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Showing result 1 - 5 of 49 essays matching the above criteria.
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1. Benchmarking linear-algebra algorithms on CPU- and FPGA-based platforms
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Moore’s law is the main driving factor behind the rapid evolution of computers that has been observed in the past 50 years. Though the law is soon ending due to heat- and sizing-related issues. One solution to continuing the evolution is utilizing alternative computer hardware, where parallel hardware is especially interesting. READ MORE
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2. Modernizing and Evaluating the Autotuning Framework of SkePU 3
University essay from Linköpings universitet/Institutionen för datavetenskapAbstract : Autotuning is a method which enables a program to automatically choose the most suitable parameters that optimizes it for a certain goal e.g. speed, cost, etc. READ MORE
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3. Integrating SkePU's algorithmic skeletons with GPI on a cluster
University essay from Linköpings universitet/Programvara och systemAbstract : As processors' clock-speed flattened out in the early 2000s, multi-core processors became more prevalent and so did parallel programming. However this programming paradigm introduces additional complexities, and to combat this, the SkePU framework was created. READ MORE
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4. Convolutional Neural Network FPGA-accelerator on Intel DE10-Standard FPGA
University essay from Linköpings universitet/Elektroniska Kretsar och SystemAbstract : Convolutional neural networks (CNNs) have been extensively used in many aspects, such as face and speech recognition, image searching and classification, and automatic drive. Hence, CNN accelerators have become a trending research. Generally, Graphics processing units (GPUs) are widely applied in CNNaccelerators. READ MORE
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5. Automatic GPU optimization through higher-order functions in functional languages
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : Over recent years, graphics processing units (GPUs) have become popular devices to use in procedures that exhibit data-parallelism. Due to high parallel capability, running procedures on a GPU can result in an execution time speedup ranging from a couple times faster to several orders of magnitude faster, compared to executing serially on a central processing unit (CPU). READ MORE