A static power model for architects
Proceedings of the 33rd annual ACM/IEEE international symposium on Microarchitecture
IEEE Transactions on Parallel and Distributed Systems
The design, implementation, and evaluation of a compiler algorithm for CPU energy reduction
PLDI '03 Proceedings of the ACM SIGPLAN 2003 conference on Programming language design and implementation
Bi-criteria algorithm for scheduling jobs on cluster platforms
Proceedings of the sixteenth annual ACM symposium on Parallelism in algorithms and architectures
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
Power-aware resource allocation in high-end systems via online simulation
Proceedings of the 19th annual international conference on Supercomputing
A performance-conserving approach for reducing peak power consumption in server systems
Proceedings of the 19th annual international conference on Supercomputing
A Power-Aware Run-Time System for High-Performance Computing
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Just In Time Dynamic Voltage Scaling: Exploiting Inter-Node Slack to Save Energy in MPI Programs
SC '05 Proceedings of the 2005 ACM/IEEE conference on Supercomputing
Online resource matching for heterogeneous grid environments
CCGRID '05 Proceedings of the Fifth IEEE International Symposium on Cluster Computing and the Grid (CCGrid'05) - Volume 2 - Volume 02
Adaptive, transparent frequency and voltage scaling of communication phases in MPI programs
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Proceedings of the 2006 ACM/IEEE conference on Supercomputing
Proceedings of the 39th Annual IEEE/ACM International Symposium on Microarchitecture
CCGRID '07 Proceedings of the Seventh IEEE International Symposium on Cluster Computing and the Grid
Analyzing the Energy-Time Trade-Off in High-Performance Computing Applications
IEEE Transactions on Parallel and Distributed Systems
Power capping: a prelude to power shifting
Cluster Computing
Selective preemption strategies for parallel job scheduling
International Journal of High Performance Computing and Networking
Bounding energy consumption in large-scale MPI programs
Proceedings of the 2007 ACM/IEEE conference on Supercomputing
Characterizing application sensitivity to OS interference using kernel-level noise injection
Proceedings of the 2008 ACM/IEEE conference on Supercomputing
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
The Datacenter as a Computer: An Introduction to the Design of Warehouse-Scale Machines
A job self-scheduling policy for HPC infrastructures
JSSPP'07 Proceedings of the 13th international conference on Job scheduling strategies for parallel processing
PowerPack: Energy Profiling and Analysis of High-Performance Systems and Applications
IEEE Transactions on Parallel and Distributed Systems
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
Optimizing job performance under a given power constraint in HPC centers
GREENCOMP '10 Proceedings of the International Conference on Green Computing
Power-Aware Linear Programming based Scheduling for heterogeneous computer clusters
GREENCOMP '10 Proceedings of the International Conference on Green Computing
Green HPC: From Nice to Necessity
Computing in Science and Engineering
Understanding the future of energy-performance trade-off via DVFS in HPC environments
Journal of Parallel and Distributed Computing
Integrating dynamic pricing of electricity into energy aware scheduling for HPC systems
SC '13 Proceedings of the International Conference on High Performance Computing, Networking, Storage and Analysis
Dynamic Voltage Scaling Scheduling on Power-Aware Clusters under Power Constraints
DS-RT '13 Proceedings of the 2013 IEEE/ACM 17th International Symposium on Distributed Simulation and Real Time Applications
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Power has become the primary constraint in high performance computing. Traditionally, parallel job scheduling policies have been designed to improve certain job performance metrics when scheduling parallel workloads on a system with a given number of processors. The available number of processors is not anymore the only limitation in parallel job scheduling. The recent increase in processor power consumption has resulted in a new limitation: the available power. Given constraints naturally lead to an optimization problem. We proposed MaxJobPerf, a new parallel job scheduling policy based on integer linear programming. Dynamic Voltage Frequency Scaling (DVFS) is a widely used technique that running applications at reduced CPU frequency/voltage trades increased execution time for power reduction. The optimization problem determines which jobs should run and at which frequency. In this paper, we compare the MaxJobPerf policy against other power budgeting policies for different power budgets. It clearly outperforms the other power-budgeting approaches at the parallel job scheduling level. Furthermore, we give a detailed analysis of the policy parameters including a discussion on how to manage job reservations to avoid job starvation.