Towards an energy-aware scientific I/O interface

Authors:
Julian M. Kunkel;Timo Minartz;Michael Kuhn;Thomas Ludwig
Affiliations:
Department of Informatics, University of Hamburg, Hamburg, Germany;Department of Informatics, University of Hamburg, Hamburg, Germany;Department of Informatics, University of Hamburg, Hamburg, Germany;DKRZ GmbH & Department of Informatics, University of Hamburg, Hamburg, Germany
Venue:
Computer Science - Research and Development
Year:
2012

Citing 14
Cited 0

Predicting Application Run Times Using Historical Information

IPPS/SPDP '98 Proceedings of the Workshop on Job Scheduling Strategies for Parallel Processing
Using multiple energy gears in MPI programs on a power-scalable cluster

Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
A Power-Aware Run-Time System for High-Performance Computing

SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
The Tau Parallel Performance System

International Journal of High Performance Computing Applications
Analyzing the Energy-Time Trade-Off in High-Performance Computing Applications

IEEE Transactions on Parallel and Distributed Systems
Bounding energy consumption in large-scale MPI programs

Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Flexible IO and integration for scientific codes through the adaptable IO system (ADIOS)

CLADE '08 Proceedings of the 6th international workshop on Challenges of large applications in distributed environments
Energy-Efficient Cluster Computing via Accurate Workload Characterization

CCGRID '09 Proceedings of the 2009 9th IEEE/ACM International Symposium on Cluster Computing and the Grid
Adaptable, metadata rich IO methods for portable high performance IO

IPDPS '09 Proceedings of the 2009 IEEE International Symposium on Parallel&Distributed Processing
Automatic performance analysis with periscope

Concurrency and Computation: Practice & Experience - Scalable Tools for High-End Computing
The Scalasca performance toolset architecture

Concurrency and Computation: Practice & Experience - Scalable Tools for High-End Computing
Using Historical Data to Predict Application Runtimes on Backfilling Parallel Systems

PDP '10 Proceedings of the 2010 18th Euromicro Conference on Parallel, Distributed and Network-based Processing
PerfExpert: An Easy-to-Use Performance Diagnosis Tool for HPC Applications

Proceedings of the 2010 ACM/IEEE International Conference for High Performance Computing, Networking, Storage and Analysis
Profile-based optimization of power performance by using dynamic voltage scaling on a PC cluster

IPDPS'06 Proceedings of the 20th international conference on Parallel and distributed processing

Quantified Score

Hi-index	0.00

Visualization

Abstract

Intelligently switching energy saving modes of CPUs, NICs and disks is mandatory to reduce the energy consumption.Hardware and operating system have a limited perspective of future performance demands, thus automatic control is suboptimal. However, it is tedious for a developer to control the hardware by himself.In this paper we propose an extension of an existing I/O interface which on the one hand is easy to use and on the other hand could steer energy saving modes more efficiently. Furthermore, the proposed modifications are beneficial for performance analysis and provide even more information to the I/O library to improve performance.When a user annotates the program with the proposed interface, I/O, communication and computation phases are labeled by the developer. Run-time behavior is then characterized for each phase, this knowledge could be then exploited by the new library.