Benchmark: divide by 2 vs multiply by 0.5 (fork @nebrob_)

Script Preparation code:

const length = 500000;
const tmp_nums=[];
for (let i = 0; i < length; i++) {
  tmp_nums.push(Date.now() + Math.random());
}
nums = [...tmp_nums];
nums_len = length;

Tests:

div by 2
const length = nums_len; for (let i = 0; i < length; i++) { nums[i] /= 2; }
div by 2.0
const length = nums_len; for (let i = 0; i < length; i++) { nums[i] /= 2.0; }
multiply by 0.5
const length = nums_len; for (let i = 0; i < length; i++) { nums[i] *= 0.5; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
div by 2
div by 2.0
multiply by 0.5

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/131.0.0.0 Safari/537.36 Edg/131.0.0.0

Browser/OS: Chrome 131 on Windows

View result in a separate tab

Test name	Executions per second
div by 2	1192.1 Ops/sec
div by 2.0	1147.4 Ops/sec
multiply by 0.5	1039.8 Ops/sec

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

LLMs can make mistakes. Check important info.

I'd be happy to explain the provided benchmark and its options.

**Benchmark Overview**

The provided benchmark is designed to measure the performance of dividing numbers by 2 versus multiplying numbers by 0.5. The test generates an array of random numbers, performs either division or multiplication on the numbers, and measures how many executions per second are performed by a Chrome browser.

**Script Preparation Code**

The script preparation code initializes variables:

* `length`: sets the length of the generated array
* `tmp_nums`: creates an array of random dates (in milliseconds) with the specified length
* `nums` and `nums_len`: copy the contents of `tmp_nums` to a new array `nums`, and store its length in `nums_len`

**Html Preparation Code**

There is no HTML preparation code provided, which suggests that this benchmark focuses solely on JavaScript performance.

**Individual Test Cases**

There are three test cases:

1. **"div by 2"`**: This test case performs division on the array elements using the `/` operator.
2. **"div by 2.0"`**: This test case is similar to the first one, but uses `2.0` instead of `2` for the division operation.
3. **"multiply by 0.5"`**: This test case performs multiplication on the array elements using the `*` operator with a fixed value of `0.5`.

**Options Compared**

The three test cases compare:

1. Using the `/` operator (division by 2)
2. Using `2.0` instead of the `/` operator for division by 2
3. Using the `*` operator with a fixed value of `0.5` for multiplication

**Pros and Cons**

Here are some pros and cons of each approach:

1. **Division using `/` (Test Case "div by 2")**:
	* Pros: Simple, intuitive, widely supported.
	* Cons: May be slower due to the overhead of floating-point operations.
2. **Division using `2.0` (Test Case "div by 2.0")**:
	* Pros: Could potentially be faster due to the use of a constant value, which might avoid some rounding or overflow issues associated with floating-point operations.
	* Cons: May not work correctly for certain edge cases (e.g., `NaN` or `Infinity`) and is less intuitive than using `/`.
3. **Multiplication by `0.5` (Test Case "multiply by 0.5")**:
	* Pros: Could potentially be faster due to the use of a constant value, similar to the `2.0` division case.
	* Cons: May not be as intuitive or widely supported as other operations.

**Library and Special Features**

There are no libraries mentioned in the benchmark definition, but some browsers (like Chrome) may have built-in optimizations for certain arithmetic operations.

**Other Considerations**

The benchmark uses a fixed array length of 500,000 elements, which might not be representative of real-world scenarios where data sizes can vary greatly. Additionally, the use of random dates as numbers might introduce some noise in the results.

**Alternative Approaches**

Some alternative approaches to measuring arithmetic performance could include:

1. Using larger or smaller dataset sizes
2. Using different types of numbers (e.g., integers, floating-point numbers)
3. Measuring performance using different algorithms or techniques (e.g., SIMD instructions, parallel processing)
4. Comparing performance across multiple browsers or architectures

Related benchmarks:

divide by 2 vs multiply by 0.5 (fork @nebrob_) (version: 0)

Comparing performance of: div by 2 vs div by 2.0 vs multiply by 0.5

Created: 2 years ago by: Guest

Jump to the latest result

div by 2

div by 2.0

multiply by 0.5

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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