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Deep Convolutional Networks (ConvNets) are currently superior in benchmark performance, but the associated demands on computation and data transfer prohibit straightforward mapping on energy constrained wearable platforms. The computational burden can be overcome by dedicated hardware accelerators, but it is the sheer amount of data transfer, and level of utilization that determines the energy-efficiency...
Modern GPUs are true power houses in every meaning of the word: While they offer general-purpose (GPGPU) compute performance an order of magnitude higher than that of conventional CPUs, they have also been rapidly approaching the infamous “power wall”, as a single chip sometimes consumes more than 300W. Thus, the design space of GPGPU microarchitecture has been extended by another dimension: power...
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