Investigation of leading HPC I/O performance using a scientific-application derived benchmark
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
I/O performance challenges at leadership scale
Proceedings of the Conference on High Performance Computing Networking, Storage and Analysis
Managing Variability in the IO Performance of Petascale Storage Systems
Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Characterizing applications from power consumption: a case study for HPC benchmarks
ICT-GLOW'11 Proceedings of the First international conference on Information and communication on technology for the fight against global warming
State of the Practice Reports
TRACON: interference-aware scheduling for data-intensive applications in virtualized environments
Proceedings of 2011 International Conference for High Performance Computing, Networking, Storage and Analysis
I/O performance of virtualized cloud environments
Proceedings of the second international workshop on Data intensive computing in the clouds
One optimized I/O configuration per HPC application: leveraging the configurability of cloud
Proceedings of the Second Asia-Pacific Workshop on Systems
An optimal candidate selection model for self-acting load balancing of parallel file system
International Journal of High Performance Computing and Networking
Light-Weight parallel i/o analysis at scale
EPEW'11 Proceedings of the 8th European conference on Computer Performance Engineering
A dynamic and adaptive load balancing strategy for parallel file system with large-scale I/O servers
Journal of Parallel and Distributed Computing
Characterizing output bottlenecks in a supercomputer
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
McrEngine: a scalable checkpointing system using data-aware aggregation and compression
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Efficient data restructuring and aggregation for I/O acceleration in PIDX
SC '12 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
A New File-Specific Stripe Size Selection Method for Highly Concurrent Data Access
GRID '12 Proceedings of the 2012 ACM/IEEE 13th International Conference on Grid Computing
Proceedings of the 22nd international symposium on High-performance parallel and distributed computing
ACIC: automatic cloud I/O configurator for parallel applications
Proceedings of the 22nd international symposium on High-performance parallel and distributed computing
Modeling I/O interference for data intensive distributed applications
Proceedings of the 28th Annual ACM Symposium on Applied Computing
Survey Cloud monitoring: A survey
Computer Networks: The International Journal of Computer and Telecommunications Networking
ACIC: automatic cloud I/O configurator for HPC applications
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Toward millions of file system IOPS on low-cost, commodity hardware
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Characterization and modeling of PIDX parallel I/O for performance optimization
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Analysis of I/O Performance on an Amazon EC2 Cluster Compute and High I/O Platform
Journal of Grid Computing
McrEngine: A scalable checkpointing system using data-aware aggregation and compression
Scientific Programming - Selected Papers from Super Computing 2012
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The unprecedented parallelism of new supercomputing platforms poses tremendous challenges to achieving scalable performance for I/O intensive applications. Performance assessments using traditional I/O system and component benchmarks are difficult to relate back to application I/O requirements. However, the complexity of full applications motivates development of simpler synthetic I/O benchmarks as proxies to the full application. In this paper we examine the I/O requirements of a range of HPC applications and describe how the LLNL IOR synthetic benchmark was chosen as suitable proxy for the diverse workload. We show a procedure for selecting IOR parameters to match the I/O patterns of the selected applications and show it can accurately predict the I/O performance of the full applications. We conclude that IOR is an effective replacement for full-application I/O benchmarks and can bridge the gap of understanding that typically exists between stand-alone benchmarks and the full applications they intend to model.