Benchmark: Native - MeasureThat.net

Tests:

Native
1/Math.sqrt(958573654687437984)
Fast inverse
var buf = new ArrayBuffer(4), f32=new Float32Array(buf), u32=new Uint32Array(buf); function squareRoot(x) { var x2 = 0.5 * (f32[0] = x); u32[0] = (0x5f3759df - (u32[0] >> 1)); var y = f32[0]; y = y * ( 1.5 - ( x2 * y * y ) ); //newton's method return ~~(0.5 + y * x) << 0 ; //bitwise rounding method } squareRoot(958573654687437984);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Native
Fast inverse

Fastest: N/A

Slowest: N/A

Latest run results:

No previous run results

This benchmark does not have any results yet. Be the first one to run it!

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 and explain what's being tested, compared, and their pros and cons.

**Benchmark Overview**

MeasureThat.net is a platform that allows users to create and run JavaScript microbenchmarks. The provided benchmark definition and test cases demonstrate two approaches: native and fast inverse (which uses a custom implementation).

The benchmark measures the execution time of mathematical operations, specifically:

* Native: Measures the execution time of the built-in `Math.sqrt` function.
* Fast inverse: Measures the execution time of a custom implementation for calculating square roots.

**Native Benchmark**

In the native benchmark, only one test case is provided:
```javascript
1/Math.sqrt(958573654687437984)
```
This test case measures the execution time of the built-in `Math.sqrt` function. The JavaScript engine will automatically optimize and execute this expression.

**Fast Inverse Benchmark**

The fast inverse benchmark provides two test cases:

* Test 1: Measures the execution time of a custom implementation for calculating square roots.
```javascript
var buf = new ArrayBuffer(4),
    f32=new Float32Array(buf),
    u32=new Uint32Array(buf);

function squareRoot(x) {
    var x2 = 0.5 * (f32[0] = x);
    u32[0] = (0x5f3759df - (u32[0] >> 1));
    var y = f32[0];
    y  = y * ( 1.5 - ( x2 * y * y ) ); //newton's method
    return ~~(0.5 + y * x) << 0 ; //bitwise rounding method
}

squareRoot(958573654687437984);
```
This custom implementation uses a combination of bitwise operations and Newton's method to estimate the square root.

**Comparison**

The two test cases are compared in terms of execution time, with the fast inverse benchmark providing a separate result for each test case. The latest benchmark results show:

* Chrome 87: Native (7501597.5 executions per second) vs Fast inverse (1229363.25 executions per second)

**Pros and Cons**

Native Benchmark:

Pros:

* Uses built-in functions, which are typically optimized by the JavaScript engine.
* No additional memory allocation or data structure creation required.

Cons:

* Execution time may be affected by the JavaScript engine's optimization strategies.
* No control over the implementation details.

Fast Inverse Benchmark:

Pros:

* Provides a custom implementation that can be optimized for specific use cases.
* Allows for fine-grained control over the calculation method and data structures used.

Cons:

* Requires additional memory allocation and data structure creation, which may impact performance.
* The custom implementation may not be as efficient as the built-in `Math.sqrt` function.

**Other Considerations**

In addition to the execution time, other factors that may affect the benchmark results include:

* Memory usage: The fast inverse benchmark creates an array buffer, which can consume memory resources.
* Cache locality: The custom implementation may exhibit poor cache locality due to its use of bitwise operations and data structure allocation.

**Alternatives**

If you're interested in exploring alternative approaches for calculating square roots or other mathematical operations, some options include:

* Using specialized libraries like NumJS or Mathjs
* Implementing custom algorithms using languages like C++ or Rust
* Leveraging hardware acceleration (e.g., SIMD instructions) to speed up calculations

Keep in mind that the best approach will depend on your specific use case and performance requirements.

Related benchmarks:

Native (version: 0)

Comparing performance of: Native vs Fast inverse

Created: 5 years ago by: Guest

Jump to the latest result

Native

Fast inverse

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):