2012 · 28 citations · 13 references
ComputingComputer EngineeringComputer ScienceComputer ArchitectureHeterogeneous ComputingParallel ComputingAccelerator ArchitectureGraphics Processing Unit ArchitectureHardware AccelerationHardware ArchitectureHeterogeneous System ArchitectureParallel ArchitecturesApplication Performance AssessmentApplication Performance OptimizationEnergy-efficient ArchitectureEnergy-efficient Hardware AccelerationHardware HeterogeneityHeterogeneous Computing ArchitectureHeterogeneous Computing SystemsMany-core Processors
We believe that by adapting architectures to fit the requirements of a given application domain, we can significantly improve the efficiency of computation. To validate the idea for our application domain, we evaluate a wide spectrum of commodity computing platforms to quantify the potential benefits of heterogeneity and customization for the domain-specific applications. In particular, we choose medical imaging as the application domain for investigation, and study the application performance and energy efficiency across a diverse set of commodity hardware platforms, such as general-purpose multi-core CPUs, massive parallel many-core GPUs, low-power mobile CPUs and fine-grain customizable FPGAs. This study leads to a number of interesting observations that can be used to guide further development of domain-specific architectures.
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Tony F. Chan, Luminita A. Vese · IEEE Transactions on Image Processing · 2001 · 10.3K citations
Bias scheduling in heterogeneous multi-core architectures
David Koufaty, Dheeraj Reddy, Scott Hahn · 2010 · 259 citations