The input/output complexity of sorting and related problems
Communications of the ACM
Parallel algorithms for shared-memory machines
Handbook of theoretical computer science (vol. A)
Introduction to parallel computing: design and analysis of algorithms
Introduction to parallel computing: design and analysis of algorithms
Journal of the ACM (JACM)
Communication-Efficient Parallel Sorting
SIAM Journal on Computing
Towards an energy complexity of computation
Information Processing Letters - Special issue in honor of Edsger W. Dijkstra
Concurrent cache-oblivious b-trees
Proceedings of the seventeenth annual ACM symposium on Parallelism in algorithms and architectures
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Power-performance considerations of parallel computing on chip multiprocessors
ACM Transactions on Architecture and Code Optimization (TACO)
Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture
Managing energy-performance tradeoffs for multithreaded applications on multiprocessor architectures
Proceedings of the 2007 ACM SIGMETRICS international conference on Measurement and modeling of computer systems
Performance-Energy Tradeoffs for Matrix Multiplication on FPGA-Based Mixed-Mode Chip Multiprocessors
ISQED '07 Proceedings of the 8th International Symposium on Quality Electronic Design
Provably good multicore cache performance for divide-and-conquer algorithms
Proceedings of the nineteenth annual ACM-SIAM symposium on Discrete algorithms
Fundamental parallel algorithms for private-cache chip multiprocessors
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
Corollaries to Amdahl's Law for Energy
IEEE Computer Architecture Letters
Prediction models for multi-dimensional power-performance optimization on many cores
Proceedings of the 17th international conference on Parallel architectures and compilation techniques
Computation with Energy-Time Trade-Offs: Models, Algorithms and Lower-Bounds
ISPA '08 Proceedings of the 2008 IEEE International Symposium on Parallel and Distributed Processing with Applications
On the Effects of Memory Latency and Bandwidth on Supercomputer Application Performance
IISWC '07 Proceedings of the 2007 IEEE 10th International Symposium on Workload Characterization
Analysis of Parallel Algorithms for Energy Conservation in Scalable Multicore Architectures
ICPP '09 Proceedings of the 2009 International Conference on Parallel Processing
Analysis of Parallel Algorithms for Energy Conservation with GPU
GREENCOM-CPSCOM '10 Proceedings of the 2010 IEEE/ACM Int'l Conference on Green Computing and Communications & Int'l Conference on Cyber, Physical and Social Computing
Modeling the energy consumption for concurrent executions of parallel tasks
Proceedings of the 14th Communications and Networking Symposium
An energy complexity model for algorithms
Proceedings of the 4th conference on Innovations in Theoretical Computer Science
Analytical modeling and simulation of the energy consumption of independent tasks
Proceedings of the Winter Simulation Conference
Energy cost evaluation of parallel algorithms for multiprocessor systems
Cluster Computing
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Energy consumption by computer systems has emerged as an important concern. However, the energy consumed in executing an algorithm cannot be inferred from its performance alone: it must be modeled explicitly. This paper analyzes energy consumption of parallel algorithms executed on shared memory multicore processors. Specifically, we develop a methodology to evaluate how energy consumption of a given parallel algorithm changes as the number of cores and their frequency is varied. We use this analysis to establish the optimal number of cores to minimize the energy consumed by the execution of a parallel algorithm for a specific problem size while satisfying a given performance requirement. We study the sensitivity of our analysis to changes in parameters such as the ratio of the power consumed by a computation step versus the power consumed in accessing memory. The results show that the relation between the problem size and the optimal number of cores is relatively unaffected for a wide range of these parameters.