Benchmark: Uint(8/16/32)Array and BigInt64Array comparison performance

Script Preparation code:

var size = 8 * 40;
var srcBuf8 = new ArrayBuffer(size);
var srcBufPtr8 = new Uint8Array(srcBuf8);
var srcBuf16 = new ArrayBuffer(size*2);
var srcBufPtr16 = new Uint16Array(srcBuf16);
var srcBuf32 = new ArrayBuffer(size*4);
var srcBufPtr32 = new Uint32Array(srcBuf32);
var srcBuf64 = new ArrayBuffer(size*8);
var srcBufPtr64 = new BigUint64Array(srcBuf64);

for (let i = 0; i < size; i++) {
    srcBufPtr8[i] = 100 * Math.random();
}
for (let i = 0; i < size; i++) {
    srcBufPtr16[i] = srcBufPtr8[i];
}
for (let i = 0; i < size; i++) {
    srcBufPtr32[i] = srcBufPtr8[i];
}
for (let i = 0; i < size; i++) {
    srcBufPtr64[i] = BigInt(srcBufPtr8[i]);
}

Tests:

Uint8Array increment
let smallerCount = 0; for (let i = 0; i < (size-1); i++) { if (srcBufPtr8[i] < srcBufPtr8[i+1]) { smallerCount++; } }
Uint16Array increment
let smallerCount = 0; for (let i = 0; i < (size-1); i++) { if (srcBufPtr16[i] < srcBufPtr16[i+1]) { smallerCount++; } }
Uint32Array increment
let smallerCount = 0; for (let i = 0; i < (size-1); i++) { if (srcBufPtr32[i] < srcBufPtr32[i+1]) { smallerCount++; } }
BigUint64Array increment
let smallerCount = 0; for (let i = 0; i < (size-1); i++) { if (srcBufPtr64[i] < srcBufPtr64[i+1]) { smallerCount++; } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Uint8Array increment
Uint16Array increment
Uint32Array increment
BigUint64Array increment

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/134.0.0.0 Safari/537.36

Browser/OS: Chrome 134 on Windows

View result in a separate tab

Test name	Executions per second
Uint8Array increment	1072470.4 Ops/sec
Uint16Array increment	1062807.2 Ops/sec
Uint32Array increment	1066712.8 Ops/sec
BigUint64Array increment	925765.9 Ops/sec

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):

LLMs can make mistakes. Check important info.

Measuring performance and optimization in JavaScript can be a complex task, especially when it comes to comparing different data structures like arrays and Big arrays.

**Benchmark Definition**

The provided benchmark is designed to compare the performance of increment operations on different array types: Uint8Array, Uint16Array, Uint32Array, and BigUint64Array. The test case generates an array of a fixed size (40 elements), populates it with random values, and then iterates over the array, checking if each value is less than the next one.

**Options Compared**

The benchmark compares the performance of four options:

1. **Uint8Array increment**: Increment operation on a Uint8Array.
2. **Uint16Array increment**: Increment operation on a Uint16Array.
3. **Uint32Array increment**: Increment operation on a Uint32Array.
4. **BigUint64Array increment**: Increment operation on a BigUint64Array.

**Pros and Cons of Each Approach**

1. **Uint8Array increment**:
	* Pros: Typically the fastest option due to the smallest size and limited range of values (0-255).
	* Cons: May lead to precision issues when dealing with large numbers or high-precision calculations.
2. **Uint16Array increment**:
	* Pros: Balances speed and accuracy, suitable for most numerical computations.
	* Cons: May be slower than Uint8Array due to the larger size and more values to compare.
3. **Uint32Array increment**:
	* Pros: Offers better performance and precision than Uint16Array, making it a good choice for high-precision calculations.
	* Cons: Can lead to overflow issues if dealing with very large numbers or negative values.
4. **BigUint64Array increment**:
	* Pros: Provides the highest level of precision and accuracy, suitable for extreme numerical computations.
	* Cons: Typically the slowest option due to the massive size and range of values.

**Other Considerations**

When working with arrays in JavaScript, it's essential to consider factors like:

* **Data type**: Choose an array type that aligns with your data requirements (e.g., using BigInt for very large or high-precision numbers).
* **Array size**: Be mindful of the array size and how it affects performance. Large arrays can lead to slower computations.
* **Iteration order**: The order in which you iterate over the array can impact performance, especially if dealing with specific data structures like Big arrays.

**Library Used**

The benchmark uses the `BigInt` function, introduced in ECMAScript 2020, for handling very large integers. This library provides a way to represent and manipulate arbitrarily-precision integers.

**Special JS Feature/Syntax**

No special JavaScript features or syntax are used in this benchmark aside from the `BigInt` function mentioned earlier.

Other alternatives to these array types include:

* **Float32Array**: A 32-bit floating-point array, suitable for numerical computations that require higher precision than integers.
* **Float64Array**: A 64-bit floating-point array, offering better performance and accuracy than Float32Array for very large or high-precision numbers.

Keep in mind that the choice of array type ultimately depends on your specific requirements and use case.

Related benchmarks:

Uint(8/16/32)Array and BigInt64Array comparison performance (version: 0)

Uint(8/16/32)Array and BigInt64Array comparison performance

Comparing performance of: Uint8Array increment vs Uint16Array increment vs Uint32Array increment vs BigUint64Array increment

Created: one year ago by: Guest

Jump to the latest result

Uint8Array increment

Uint16Array increment

Uint32Array increment

BigUint64Array increment

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 6 months ago):