Benchmark: Float32 vs Float64 vs Array only iterate1e5

Script Preparation code:

var length = 1e5;

var f32_a = Float32Array.from({length}, Math.random);
var f32_b = Float32Array.from({length}, Math.random);

var f64_a = Float64Array.from({length}, Math.random);
var f64_b = Float64Array.from({length}, Math.random);

var arr_a = Array.from({length}, Math.random);
var arr_b = Array.from({length}, Math.random);

Tests:

iterate and set f32
for (let i = 0; i < length; i++) { f32_a[i] = f32_b[i]; }
iterate and set f64
for (let i = 0; i < length; i++) { f64_a[i] = f64_b[i]; }
iterate and set array
for (let i = 0; i < length; i++) { arr_a[i] = arr_b[i]; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
iterate and set f32
iterate and set f64
iterate and set array

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 12 days ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/135.0.0.0 Safari/537.36

Browser/OS: Chrome 135 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
iterate and set f32	3295.7 Ops/sec
iterate and set f64	3232.3 Ops/sec
iterate and set array	3532.7 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated 12 days ago):

LLMs can make mistakes. Check important info.

The benchmark represented in the provided JSON tests the performance of different data types during iteration and assignment operations in JavaScript. Specifically, it compares the performance of `Float32Array`, `Float64Array`, and standard JavaScript arrays when performing the same iterative operation—assigning values from one array to another.

### Options Compared

1. **Float32Array**
   - **Operation:** `for (let i = 0; i < length; i++) { f32_a[i] = f32_b[i]; }`
   - **Pros:** 
      - Uses less memory (32 bits per value) compared to Float64.
      - Can be faster for certain applications that do not require the higher precision.
   - **Cons:** 
      - Limited precision can lead to rounding errors in calculations that require high precision.
  
2. **Float64Array**
   - **Operation:** `for (let i = 0; i < length; i++) { f64_a[i] = f64_b[i]; }`
   - **Pros:** 
      - Accurate representation of floating-point numbers with higher precision (64 bits).
      - Can handle a larger range of values.
   - **Cons:** 
      - Consumes more memory (64 bits per value).
      - Potentially slower in operations compared to Float32Array, especially when processing large amounts of data that do not require extreme precision.
  
3. **Standard Array**
   - **Operation:** `for (let i = 0; i < length; i++) { arr_a[i] = arr_b[i]; }`
   - **Pros:** 
      - Flexible and automatically handles various types of data.
      - Built-in support for diverse data manipulations and higher-level operations.
   - **Cons:** 
      - Generally slower than Typed Arrays (Float32Array and Float64Array) for numerical computations and more memory overhead due to dynamic sizing.
      - Performance suffers due to the absence of specialized optimizations that exist for Typed Arrays.

### Comparison of Results

From the benchmark results, we observe the following execution rates:
- **Standard Array**: 3532.74 executions per second (fastest)
- **Float32Array**: 3295.71 executions per second
- **Float64Array**: 3232.30 executions per second (slowest)

This indicates that the standard JavaScript array iteration performed better in this specific benchmark scenario, which can be counterintuitive but could be attributed to optimizations in the JavaScript engine for array handling. In typical use cases, one might expect that Typed Arrays would fare better due to their reduced memory footprint and specialized handling. However, the overhead of access and assignment patterns in this benchmark may have favored standard arrays in performance.

### Considerations

- The results could vary based on the JavaScript engine implementation (e.g., V8 for Chrome vs. SpiderMonkey for Firefox) and the specific environment in which the code is run.
- While the benchmark focuses primarily on iteration and assignment, actual performance benefits of Typed Arrays may be more pronounced in mathematical computations or large data processing tasks where their efficiency in memory and performance differences become critical.

### Alternatives

Other alternatives for handling numeric arrays in JavaScript could include:
- **Typed Arrays**: Beyond Float32Array and Float64Array, other Typed Arrays like Int32Array or Uint8Array could be tested for different use cases.
- **Array Buffers**: A low-level representation of binary data, often used in conjunction with Typed Arrays for efficient data manipulation.
- **Libraries**: Libraries like [math.js](https://mathjs.org/) or [numjs](https://numjs.org/) that provide numerical operations and matrix manipulations with optimizations, allowing for potentially more efficient handling of large datasets.

Each of these alternatives comes with its own set of advantages and trade-offs based on precision, performance, and ease of use.

Related benchmarks:

Float32 vs Float64 vs Array only iterate1e5 (version: 1)

Comparing performance of: iterate and set f32 vs iterate and set f64 vs iterate and set array

Created: 12 days ago by: Guest

Jump to the latest result

iterate and set f32

iterate and set f64

iterate and set array

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated 12 days ago):