Benchmark: Division - MeasureThat.net

Script Preparation code:

this.numberA = Math.random() * 1000;

Tests:

regular
return this.numberA / 1000 / 60;
faster?
return this.numberA / 60000;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
regular
faster?

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10.15; rv:109.0) Gecko/20100101 Firefox/113.0

Browser/OS: Firefox 113 on Mac OS X 10.15

View result in a separate tab

Test name	Executions per second
regular	584295424.0 Ops/sec
faster?	683661632.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided JSON to understand what is being tested and the different approaches compared.

**Benchmark Definition**

The benchmark definition is a JavaScript function that calculates the division of `this.numberA` by 1000 and then again by 60. This is done twice: once with a simple division (`this.numberA / 1000`) and another time with an additional intermediate step (`(this.numberA / 1000) / 60`). The difference between these two approaches is the number of operations performed.

**Script Preparation Code**

The script preparation code is used to set up the environment before running the benchmark. In this case, `Math.random() * 1000` generates a random value for `this.numberA`, ensuring that the division operation has a variable result each time the benchmark is run.

**Html Preparation Code**

There is no HTML preparation code provided, which means that the JavaScript execution context and environment are not affected by any additional HTML-related setup.

**Test Cases**

The test cases are defined in the "Individual test cases" section. There are two test cases:

1. `regular`: This test case uses the simple division approach (`this.numberA / 1000`) without any intermediate steps.
2. `faster?`: This test case uses the more complex approach with an additional intermediate step (`(this.numberA / 1000) / 60`).

**Pros and Cons of Different Approaches**

* **Simple Division (Regular)**:
	+ Pros: Fewer operations, potentially faster execution time.
	+ Cons: May not take advantage of optimizations that can improve performance in more complex scenarios.
* **Complex Division (Faster?)**:
	+ Pros: Can potentially leverage compiler optimizations or other performance enhancements that apply to the additional intermediate step.
	+ Cons: More operations are performed, which may lead to slower execution times.

Other considerations:

* The use of `Math.random() * 1000` ensures that each benchmark run starts with a different value for `this.numberA`, reducing any potential bias towards one approach over the other.
* The comparison between these two approaches can help identify performance optimizations in JavaScript engines.

**Library and Purpose**

There is no explicit library mentioned in the provided JSON. However, it's likely that the benchmark script uses built-in JavaScript functions or a specific optimization framework to measure performance.

**Special JS Feature/Syntax**

None are mentioned in this specific benchmark definition.

**Other Alternatives**

To create similar benchmarks, you could consider using other tools and frameworks, such as:

1. Google Benchmark: A popular open-source benchmarking library for C++ but also supports JavaScript.
2. micro-benchmark: Another lightweight benchmarking tool specifically designed for Node.js and JavaScript engines.
3. Perf: A built-in Node.js module that allows running performance tests and benchmarks.

Keep in mind that these alternatives might have different features, ease of use, or compatibility with specific JavaScript engines.

Related benchmarks:

Division (version: 0)

Comparing performance of: regular vs faster?

Created: one year ago by: Guest

Jump to the latest result

regular

faster?

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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