Benchmark: floor() vs trunc() vs bitwise hacks (~~, >> 0, etc) 2

Script Preparation code:

var x = Math.random() * 100000000;
var y;

Tests:

modulus
y = x % 2;
bitwise
y = x & 1;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
modulus
bitwise

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 10 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:140.0) Gecko/20100101 Firefox/140.0

Browser/OS: Firefox 140 on Linux

View result in a separate tab

Test name	Executions per second
modulus	1149839104.0 Ops/sec
bitwise	1068376512.0 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**What is being tested?**

The test is designed to compare the performance of three different approaches to achieve the same result: calculating the remainder of an integer division operation:

1. `Math.floor()`
2. `Math.trunc()`
3. Bitwise hacks using `~~` (two's complement), `>> 0`, and other techniques.

**Options being compared**

The test is comparing the performance of these three approaches for two individual test cases:

* "modulus": `y = x % 2;`
* "bitwise": `y = x & 1;`

In each test case, the script preparation code generates a random integer `x` and then calculates the result using one of the three approaches.

**Pros and Cons**

Here's a brief analysis of each approach:

1. **Math.floor()**: This is a built-in JavaScript function that returns the largest integer less than or equal to the input value. It's a straightforward and efficient way to calculate remainders, but it may not be optimized for specific platforms.
	* Pros: Easy to implement, well-supported by browsers.
	* Cons: May not be the fastest option due to its overhead.
2. **Math.trunc()**: This is another built-in JavaScript function that returns the integer part of a number. It's similar to `floor()` but can return negative values if necessary.
	* Pros: Similar performance characteristics to `floor()`, and may be faster in some cases.
	* Cons: May not work as expected for large integers due to its rounding behavior.
3. **Bitwise hacks**: These are low-level optimizations that use bitwise operations to achieve the desired result without using the built-in `Math` functions.
	* Pros: Can potentially be very fast and efficient, especially on platforms where arithmetic instructions are optimized.
	* Cons: Require a good understanding of binary arithmetic and may not work across all browsers.

**Other considerations**

The test also measures the performance of Firefox 83 on Linux desktops. This means that any differences in performance between approaches may be due to platform-specific optimizations or browser-specific behavior.

**Library and special JS features**

None of the test cases use any external libraries, but they do rely on the following special JavaScript features:

* `Math.random()`: a built-in function for generating random numbers.
* Arithmetic operators (`%`, `&`): built-in operators that perform integer division and bitwise operations, respectively.

**Alternatives**

If you want to compare the performance of other approaches or test different scenarios, here are some alternatives to explore:

* Use different browsers, such as Chrome, Safari, or Edge, to see if there's a difference in performance.
* Test with larger input values to stress the arithmetic capabilities of each approach.
* Experiment with different bitwise hack optimizations (e.g., using `x & 0xFF` instead of `x & 1`) to see if you can find faster alternatives.
* Investigate other built-in JavaScript functions, such as `Math.abs()` or `Number.isInteger()`, that might be relevant for this type of calculation.

Related benchmarks:

floor() vs trunc() vs bitwise hacks (~~, >> 0, etc) 2 (version: 0)

Comparing performance of: modulus vs bitwise

Created: 5 years ago by: Guest

Jump to the latest result

modulus

bitwise

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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