Search for dissertations about: "Approximate Computing"
Showing result 1 - 5 of 63 swedish dissertations containing the words Approximate Computing.
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1. Reducing Memory Traffic with Approximate Compression
Abstract : Memory bandwidth is a critical resource in modern systems and has an increasing demand. The large number of on-chip cores and specialized accelerators improves the potential processing throughput but also calls for higher data rates. In addition, new emerging data-intensive applications further increase memory traffic. READ MORE
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2. Large-scale simulation-based experiments with stochastic models using machine learning-assisted approaches : Applications in systems biology using Markov jump processes
Abstract : Discrete and stochastic models in systems biology, such as biochemical reaction networks, can be modeled as Markov jump processes. The chemical master equation describes how the probability distribution of a biochemical system's states evolves. Unfortunately, solutions to the chemical master equation only exist for trivial problems. READ MORE
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3. The quantum approximate optimization algorithm: optimization problems and implementations
Abstract : This thesis explores the Quantum Approximate Optimization Algorithm (QAOA), a hybrid classical-quantum algorithm designed to solve combinatorial optimization problems. The goal of this algorithm is to iteratively optimize a variational state to approximate the ground state of a cost Hamiltonian that encodes a combinatorial optimization problem. READ MORE
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4. Applying quantum approximate optimization to the heterogeneous vehicle routing problem
Abstract : Quantum computing offers new heuristics for combinatorial problems. With small- and intermediate-scale quantum devices becoming available, it is possible to implement and test these heuristics on small-size problems. READ MORE
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5. Application of the quantum approximate optimization algorithm to combinatorial optimization problems
Abstract : This licentiate thesis is an extended introduction to the accompanying papers, which encompass a study of the quantum approximate optimization algorithm (QAOA). It is a hybrid quantum-classical algorithm for solving combinatorial optimization problems and is a promising algorithm to run on near term quantum devices. READ MORE