confidence: 99%

IOrchestrator: Improving the Performance of Multi-node I/O Systems via Inter-Server Coordination

Zhang

Davis

Jiang

2010

2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis

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Abstract-A cluster of data servers and a parallel file system are often used to provide high-throughput I/O service to parallel programs running on a compute cluster. To exploit I/O parallelism parallel file systems stripe file data across the data servers. While this practice is effective in serving asynchronous requests, it may break individual program's spatial locality, which can seriously degrade I/O performance when the data servers concurrently serve synchronous requests from multiple I/O-intensive programs.In this paper we propose a scheme, IOrchestrator, to improve I/O performance of multi-node storage systems by orchestrating I/O services among programs when such inter-data-server coordination is dynamically determined to be cost effective. We have implemented IOrchestrator in the PVFS2 parallel file system. Our experiments with representative parallel benchmarks show that IOrchestrator can significantly improve I/O performanceby up to a factor of 2.5-delivered by a cluster of data servers servicing concurrently-running parallel programs. Notably, we have not observed any scenarios in which the use of IOrchestrator causes substantial performance degradation.

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Section: A Modifying Request Streams For Greater Spatial Localitymentioning

confidence: 99%

IOrchestrator: Improving the Performance of Multi-node I/O Systems via Inter-Server Coordination

Zhang

Davis

Jiang

2010

2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis

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“…Non-contiguous access patterns and overlapping I/O patterns [8] [9] [12] have been widely studied and the customized locking schemes, process rank ordering and handshaking have been proposed. List locks and datatype locks [5] [10] have maximum concurrency, but they acquire and maintain locks for all regions accessed by a process.…”

Section: Methodsmentioning

confidence: 99%

Conflict Detection Algorithm to Minimize Locking for MPI-IO Atomicity

Sehrish

Wang

Thakur

2009

Recent Advances in Parallel Virtual Machine and Message Passing Interface

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Abstract. Many scientific applications require high-performance concurrent I/O accesses to a file by multiple processes. Those applications rely indirectly on atomic I/O capabilities in order to perform updates to structured datasets, such as those stored in HDF5 format files. Current support for atomicity in MPI-IO is provided by locking around the operations, imposing lock overhead in all situations, even though in many cases these operations are non-overlapping in the file. We propose to isolate non-overlapping accesses from overlapping ones in independent I/O cases, allowing the nonoverlapping ones to proceed without imposing lock overhead. To enable this, we have implemented an efficient conflict detection algorithm in MPI-IO using MPI file views and datatypes. We show that our conflict detection scheme incurs minimal overhead on I/O operations, making it an effective mechanism for avoiding locks when they are not needed.

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“…The benefits of having a smaller number of large requests include reduced request processing overhead and increased disk efficiency. As the core-first and the disk-first schemes do not use list I/O [10] to pack requests, the number of requests to the kernels of the data nodes is not reduced. When the requests are very small (even if they are well ordered), ROMIO's increased disk efficiency through data sieving can be still substantial in comparison.…”

Section: Candidate Collective-i/o Implementationsmentioning

confidence: 99%

Orthrus: A Framework for Implementing Efficient Collective I/O in Multi-core Clusters

Zhang

Davis

et al. 2014

Lecture Notes in Computer Science

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Abstract. Optimization of access patterns using collective I/O imposes the overhead of exchanging data between processes. In a multi-core-based cluster the costs of inter-node and intra-node data communication are vastly different, and heterogeneity in the efficiency of data exchange poses both a challenge and an opportunity for implementing efficient collective I/O. The opportunity is to effectively exploit fast intra-node communication. We propose to improve communication locality for greater data exchange efficiency. However, such an effort is at odds with improving access locality for I/O efficiency, which can also be critical to collective-I/O performance. To address this issue we propose a framework, Orthrus, that can accommodate multiple collective-I/O implementations, each optimized for some performance aspects, and dynamically select the best performing one accordingly to current workload and system patterns. We have implemented Orthrus in the ROMIO library. Our experimental results with representative MPI-IO benchmarks on both a small dedicated cluster and a large production HPC system show that Orthrus can significantly improve collective I/O performance under various workloads and system scenarios.

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Noncontiguous I/O accesses through MPI-IO

Abstract: Abstract

Cited by 56 publications

References 16 publications

IOrchestrator: Improving the Performance of Multi-node I/O Systems via Inter-Server Coordination

IOrchestrator: Improving the Performance of Multi-node I/O Systems via Inter-Server Coordination

Conflict Detection Algorithm to Minimize Locking for MPI-IO Atomicity

Orthrus: A Framework for Implementing Efficient Collective I/O in Multi-core Clusters

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