Benchmark: Inverse square root

Script Preparation code:

var fArr = new Float32Array(1);
var iArr = new Int32Array(fArr.buffer);
function fsr(n) {
	fArr[0] = n;
	iArr[0] = 0x5f375a86 - ( iArr[0] >> 1 );
	fArr[0] = fArr[0] * (1.5 - (n * 0.5) * fArr[0] * fArr[0]);
	return fArr[0];
}

Tests:

Traditional square root
var sqroots = []; for (var i = 0; i < 5000; i++) { sqroots.push(Math.sqrt(Math.random()*i)); }
Fast square root
var sqroots = []; for (var i = 0; i < 5000; i++) { sqroots.push(fsr(Math.random()*i)); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Traditional square root
Fast square root

Fastest: N/A

Slowest: N/A

Latest run results:

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

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Let's break down what's being tested in the provided JSON benchmark.

**Benchmark Definition**

The first part, "Inverse square root", represents a JavaScript microbenchmark that tests the execution speed of two different methods to calculate the inverse square root:

1. **Fast Square Root**: This method uses a specialized algorithm (not explicitly shown in the code) to calculate the inverse square root. The provided code snippet `fsr` is likely implementing this algorithm.
2. **Traditional Square Root**: This method simply uses the built-in `Math.sqrt` function to calculate the inverse square root.

**Options Compared**

In this benchmark, two options are being compared:

* **Fast Square Root** (using a specialized algorithm)
* **Traditional Square Root** (using the built-in `Math.sqrt` function)

**Pros and Cons of Each Approach**

1. **Fast Square Root**:
	* Pros: potentially faster execution speed due to optimized algorithm
	* Cons: may require more complex implementation, potentially harder to understand and maintain
2. **Traditional Square Root**:
	* Pros: simpler implementation, easier to understand and maintain
	* Cons: may be slower than the specialized algorithm

**Library Used**

In this benchmark, the `Float32Array` and `Int32Array` classes from the JavaScript standard library are used. These arrays provide efficient storage for floating-point and integer data types, respectively.

**Special JS Feature/Syntax**

The benchmark uses a feature called "bitwise operation" (specifically, the expression `0x5f375a86 - ( iArr[0] >> 1 )`) in the `fsr` function. This is a low-level optimization technique that leverages the properties of bitwise operations to improve performance.

**Other Considerations**

When choosing between these two approaches, consider the trade-off between code simplicity and performance. If speed is crucial, using a specialized algorithm like `fsr` might be beneficial. However, if readability and maintainability are more important, the traditional approach with `Math.sqrt` might be a better choice.

**Other Alternatives**

Some alternative approaches to calculating the inverse square root include:

* Using a library function from a third-party library (e.g., `mathjs`)
* Implementing a custom algorithm using floating-point arithmetic (e.g., Newton's method)
* Using SIMD instructions (if available on the target platform)

Keep in mind that these alternatives might have different performance characteristics and trade-offs, depending on the specific requirements of your use case.

Related benchmarks:

Inverse square root (version: 0)

Comparing performance of: Traditional square root vs Fast square root

Created: 8 years ago by: Guest

Jump to the latest result

Traditional square root

Fast square root

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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