Benchmark: test float - MeasureThat.net

Tests:

float
let i = 10.00000123; i*i;
num
let i = 10; i*i;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
float
num

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

I'll break down the provided benchmark JSON and explain what's being tested, compared options, pros/cons of those approaches, and other considerations.

**Benchmark Definition**

The provided `benchmark definition` JSON is empty, which means that there is no script or HTML code associated with this benchmark. It only contains metadata like a name and description.

**Individual Test Cases**

There are two individual test cases:

1. **Test Case 1: "float"**
	* Benchmark Definition: `let i = 10.00000123; i*i;`
	* This test case is designed to measure the performance of floating-point arithmetic operations in JavaScript.
2. **Test Case 2: "num"**
	* Benchmark Definition: `let i = 10; i*i;`
	* This test case is designed to measure the performance of integer arithmetic operations in JavaScript.

**Options Compared**

In this benchmark, two options are being compared:

1. **Floating-point arithmetic**: The first test case measures the performance of floating-point arithmetic operations, specifically squaring a number with a large decimal value (10.00000123).
2. **Integer arithmetic**: The second test case measures the performance of integer arithmetic operations, specifically squaring an integer value (10).

**Pros and Cons**

The pros and cons of these approaches are:

* **Floating-point arithmetic:**
	+ Pros:
		- Can be useful for measuring performance in numerical computations.
		- May help identify issues related to floating-point precision or rounding errors.
	+ Cons:
		- May not be representative of real-world scenarios where floating-point numbers are used extensively.
		- Can be sensitive to the specific JavaScript engine implementation and its handling of floating-point arithmetic.
* **Integer arithmetic:**
	+ Pros:
		- More representative of typical use cases in software development, such as working with integers or performing mathematical operations on integer values.
		- Less susceptible to issues related to floating-point precision or rounding errors.
	+ Cons:
		- May not be as useful for measuring performance in numerical computations that require high precision.

**Library and Special JS Features**

There is no library mentioned in the provided benchmark JSON. However, it's worth noting that some JavaScript engines may use libraries like `Math.js` or other libraries to optimize mathematical operations. But in this case, the benchmarks seem to be focused on basic arithmetic operations.

**Special JS Features**

There are no special JS features mentioned in the provided benchmark JSON.

**Other Alternatives**

Other alternatives for measuring performance in JavaScript include:

1. **GC (Garbage Collection) tests**: Measures how long it takes for a JavaScript engine to collect garbage and free memory.
2. **Threaded tasks**: Measures the performance of concurrent execution of multiple threads or tasks.
3. **UI-related tests**: Measures the performance of rendering, painting, or updating UI elements in a web application.

Keep in mind that these alternatives may require more complex setup and configuration compared to basic arithmetic operations benchmarks like the ones provided.

Latest run results:

Run details: (Test run date: 2 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/107.0.0.0 Safari/537.36

Browser/OS: Chrome 107 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
float	761102336.0 Ops/sec
num	757569664.0 Ops/sec

Related benchmarks:

test float (version: 0)

Comparing performance of: float vs num

Created: 2 years ago by: Guest

Jump to the latest result

float

num

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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