A practical algorithm for exact array dependence analysis
Communications of the ACM
RAID: high-performance, reliable secondary storage
ACM Computing Surveys (CSUR)
Compiler and runtime support for out-of-core HPF programs
ICS '94 Proceedings of the 8th international conference on Supercomputing
SUIF: an infrastructure for research on parallelizing and optimizing compilers
ACM SIGPLAN Notices
Automatic optimization of communication in compiling out-of-core stencil codes
ICS '96 Proceedings of the 10th international conference on Supercomputing
Proceedings of the fifth workshop on I/O in parallel and distributed systems
Compiler-based I/O prefetching for out-of-core applications
ACM Transactions on Computer Systems (TOCS)
Optimizing compilers for modern architectures: a dependence-based approach
Optimizing compilers for modern architectures: a dependence-based approach
Dependence Analysis for Supercomputing
Dependence Analysis for Supercomputing
Application Transformations for Energy and Performance-Aware Device Management
Proceedings of the 2002 International Conference on Parallel Architectures and Compilation Techniques
Massive arrays of idle disks for storage archives
Proceedings of the 2002 ACM/IEEE conference on Supercomputing
Conserving disk energy in network servers
ICS '03 Proceedings of the 17th annual international conference on Supercomputing
DRPM: dynamic speed control for power management in server class disks
Proceedings of the 30th annual international symposium on Computer architecture
Energy conservation techniques for disk array-based servers
Proceedings of the 18th annual international conference on Supercomputing
PB-LRU: a self-tuning power aware storage cache replacement algorithm for conserving disk energy
Proceedings of the 18th annual international conference on Supercomputing
Software-Directed Disk Power Management for Scientific Applications
IPDPS '05 Proceedings of the 19th IEEE International Parallel and Distributed Processing Symposium (IPDPS'05) - Papers - Volume 01
Managing server energy and operational costs in hosting centers
SIGMETRICS '05 Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Exposing disk layout to compiler for reducing energy consumption of parallel disk based systems
Proceedings of the tenth ACM SIGPLAN symposium on Principles and practice of parallel programming
Reducing Energy Consumption of Disk Storage Using Power-Aware Cache Management
HPCA '04 Proceedings of the 10th International Symposium on High Performance Computer Architecture
Disk layout optimization for reducing energy consumption
Proceedings of the 19th annual international conference on Supercomputing
Energy efficient prefetching and caching
ATEC '04 Proceedings of the annual conference on USENIX Annual Technical Conference
Taming the memory hogs: using compiler-inserted releases to manage physical memory intelligently
OSDI'00 Proceedings of the 4th conference on Symposium on Operating System Design & Implementation - Volume 4
Automatic Partitioning of Parallel Loops for Cache-Coherent Multiprocessors
ICPP '93 Proceedings of the 1993 International Conference on Parallel Processing - Volume 01
Thwarting the power-hungry disk
WTEC'94 Proceedings of the USENIX Winter 1994 Technical Conference on USENIX Winter 1994 Technical Conference
Scheduling for reduced CPU energy
OSDI '94 Proceedings of the 1st USENIX conference on Operating Systems Design and Implementation
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Power consumption of large servers and clusters has recently been a popular research topic, since this issue is important from both technical and environmental viewpoints. The prior research proposed disk power management as one of the important ways of reducing overall power of a large system and considered both hardware-based and softwareguided disk power reduction schemes. One of the common characteristics of the previously proposed approaches to disk power reduction is that they work with a given disk access pattern. In comparison, the goal of the approach proposed in this paper is to restructure application code using an optimizing compiler so that disk idle periods are lengthened. This in turn allows the underlying disk power management scheme to be more effective since such schemes usually prefer the long idle periods over the short ones. Our approach targets at large scientific applications that operate on disk-resident arrays using nested loops and exhibit regular data access patterns. To test the effectiveness of the proposed approach, we implemented it within an optimizing compiler and performed experiments with six data-intensive applications that manipulate disk-resident data. Our experimental analysis shows that the proposed approach is very successful in practice and reduces the total disk energy consumption on average by 18.17%, as compared to an execution without any disk power management, and by 11.55%, as compared to an execution that employs disks with low-power capabilities without our code restructuring approach.