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Visar resultat 1 - 5 av 26 uppsatser som matchar ovanstående sökkriterier.

1. 1. Analysis and optimization of an implementation of hierarchical Tucker tensors

   Kandidat-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Daniel Wallgren; [2023]
   Nyckelord :;

   Sammanfattning : The hierarchical Tucker tensor format is a format for approximated tensors which has been decomposed into smaller parts. This structure can be useful in high-dimensional computer simulations. One implementation of this structure is in a library called htlib. LÄS MER

3. 2. On quantum systems and the measurement problem

   Master-uppsats, Stockholms universitet/Fysikum

   Författare :Nicolas Boulle; [2023]
   Nyckelord :Quantum physics; the measurement problem; quantum information; Hilbert spaces; physical systems; unitary; collapse; Euler angles parametrization; Copenhagen interpretation; many- world; measure;

   Sammanfattning : We focus on the Tensor Product Structure (TPS) of the Hilbert space and the fact that a choice in the TPS has an impact on the representation of the studied quantum system. We define the measurement problem in quantum mechanics and present some theories about quantum mechanics, each of them highlighting a different approach to quantum measurements. LÄS MER

4. 3. Designing Effective Derivative Line Filters: Utilizing convolution to extract extra information

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Gustaf Lorentzon; [2023]
   Nyckelord :Computational Fluid Dynamics; Convolution Filters; Convolution Kernels; Derivatives; Extracting Extra Accuracy; Filtration; Post-processing; Smoothness-Increasing Accuracy-Conserving; Signal-processing; Visualization; Vorticity; Beräkningsbaserad Strömningsdynamik; Faltningsfilter; Faltningskärnor; Derivator; Extrahering av Extra Noggrannhet; Filtrering; Efterbehandling; Kontinuitetsökande; Noggrannhetsbevarande; Signalbehandling; Visualisering; Vorticitet;

   Sammanfattning : The ability to generate accurate approximations of derivatives holds significant importance in numerous scientific fields, including chemistry, economics and fluid mechanics. This thesis is centred around extracting hidden information in data using Smoothness-Increasing Accuracy-Conserving (SIAC) filters. LÄS MER

5. 4. Multi-Scale Topology Optimization of Lattice Structures Using Machine Learning

   Uppsats för yrkesexamina på avancerad nivå, Uppsala universitet/Tillämpad mekanik

   Författare :Julia Ibstedt; [2023]
   Nyckelord :Topology optimization; Multi-scale topology optimization; Machine learning; Gaussian process; Homogenization; Inverse homogenization; Anisotropic materials; Symmetry groups; Material property space; Topologioptimering; Flerskalig topologioptimering; Maskininlärning; Gaussian process; Homogenisering; Anisotropa material; Symmetrigrupper; Materialegenskapsrymd;

   Sammanfattning : This thesis explores using multi-scale topology optimization (TO) by utilizing inverse homogenization to automate the adjustment of each unit-cell's geometry and placement in a lattice structure within a pressure vessel (the design domain) to achieve desired structural properties. The aim is to find the optimal material distribution within the design domain as well as desired material properties at each discretized element and use machine learning (ML) to map microstructures with corresponding prescribed effective properties. LÄS MER

7. 5. Register Caching for Energy Efficient GPGPU Tensor Core Computing

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Qiran Qian; [2023]
   Nyckelord :Computer Architecture; GPGPU; Tensor Core; GEMM; Energy Efficiency; Register File; Cache; Instruction Scheduling; Datorarkitektur; GPGPU; Tensor Core; GEMM; energieffektivitet; registerfil; cache; instruktionsschemaläggning;

   Sammanfattning : The General-Purpose GPU (GPGPU) has emerged as the predominant computing device for extensive parallel workloads in the fields of Artificial Intelligence (AI) and Scientific Computing, primarily owing to its adoption of the Single Instruction Multiple Thread architecture, which not only provides a wealth of thread context but also effectively hide the latencies exposed in the single threads executions. As computational demands have evolved, modern GPGPUs have incorporated specialized matrix engines, e. LÄS MER