Title
Improving Collective Mpi-Io Using Topology-Aware Stepwise Data Aggregation With I/O Throttling
Abstract
MPI-IO has been used in an internal I/O interface layer of HDF5 or PnetCDF, where collective MPI-IO plays a big role in parallel I/O to manage a huge scale of scientific data. However, existing collective MPI-IO optimization named two-phase I/O has not been tuned enough for recent supercomputers consisting of mesh/torus interconnects and a huge scale of parallel file systems due to lack of topology-awareness in data transfers and optimization for parallel file systems. In this paper, we propose I/O throttling and topology-aware stepwise data aggregation in two-phase I/O of ROMIO, which is a representative MPI-IO library, in order to improve collective MPI-IO performance even if we have multiple processes per compute node. Throttling I/O requests going to a target file system mitigates I/O request contention, and consequently I/O performance improvements are achieved in file access phase of two-phase I/O. Topology-aware aggregator layout with paying attention to multiple aggregators per compute node alleviates contention in data aggregation phase of two-phase I/O. In addition, stepwise data aggregation improves data aggregation performance. HPIO benchmark results on the K computer indicate that the proposed optimization has achieved up to about 73% and 39% improvements in write performance compared with the original implementation using 12,288 and 24,576 processes on 3,072 and 6,144 compute nodes, respectively.
Year
DOI
Venue
2018
10.1145/3149457.3149464
PROCEEDINGS OF THE INTERNATIONAL CONFERENCE ON HIGH PERFORMANCE COMPUTING IN ASIA-PACIFIC REGION (HPC ASIA 2018)
Keywords
Field
DocType
MPI-IO, two-phase I/O, aggregator, topology-aware stepwise data aggregation, I/O throttling
Hierarchical Data Format,File system,Interface layer,News aggregator,Computer science,Parallel computing,Torus,Input/output,Data aggregator,Bandwidth throttling
Conference
Citations 
PageRank 
References 
1
0.36
14
Authors
6
Name
Order
Citations
PageRank
Yuichi Tsujita16212.62
Atsushi Hori210.69
Toyohisa Kameyama311.03
Atsuya Uno48712.94
Fumiyoshi Shoji5527.36
Yutaka Ishikawa61449188.06