Benchmark: hypot vs sqrt - MeasureThat.net

Script Preparation code:

var dx = 100;
var dy = 200;

Tests:

hyp
Math.hypot(dx,dy);
sqrt
var c = Math.sqrt(dx * dx + dy * dy);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
hyp
sqrt

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 9 months ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/138.0.0.0 Safari/537.36

Browser/OS: Chrome 138 on Windows

View result in a separate tab

Test name	Executions per second
hyp	40103616.0 Ops/sec
sqrt	123706832.0 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 and explain what's being tested.

**Benchmark Definition**

The provided JSON defines a benchmark with two test cases: `hypot` and `sqrt`. The script preparation code initializes variables `dx` and `dy` with values 100 and 200, respectively. These values are likely used as inputs for the mathematical operations to be measured.

**Test Cases**

There are two test cases:

1. `hyp`: This test case uses the `Math.hypot` function to calculate the Euclidean distance between `dx` and `dy`. The JavaScript code is: `var c = Math.hypot(dx, dy);`
2. `sqrt`: This test case calculates the same value using a manual implementation of the Pythagorean theorem: `var c = Math.sqrt(dx * dx + dy * dy);`

**Options Compared**

The two test cases compare the performance of:

* `Math.hypot` (browser's built-in function) vs a manual implementation of the Euclidean distance formula.

**Pros and Cons**

* **Math.hypot**: This function is likely to be optimized for performance by the browser's JavaScript engine. It may provide better results due to:
	+ Fewer CPU instructions executed.
	+ Reduced memory allocation (no temporary variables needed).
	+ Possibly, cache-friendly access patterns.
However, using a built-in function might also introduce some overhead, such as:
	+ Additional function call overhead.
	+ Potential differences in behavior due to the implementation details.

* **Manual Implementation**: This approach allows for better control over the code's performance characteristics. However, it may lead to:
	+ More CPU instructions executed (due to loops and arithmetic operations).
	+ Increased memory allocation (for temporary variables).

**Library**

None of the test cases explicitly uses a library beyond the built-in `Math` object.

**Special JS Feature or Syntax**

There are no special JavaScript features or syntax used in these test cases. They only rely on standard JavaScript language constructs.

**Other Alternatives**

For measuring the performance of mathematical operations, other alternatives might include:

* Using different data types (e.g., integers vs floats) to see how they affect performance.
* Testing with larger or smaller input values to observe scaling effects.
* Comparing performance across multiple browsers or environments.
* Using a more advanced benchmarking framework or library that provides additional features and control.

Keep in mind that the specific options for alternatives will depend on the goals and requirements of the benchmark.

Related benchmarks:

hypot vs sqrt (version: 0)

Comparing performance of: hyp vs sqrt

Created: 2 years ago by: Guest

Jump to the latest result

hyp

sqrt

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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