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Convolutional neural network (CNN), well-knownto be computationally intensive, is a fundamental algorithmicbuilding block in many computer vision and artificial intelligenceapplications that follow the deep learning principle. This workpresents a novel stochastic-based and scalable hardware architectureand circuit design that computes a convolutional neuralnetwork with FPGA. The key idea is to implement...
Power gating (PG) is an effective power efficiency improvement technique. Future general-purpose graphics processing units (GPGPUs) will likely feature hundreds of compute units (CUs) and be power constrained, which leads to serious challenges to existing PG methodologies. In this paper, we propose novel design-time and run-time techniques to effectively implement power gating in future GPGPUs. Based...
The FCUDA project aims to improve programmability of FPGAs and expression of application parallelism in High Level Synthesis (HLS) through the use of the CUDA language. The CUDA language is a popular single-instruction multiple data (SIMD) style programming language with wide adoption, thus offering significant opportunity to bring experienced programmers to FPGA computing. The FCUDA project now has...
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