Essays about: "Parallelization computing"
Showing result 1 - 5 of 24 essays containing the words Parallelization computing.
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1. Using MPI One-Sided Communication for Parallel Sudoku Solving
University essay from Umeå universitet/Institutionen för datavetenskapAbstract : This thesis investigates the scalability of parallel Sudoku solving using Donald Knuth’s Dancing Links and Algorithm X with two different MPI communication methods: MPI One-Sided Communication and MPI Send-Receive. The study compares the performance of the two communication approaches and finds that MPI One-Sided Communication exhibits better scalability in terms of speedup and efficiency. READ MORE
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2. Minimum Cost Distributed Computing using Sparse Matrix Factorization
University essay from KTH/Optimeringslära och systemteoriAbstract : Distributed computing is an approach where computationally heavy problems are broken down into more manageable sub-tasks, which can then be distributed across a number of different computers or servers, allowing for increased efficiency through parallelization. This thesis explores an established distributed computing setting, in which the computationally heavy task involves a number of users requesting a linearly separable function to be computed across several servers. READ MORE
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3. D-Wave Systems Quantum Computing : State-of-the-Art and Performance Comparison with Classical Computing
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : The aim of this project is to study Quantum Computing state-of-art and to compare it with classical computing methods. The research is focused on D-Wave Systems’ Quantum Computing approach, exploring its architectures: Chimera and Pegasus; tools, and its Quantum Annealing process. READ MORE
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4. Acceleration of Machine-Learning Pipeline Using Parallel Computing
University essay from Uppsala universitet/Signaler och systemAbstract : Researchers from Lund have conducted research on classifying images in three different categories, faces, landmarks and objects from EEG data [1]. The researchers used SVMs (Support Vector Machine) to classify between the three different categories [2, 3]. READ MORE
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5. GPU-Assisted Collision Avoidance for Trajectory Optimization : Parallelization of Lookup Table Computations for Robotic Motion Planners Based on Optimal Control
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)Abstract : One of the biggest challenges associated with optimization based methods forrobotic motion planning is their extreme sensitivity to a good initial guess,especially in the presence of local minima in the cost function landscape.Additional challenges may also arise due to operational constraints, robotcontrollers sometimes have very little time to plan a trajectory to perform adesired function. READ MORE