Empirical Optimization of Collective Communications with ADCL

Benkert, Katharina; Gabriel, Edgar

doi:10.1007/978-3-642-11851-7_3

Cited by 1 publication

(1 citation statement)

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“…To match DRAM page size and CPU cache size, the CMSSL library contains routines for automatic selection of optimal parameters, such as loop order and operator alignments, for matrix multiplication in both local and global scopes [18]. Benkert et al uses an empirical approach for MPI communication auto-tuning with ADCL library [3]. In comparison, Orthrus introduces a self-adapting technique to improve collective I/O performance and demonstrates its feasibility and effectiveness, which may inspire more innovative applications of the technique to address I/O issues in large-scale HPC systems.…”

Section: Related Workmentioning

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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Section: Related Workmentioning

confidence: 99%