Benchmark: Math max - MeasureThat.net

Script Preparation code:

var arr = []
for(let i=0;i<10000000;i++) {
  arr.push(Math.random() - Math.random())
}
function min(val) {
  return val > 0 ? val : 0
}

function mathmin(val) {
  return Math.min(0, val) 
}

Tests:

comparison
for(let i=0;i<10000000;i++) { min(arr[i]) }
lib
for(let i=0;i<10000000;i++) { mathmin(arr[i]) }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
comparison
lib

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: one year ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/130.0.0.0 Safari/537.36

Browser/OS: Chrome 130 on Windows

View result in a separate tab

Test name	Executions per second
comparison	0.4 Ops/sec
lib	0.4 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases to understand what's being tested.

**Benchmark Definition JSON**

The benchmark definition represents a JavaScript function that generates an array of 10 million random numbers using `Math.random() - Math.random()` (a common trick to generate pseudo-random numbers) and then iterates through this array, applying two functions: `min` and `mathmin`.

*   `min(val)` is a simple function that returns the minimum value between `val` and 0.
*   `mathmin(val)` is another function that uses the built-in `Math.min()` function to achieve the same result as `min(val)`. The purpose of `mathmin` seems to be for comparison, possibly to test for the presence of negative numbers or other edge cases.

**Comparison (Test Case)**

The "comparison" test case measures the performance of iterating through the array and calling the `min` function. This approach is likely used to test the overhead of iterating over an array, comparing values, and applying a simple function like `min`.

Pros:

*   Easy to understand and implement
*   Focuses on the iteration and comparison operations

Cons:

*   May not accurately represent real-world scenarios that involve more complex logic or data structures

**lib (Test Case)**

The "lib" test case measures the performance of iterating through the array and calling the `mathmin` function. This approach is used to test the overhead of using a built-in function like `Math.min()`.

Pros:

*   Tests the impact of using built-in functions on performance
*   Helps ensure that libraries or frameworks can optimize their implementations

Cons:

*   May not accurately represent scenarios where custom logic is preferred

**Lib and Comparison**

Both approaches have pros and cons, as mentioned above. The "lib" test case provides insight into how built-in functions affect performance, while the "comparison" test case focuses on iteration and comparison operations.

**Other Considerations**

When writing benchmarks, it's essential to consider various factors that might impact performance:

*   **Cache locality**: How do different data structures and access patterns affect cache behavior?
*   **Memory allocation**: What are the costs of allocating and deallocating memory during runtime?
*   **System resources**: How do different scenarios impact CPU usage, memory usage, and I/O operations?

**Alternative Approaches**

When creating benchmarks, you might consider exploring alternative approaches:

*   **Parallelization**: Can you parallelize the benchmark to simulate multi-threaded or concurrent execution environments?
*   **Distributed testing**: Can you split the workload across multiple machines to test scalability and performance under load?
*   **Memory-intensive scenarios**: What are the costs of memory allocation, deallocation, and fragmentation?

Keep in mind that the specific approach depends on the goals and requirements of your benchmark.

Related benchmarks:

Math max (version: 0)

Comparing performance of: comparison vs lib

Created: 7 years ago by: Guest

Jump to the latest result

comparison

lib

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated one year ago):