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How I Solved a 7-Day Calculation Problem in a weekend
- The author faced a performance issue where it took 15 seconds for the ML model to respond each time the slider moved.
- Due to budget constraints, they couldn't upgrade hardware and decided to pre-compute and cache values for efficiency.
- The calculations involved 10 SKUs, 4 regions, and 1,001 price points, totaling 40,040 requests.
- At 15 seconds per request, it would take around 6.9 days to process all the combinations.
- To speed up the process, they opted to pre-compute only odd values, with a 50% chance of instant retrieval.
- The author applied Gaussian sampling by focusing on more values in the middle of the range for better efficiency.
- By strategically choosing roughly 1/3rd of the total values, they reduced the processing time to approximately 55.5 hours.
- After running the computation script over the weekend, the results were ready by Monday morning.
- During the demo, the cached value was instantly retrieved when the slider was in the middle, leading to a successful presentation.
- The author trusted their methodology and was satisfied with the outcome.
- The approach significantly reduced the processing time and enabled a smoother demo.
- This creative solution showcased the author's problem-solving skills and knowledge in optimization.
- The use of Gaussian sampling and strategic computation helped overcome the performance challenge effectively.
- The successful demonstration highlighted the importance of thoughtful planning and innovative solutions in technical projects.
- The story reflects the author's ability to think outside the box and adapt techniques from different domains to solve real-world problems.
- The efficient use of resources and strategic decision-making were key factors in resolving the performance issue.
- The author's commitment to finding an optimal solution under constraints demonstrates dedication and expertise in problem-solving.
- The experience emphasizes the importance of analyzing data patterns and applying tailored strategies for improved efficiency.
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