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Showing result 1 - 5 of 11 essays matching the above criteria.
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1. Design of a Coprocessor Board for an On Board Computer
University essay from Luleå tekniska universitet/Institutionen för system- och rymdteknikAbstract : The goal of this thesis is to design a coprocessor expansion board for an On Board Computer (OBC) using Commersial Off The Shelf (COTS) components. This is done in order to meet the increasing demand of more processing power as spacecrafts become more autonomous. READ MORE
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2. Hardware Accelerator of Matrix Multiplication on FPGAs : Hardware Accelerator of Matrix Multiplication on FPGAs
University essay from Uppsala universitet/Institutionen för informationsteknologiAbstract : To solve the computational complexity and time-consuming problem of large matrix multiplication, this thesis design a hardware accelerator using parallel computation structure based on FPGA. After function simulation in ModelSim, matrix multiplication functional modules as a custom component used as a coprocessor in co-operation with Nios II CPU by Avalon bus interface. READ MORE
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3. Efficient Implementation of 3D Finite Difference Schemes on Recent Processor Architectures
University essay from KTH/Skolan för datavetenskap och kommunikation (CSC)Abstract : Efficient Implementation of 3D Finite Difference Schemes on Recent Processors Abstract In this paper a solver is introduced that solves a problem set modelled by the Burgers equation using the finite difference method: forward in time and central in space. The solver is parallelized and optimized for Intel Xeon Phi 7120P as well as Intel Xeon E5-2699v3 processors to investigate differences in terms of performance between the two architectures. READ MORE
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4. Accelerated Deep Learning using Intel Xeon Phi
University essay from Linnéuniversitetet/Institutionen för datavetenskap (DV)Abstract : Deep learning, a sub-topic of machine learning inspired by biology, have achieved wide attention in the industry and research community recently. State-of-the-art applications in the area of computer vision and speech recognition (among others) are built using deep learning algorithms. READ MORE
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5. Parallel implementation of the projected Gauss-Seidel method on the Intel Xeon Phi processor – Application to granular matter simulation.
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : Being able to simulate granular matter is important, because they are ubiquitous both in nature and in industry. Some examples of granular materials are ore, sand, coffee, rice, corn, and snow. Research and development of new, more accurate, and faster methods to simulate even more complex materials with millions of particles are needed. READ MORE