Corollaries to Amdahl's Law for Energy
IEEE Computer Architecture Letters
A Constraint Programming Approach for Allocation and Scheduling on the CELL Broadband Engine
CP '08 Proceedings of the 14th international conference on Principles and Practice of Constraint Programming
ACM Transactions on Design Automation of Electronic Systems (TODAES)
Validity of the single processor approach to achieving large scale computing capabilities
AFIPS '67 (Spring) Proceedings of the April 18-20, 1967, spring joint computer conference
Performance analysis of accelerated image registration using GPGPU
Proceedings of 2nd Workshop on General Purpose Processing on Graphics Processing Units
CSE '09 Proceedings of the 2009 International Conference on Computational Science and Engineering - Volume 01
Cortical architectures on a GPGPU
Proceedings of the 3rd Workshop on General-Purpose Computation on Graphics Processing Units
Energy-aware high performance computing with graphic processing units
HotPower'08 Proceedings of the 2008 conference on Power aware computing and systems
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In this paper, novel objectives for the design space exploration of GPGPU applications are presented. The design space exploration takes the combination of energy efficiency and realtime requirements into account. This is completely different to the commonest high performance computing objective, which is to accelerate an application as much as possible.As a proof-of-concept, a GPGPU based image processing and virus detection pipeline for a newly developed biosensor, called PAMONO, is presented. The importance of realtime capable and portable biosensors increases according to rising number of worldwide spreading virus infections. The local availability of biosensors at e.g. airports to detect viruses in-situ demand to take costs and energy for the development of GPGPU-based biosensors into account. The consideration of the energy is especially important with respect to green computing.The results of the conducted design space exploration show that during the design process of a GPGPU-based application the platform must also be evaluated to get the most energy-aware solution. In particular, it was shown that increasing numbers of parallel running cores need not decrease the energy consumption.