Hitting the memory wall: implications of the obvious
ACM SIGARCH Computer Architecture News
ICFP '97 Proceedings of the second ACM SIGPLAN international conference on Functional programming
Heuristic Algorithms for Scheduling Independent Tasks on Nonidentical Processors
Journal of the ACM (JACM)
Improving dynamic voltage scaling algorithms with PACE
Proceedings of the 2001 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Journal of Parallel and Distributed Computing
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models
Sensitivity Analysis in Practice: A Guide to Assessing Scientific Models
Power reduction techniques for microprocessor systems
ACM Computing Surveys (CSUR)
Integrating concurrency control and energy management in device drivers
Proceedings of twenty-first ACM SIGOPS symposium on Operating systems principles
A Practical Introduction to Computer Architecture
A Practical Introduction to Computer Architecture
Managing contention for shared resources on multicore processors
Communications of the ACM
Online cache modeling for commodity multicore processors
Proceedings of the 19th international conference on Parallel architectures and compilation techniques
Memory-Aware Green Scheduling on Multi-core Processors
ICPPW '10 Proceedings of the 2010 39th International Conference on Parallel Processing Workshops
Reducing energy consumption in distributed computing through economic resource allocation
International Journal of Grid and Utility Computing
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Today's datacenters and large scale enterprise computing are power hungry. A lot of research effort is devoted in industry and academy to address this challenging issue. In this context, a new type of enterprise computing platform is being investigated. This computing platform is composed of hundred of millicomputers, each requiring orders of magnitude less power. The millicomputing aims to significantly increase the energy efficiency of data centers by delivering high performance computing. However, this approach brings challenges that must be met in order to compete with the current practice. This paper addresses two such critical challenges. First, it suggests how to decompose large applications into smaller tasks, better suited to millicomputers. Then, it casts the performance oriented and energy efficient problem into a soft real-time scheduling problem, for which several algorithms are then proposed and evaluated. Sensitivity analysis is used to provide insights into the model, and plan the evaluation of the scheduling algorithms. The contention found in multi-core millicomputing processors is also accounted for.