Profiler and compiler assisted adaptive I/O prefetching for shared storage caches

Son, Seung Woo; Muralidhara, Sai Prashanth; Öztürk, Özcan; Kandemir, Mahmut; Kolcu, I.; Karakoy, Mustafa

doi:10.1145/1454115.1454133

Cited by 13 publications

(8 citation statements)

References 30 publications

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“…There are a large body of studies on data access pattern analysis using parallel I/O traces [6] [7][8] [9]. Usually, the data access pattern can be described in I/O trace files, I/O signature [8], profiles [28] [29], and hints [30], etc. The offline approach can utilize all of them to analyze access cost and distribute data blocks across file servers.…”

Section: A Offline Approachmentioning

confidence: 99%

A Server-Level Adaptive Data Layout Strategy for Parallel File Systems

Song

Jin

et al. 2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops &Amp; PhD Forum

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Abstract-Parallel file systems are widely used for providing a high degree of I/O parallelism to mask the gap between I/O and memory speed. However, peak I/O performance is rarely attained due to complex data access patterns of applications. Based on the observation that the I/O performance of small requests is often limited by the request service rate, and the performance of large requests is limited by I/O bandwidth, we take into consideration both factors and propose a server-level adaptive data layout strategy. The proposed strategy adopts different stripe sizes for different file servers according to the data access characteristics on each individual server. We let the file servers that can fully utilize bandwidth hold more data, and the file servers that are limited with request service rate hold less data. As a result, heavy-load servers can offload some data accesses to light-load servers for potential improvement of I/O performance. We present a method to measure access cost for each data block and then utilize an equal-depth histogram approach to distributed data blocks across multiple servers adaptively, so as to balance data accesses on all file servers. Analytical and experimental results demonstrate that the proposed server-level adaptive layout strategy can improve I/O performance by as much as 80.3% and is more appropriate for applications with complex data access patterns.Keywords-Server-level adaptive data layout, variable stripe size, equal-depth histogram, data layout optimization, parallel file system

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Section: A Offline Approachmentioning

confidence: 99%

A Server-Level Adaptive Data Layout Strategy for Parallel File Systems

Song

Jin

et al. 2012

2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops &Amp; PhD Forum

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“…Helper threading has been used in softwareguided prefetching to hide I/O latency [5,23]. To minimize I/O latency, these techniques require timely prefetching.…”

Section: Related Workmentioning

confidence: 99%

Effective parallelization of loops in the presence of I/O operations

Feng

Gupta

Neamtiu

2012

Proceedings of the 33rd ACM SIGPLAN Conference on Programming Language Design and Implementation

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Software-based thread-level parallelization has been widely studied for exploiting data parallelism in purely computational loops to improve program performance on multiprocessors. However, none of the previous efforts deal with efficient parallelization of hybrid loops, i.e., loops that contain a mix of computation and I/O operations. In this paper, we propose a set of techniques for efficiently parallelizing hybrid loops. Our techniques apply DOALL parallelism to hybrid loops by breaking the cross-iteration dependences caused by I/O operations. We also support speculative execution of I/O operations to enable speculative parallelization of hybrid loops. Helper threading is used to reduce the I/O bus contention caused by the improved parallelism. We provide an easy-to-use programming model for exploiting parallelism in loops with I/O operations. Parallelizing hybrid loops using our model requires few modifications to the code. We have developed a prototype implementation of our programming model. We have evaluated our implementation on a 24-core machine using eight applications, including a widely-used genomic sequence assembler and a multi-player game server, and others from PARSEC and SPEC CPU2000 benchmark suites. The hybrid loops in these applications take 23%-99% of the total execution time on our 24-core machine. The parallelized applications achieve speedups of 3.0x-12.8x with hybrid loop parallelization over the sequential versions of the same applications. Compared to the versions of applications where only computation loops are parallelized, hybrid loop parallelization improves the application performance by 68% on average.

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“…Data prefetching has been proposed as a solution for hiding latency of I/O accesses [33,44,15,14,40,45,22,51]. In case of I/O prefetching, the goal is to hide I/O latency by overlapping disk I/O with computation.…”

Section: I/o Prefetchingmentioning

confidence: 99%

Cashing in on hints for better prefetching and caching in PVFS and MPI-IO

Patrick

Kandemir

Karakoy

et al. 2010

Proceedings of the 19th ACM International Symposium on High Performance Distributed Computing

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In this work, we propose, implement and test a novel approach to the management of parallel I/O in high-performance computing. Our proposed approach is built upon three complementary ideas: (i) allowing users to place hints into the application code indicating high-level data access patterns, (ii) enabling an optimizing compiler to process these hints and develop I/O optimization strategies, and (iii) enhancing the I/O stack to accept these optimizations and process them across the different layers in the stack. We describe a general hint processing framework that accommodates this approach and demonstrate its potential by applying it to two sample problems: (i) shared storage cache management and (ii) I/O prefetching. In the former, our approach decides, at each program point of interest, the ideal set of data blocks to keep in shared storage caches in the I/O stack, and in the latter, the high-level data access pattern is propagated from application layer to the parallel file system layer for prefetching data from the storage subsystem. Our approach is designed to complement and work synergistically with the MPI-IO and PVFS frameworks and exploits the characteristics of applications written using these software. We tested our approach using both synthetic data access patterns and disk I/O intensive application programs. The results collected indicate that the proposed approach improves over existing storage caching and I/O prefetching schemes by 28% and 66%, respectively.

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Profiler and compiler assisted adaptive I/O prefetching for shared storage caches

Cited by 13 publications

References 30 publications

A Server-Level Adaptive Data Layout Strategy for Parallel File Systems

A Server-Level Adaptive Data Layout Strategy for Parallel File Systems

Effective parallelization of loops in the presence of I/O operations

Cashing in on hints for better prefetching and caching in PVFS and MPI-IO

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