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 lukesingham.com
Grokking Algorithms - Summary
| | bayesianneuron.com
0/1 Knapsack Discrete Optimization w/ Dynamic Programming - Bayesian Neuron
3.6 parsecs away

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| | [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.
| | initialcommit.com
Plain old graphs that solve your problems
3.1 parsecs away

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| | The graphs in computer software are a little different from the bar graphs in high school. Sure, they are still a mapping of relations just represented differently.
| | www.integralist.co.uk
Integralist
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| | savvinov.com
Where did my RAM go? - Oracle Diagnostician
33.4 parsecs away

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| In my previous posts (e.g. here and here) I showed how to use ps output (e.g. from ExaWatcher) visualization to spot performance problems in Linux. Here I'd like to show that this approach can be taken a little bit further, namely, to find the source of increase in memory usage. The R code for this...