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funloop.org | ||
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matbesancon.xyz
Solving a cutting stock problem step by step using Julia and JuMP |
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bayesianneuron.com
[AI summary] The user has shared a detailed exploration of optimizing the 0/1 Knapsack problem using dynamic programming with Python and NumPy. They discuss various optimization techniques, including reducing memory usage with a 2-row approach, vectorization using NumPy's `np.where` for faster computation, and the performance improvements achieved. The final implementation shows significant speedups, especially for large-scale problems, and the user highlights the importance of vectorization and efficient memory management in computational tasks. |
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wonger.dev
[AI summary] This article discusses the development of a web-based tool for creating and manipulating Venn diagrams, focusing on the use of bitstrings and clipping masks to represent regions. It covers the challenges of implementing interactive Venn diagrams, including the need for efficient region highlighting and erasing, and explores the use of bitwise operations and combinatorics (like Pascal's triangle) to manage complex Venn configurations. The author also touches on optimization techniques and potential future improvements for the tool. |
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patshaughnessy.net
[AI summary] The article discusses the process of learning to read x86 assembly language, focusing on how it can be a useful skill for understanding low-level operations of microprocessors. It outlines the challenges of reading assembly, especially in debugging scenarios, and provides an example of translating Ruby code into x86 assembly using Crystal. The article also explains the syntax and structure of x86 assembly, including register usage, instruction suffixes, and the differences between AT&T and Intel syntax. It highlights the complexity of x86 assembly due to its historical evolution and the need for understanding register sizes and operand notation. |
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