Benchmark: Sqrt vs Alpha max plus beta min algorithm

Tests:

Math.sqrt()
const RAD_PER_DEG = Math.PI / 180; for(let i = 0; i < 360; i += 0.1) { const r = i * RAD_PER_DEG; const x = Math.sin(r); const y = -Math.cos(r); const s = Math.sqrt(x * x + y * y); }
Alpha max plus beta min
const ALPHA = 0.96043387010342; const BETA = 0.397824734759316; const RAD_PER_DEG = Math.PI / 180; for(let i = 0; i < 360; i += 0.1) { const r = i * RAD_PER_DEG; const x = Math.abs(Math.sin(r)); const y = Math.abs(-Math.cos(r)); const h = x > y ? ALPHA*x + BETA*y : ALPHA*y + BETA*x; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Math.sqrt()
Alpha max plus beta min

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Linux; Android 10; K) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/132.0.0.0 Mobile Safari/537.36

Browser/OS: Chrome Mobile 132 on Android

View result in a separate tab

Test name	Executions per second
Math.sqrt()	8439.4 Ops/sec
Alpha max plus beta min	13471.1 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark definition and test cases to help explain what's being tested.

**Benchmark Definition**

The benchmark definition is a JSON object that provides information about the benchmark being created. In this case, it has the following fields:

* `Name`: A human-readable name for the benchmark.
* `Description`: An optional description of the benchmark (in this case, empty).
* `Script Preparation Code`: Optional code to be executed before running the benchmark (empty in this case).
* `Html Preparation Code`: Optional HTML code to be used when creating the benchmark page (empty in this case).

**Test Cases**

The test cases are individual tests that compare different approaches. There are two test cases:

1. **Math.sqrt()**
This test case compares the performance of using the built-in `Math.sqrt()` function to calculate the square root of a number.

```javascript
const RAD_PER_DEG = Math.PI / 180;
for(let i = 0; i < 360; i += 0.1) {
  const r = i * RAD_PER_DEG;
  const x = Math.sin(r);
  const y = -Math.cos(r);
  const s = Math.sqrt(x * x + y * y);
}
```

This test case is likely measuring the performance of calculating the square root of a value in radians.

2. **Alpha max plus beta min**
This test case compares the performance of an alternative algorithm for calculating the square root, which involves using alpha and beta values to approximate the square root.

```javascript
const ALPHA = 0.96043387010342;
const BETA = 0.397824734759316;
const RAD_PER_DEG = Math.PI / 180;
for(let i = 0; i < 360; i += 0.1) {
  const r = i * RAD_PER_DEG;
  const x = Math.abs(Math.sin(r));
  const y = Math.abs(-Math.cos(r));
  const h = x > y ? ALPHA*x + BETA*y : ALPHA*y + BETA*x;
}
```

This test case is likely measuring the performance of this alternative algorithm for calculating the square root.

**Library and Special JS Features**

There are no libraries explicitly mentioned in the benchmark definition. However, it's worth noting that the `Math` object is used extensively throughout both test cases.

One special JS feature being used is the use of template literals (the backticks ``) to define multiline strings. This feature was introduced in ECMAScript 2015 (ES6).

**Alternatives**

Some alternatives to this benchmarking approach could include:

* Using a different testing framework or tool, such as Jest or Mocha.
* Adding more test cases to compare other algorithms or approaches for calculating the square root.
* Using a different type of data or input to test the performance of these algorithms (e.g., large numbers, complex expressions).
* Comparing the performance of these algorithms on different platforms or devices.

Related benchmarks:

Sqrt vs Alpha max plus beta min algorithm (version: 0)

Comparing performance of: Math.sqrt() vs Alpha max plus beta min

Created: 3 years ago by: Guest

Jump to the latest result

Math.sqrt()

Alpha max plus beta min

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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