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Log Test
(version: 0)
Comparing performance of:
Non Cached vs Cached
Created:
3 years ago
by:
Guest
Jump to the latest result
Script Preparation code:
var base = 80000000000;
Tests:
Non Cached
var start = 5 / Math.log(base); var end = 10 / Math.log(base);
Cached
var baseVal = Math.log(base); var start = 5 / baseVal; var end = 10 / baseVal;
Rendered benchmark preparation results:
Suite status:
<idle, ready to run>
Run tests (2)
Previous results
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Test case name
Result
Non Cached
Cached
Fastest:
N/A
Slowest:
N/A
Latest run results:
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Autogenerated LLM Summary
(model
llama3.2:3b
, generated one year ago):
Let's break down the provided JSON and benchmark preparation code to understand what is being tested. **Benchmark Overview** The benchmark measures the performance difference between two approaches for calculating logarithmic values in JavaScript: 1. **Cached approach**: Stores the result of `Math.log(base)` in a variable, `baseVal`, and uses this cached value for subsequent calculations. 2. **Non-Cached approach**: Does not cache the result of `Math.log(base)`, recalculating it for each use. **Options Compared** The benchmark compares the performance difference between these two approaches: Pros of Cached approach: * Reduced overhead due to repeated calculations * Potential for better performance, especially with large inputs Cons of Cached approach: * Requires additional memory allocation for storing the cached value * May lead to increased memory usage if not managed properly Pros of Non-Cached approach: * No additional memory required * Simple implementation Cons of Non-Cached approach: * Higher overhead due to repeated calculations * Potential for slower performance, especially with large inputs **Library and Special JS Feature** The benchmark uses the `Math.log()` function from the JavaScript standard library. This function is used to calculate the natural logarithm of a given number. **Special JS Feature** There are no special JavaScript features or syntax mentioned in the provided code. The focus is on comparing the performance difference between two approaches for calculating logarithmic values. **Other Alternatives** If you were to implement this benchmark yourself, you could consider adding additional variations, such as: * Using a different caching mechanism (e.g., object cache, array cache) * Adding more inputs or edge cases * Comparing performance with other libraries or frameworks (e.g., V8, SpiderMonkey) In terms of the cached approach, you might also consider using techniques like memoization or optimization to reduce memory usage. Overall, this benchmark provides a simple yet informative way to compare the performance difference between two approaches for calculating logarithmic values in JavaScript.
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