Benchmark: read write ArrayBuffer: DataView vs Float64Array.set v2

Script Preparation code:

var size = 50000;
var buf = new ArrayBuffer(size*8);
var view = new DataView(buf);
var buf2 = new ArrayBuffer(size*4);
var view2 = new DataView(buf2);
var data = new Float64Array(size);
var data2 = new Float32Array(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]; }
Float32Array
for (let i=0; i < size; i++) { data[i] = 992.2258; } for (let i=0; i < size; i++) { const res = data[i]; }
DataView 32
for (let i=0; i < size; i++) { view2.setFloat32(i*4, 992.2258); } for (let i=0; i < size; i++) { const res = view2.getFloat32(i*4); }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
DataView
Float64Array
Float32Array
DataView 32

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/148.0.0.0 Safari/537.36

Browser/OS: Chrome 148 on Windows

View result in a separate tab

Float64Array

715/s

Float32Array

715/s

DataView

431/s

DataView 32

412/s

View exact numbers

Test name	Executions per second
✓ Float64Array	715 Ops/sec
Float32Array	715 Ops/sec
DataView	431 Ops/sec
DataView 32	412 Ops/sec

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 and explain what's being tested.

**Benchmark Overview**

The benchmark compares the performance of four approaches:

1. `Float64Array.set` (using `DataView`)
2. Direct assignment to an array (`Float64Array` or `Float32Array`)
3. Using a `DataView` with 32-bit floating-point numbers (i.e., `Float32Array`)

**What's being tested**

The benchmark is testing the performance of writing and reading data from arrays using different approaches.

1. The first test case uses `DataView.set` to write data to an array, and then reads it back using `DataView.getFloat64`.
2. The second test case directly assigns values to a `Float64Array`, which becomes the source for the read operation.
3. The third test case is similar to the second one but uses a `DataView` with 32-bit floating-point numbers (`Float32Array`) instead of 64-bit.

**Options comparison**

Here's a brief overview of each option and their pros and cons:

1. **Direct assignment**: This approach is straightforward and easy to understand. However, it may incur additional overhead due to the language's garbage collection mechanism.
	* Pros: Easy to implement, no additional libraries required.
	* Cons: May incur performance overhead due to garbage collection.
2. **DataView.set** (using `DataView`): This approach uses a `DataView` object to write data to an array. It provides more control over memory management and can be faster than direct assignment.
	* Pros: Can be faster, provides better memory management control.
	* Cons: Requires understanding of `DataView` and its usage.
3. **Direct assignment (32-bit float)**: This approach uses a `Float32Array`, which reduces memory usage compared to using a `Float64Array`. However, it may incur additional overhead due to the difference in data types.
	* Pros: Reduced memory usage, potentially faster due to reduced memory access patterns.
	* Cons: May incur performance overhead due to type conversion.

**Library**

In this benchmark, no explicit library is mentioned. However, it's worth noting that `DataView` and array operations are part of the standard JavaScript API.

**Special JS feature or syntax**

There's no special JavaScript feature or syntax being used in this benchmark. The tests only involve basic arithmetic operations and array manipulation.

**Alternative approaches**

Other alternatives to consider when working with arrays and memory management include:

* Using typed arrays (e.g., `Int32Array`, `Uint8Array`) for specific use cases.
* Utilizing WebAssembly (WASM) for performance-critical code that requires direct memory access.
* Employing libraries like WebAssembly's `wasm-bindgen` or JavaScript libraries like `fastify` or `express` for high-performance networking.

In summary, this benchmark compares the performance of different approaches to writing and reading data from arrays using JavaScript. The results can help developers understand the trade-offs between direct assignment, `DataView`, and 32-bit floating-point numbers when working with memory management in JavaScript.

read write ArrayBuffer: DataView vs Float64Array.set v2 (version: 0)

Comparing performance of: `DataView vs Float64Array vs Float32Array vs DataView 32`

Created: 2 years ago by: Guest

Go to the latest result

DataView

Float64Array

Float32Array

DataView 32

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

read write ArrayBuffer: DataView vs Float64Array.set v2 (version: 0)

Comparing performance of: DataView vs Float64Array vs Float32Array vs DataView 32

Created: 2 years ago by: Guest

Go to the latest result

DataView

Float64Array

Float32Array

DataView 32

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

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

Related benchmarks

Comparing performance of: `DataView vs Float64Array vs Float32Array vs DataView 32`