Effective and Transparent Use of GPU in Constraint Solving

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Publicat a:ProQuest Dissertations and Theses (2025)
Autor principal: Tardivo, Fabio
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ProQuest Dissertations & Theses
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100 1 |a Tardivo, Fabio 
245 1 |a Effective and Transparent Use of GPU in Constraint Solving 
260 |b ProQuest Dissertations & Theses  |c 2025 
513 |a Dissertation/Thesis 
520 3 |a Combinatorial problems are pervasive in our lives. From solving a Sudoku puzzle to quickly delivering Amazon orders, all these tasks requires finding a good combinations of elements, locations, and more. The ability to effectively solve combinatorial problems is essential, as it minimizes resource waste, prevents service delays, and reduces costs. For decades, Constraint Programming (CP) has been successfully employed to tackle combinatorial problems. However, as these problems grow larger and more complex each year, constraint solvers must continuously advance their capabilities to keep pace. Graphics Processing Units (GPUs) accelerate costly computations and have been successfully used across various domains. Their unprecedented power and accessibility prompt a (re)consideration of their use in CP. This thesis identifies and develops novel approaches to effectively and transparently harness the power of GPUs to advance CP. It introduces a shift in perspective that enables the achievement of meaningful results and paves the way for addressing increasingly complex and large-scale problems.  
653 |a Computer science 
653 |a Computer engineering 
653 |a Web studies 
653 |a Information technology 
773 0 |t ProQuest Dissertations and Theses  |g (2025) 
786 0 |d ProQuest  |t ProQuest Dissertations & Theses Global 
856 4 1 |3 Citation/Abstract  |u https://www.proquest.com/docview/3216745877/abstract/embedded/ZKJTFFSVAI7CB62C?source=fedsrch 
856 4 0 |3 Full Text - PDF  |u https://www.proquest.com/docview/3216745877/fulltextPDF/embedded/ZKJTFFSVAI7CB62C?source=fedsrch