Benchmark: read write ArrayBuffer: DataView vs Float64Array.set

Script Preparation code:

var size = 50000;
var buf = new ArrayBuffer(size*8);
var view = new DataView(buf);
var data = new Float64Array(size);

Tests:

DataView
for (let i=0; i < size; i++) { view.setFloat64(i*8, 992.2258); } for (let i=0; i < size; i++) { const res = view.getFloat64(i*8); }
Float64Array
for (let i=0; i < size; i++) { data[i] = 992.2258; } for (let i=0; i < size; i++) { const res = data[i]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
DataView
Float64Array

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases to understand what's being tested.

**What is being tested?**

The provided benchmark measures the performance difference between two approaches for setting values in an ArrayBuffer using either a DataView or a Float64Array.

In more detail, the tests involve:

1. Creating a large ArrayBuffer (50000 bytes) and a new DataView that views this buffer.
2. Iterating over the array and setting float64 values into the DataView using `setFloat64()` method.
3. Iterating over the same range and accessing these previously set values from the DataView using `toFloat64()` method.

The second test case is similar, but instead of using a DataView, it uses a Float64Array directly to store and access the values.

**Options compared**

Two main options are being compared:

1. **DataView**: A typed array that provides a buffer view into a binary ArrayBuffer. It allows for more fine-grained control over memory management and data type conversion.
2. **Float64Array**: A type of Typed Array that stores 64-bit floating-point numbers in an ArrayBuffer.

**Pros and Cons**

* **DataView**:
	+ Pros:
		- More flexible and powerful, allowing for arbitrary data type conversions and manipulation.
		- Can be used to access raw binary data in the ArrayBuffer.
	+ Cons:
		- More complex and harder to use due to its advanced features.
		- May introduce overhead due to additional operations required for data type conversion.
* **Float64Array**:
	+ Pros:
		- Simpler and easier to use, as it's a specialized array for floating-point numbers.
		- Often preferred when working with numerical computations or scientific simulations.
	+ Cons:
		- Limited flexibility and customization options compared to DataView.

**Library**

None of the provided test cases rely on any external libraries. However, it's worth noting that DataView is an inherent feature of the JavaScript language and doesn't require additional library imports.

**Special JS features/syntax**

The tests do not utilize any special JavaScript features or syntax beyond what's described above (e.g., no async/await, no promises).

**Other alternatives**

Other alternatives for setting values in an ArrayBuffer could include:

1. Using a Uint8Array and manual buffer manipulation.
2. Utilizing other typed arrays like Int32Array, Float32Array, etc.
3. Employing third-party libraries that provide optimized or specialized buffer management functionality.

However, these alternatives are not tested in the provided benchmark definition.

In summary, this benchmark compares two approaches for setting values in an ArrayBuffer: using a DataView and using a Float64Array directly. The tests evaluate the performance difference between these two methods, considering factors like data type conversion overhead and simplicity of usage.

Related benchmarks:

read write ArrayBuffer: DataView vs Float64Array.set (version: 0)

Comparing performance of: DataView vs Float64Array

Created: 4 years ago by: Guest

Jump to the latest result

DataView

Float64Array

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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