Benchmark: Access Float64Array

Script Preparation code:

var ta = (new Float64Array(10000)).map(_ => Math.random());

Tests:

i
for (let i = 0; i < 10000; ++i) { const t = ta[i]; }
i/o
for (let i = 0; i < 10000; ++i) ta[i] = ta[i] + 1;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
i
i/o

Fastest: N/A

Slowest: N/A

Latest run results:

No previous 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.

**Benchmark Definition**

The benchmark definition is represented as JSON, which describes two test cases:

1. **Access Float64Array**: This test case measures the time it takes to access an element in a `Float64Array`. The script preparation code creates a 10,000-element `Float64Array` filled with random values using `Math.random()`.
2. **i/o (Indexing and Overwriting)**: This test case measures the time it takes to iterate over the elements of the same `Float64Array`, both indexing and overwriting each element.

**Script Preparation Code**

The script preparation code is a JavaScript snippet that creates a 10,000-element `Float64Array` using the `Float64Array` constructor. The array is then mapped to create an array of random values.

```javascript
var ta = (new Float64Array(10000)).map(_ => Math.random());
```

**Html Preparation Code**

There is no HTML preparation code provided, which means that the benchmark does not rely on any specific DOM elements or interactions.

**Test Cases**

The two test cases are:

1. **`i`**: This test case measures the time it takes to access a single element in the `Float64Array`. The benchmark definition is:
```javascript
for (let i = 0; i < 10000; ++i) {
  const t = ta[i];
}
```
This test case only accesses each element of the array once.

2. **`i/o`**: This test case measures the time it takes to iterate over all elements in the `Float64Array`, both indexing and overwriting each element. The benchmark definition is:
```javascript
for (let i = 0; i < 10000; ++i)
  ta[i] = ta[i] + 1;
```
This test case iterates over the array twice: once to access each element, and again to modify each element.

**Pros and Cons of Different Approaches**

1. **Accessing a single element**: This approach is simple and can provide insights into the performance of accessing individual elements in an array.
	* Pros: easy to implement, provides insight into individual element access.
	* Cons: may not accurately represent real-world scenarios where arrays are used extensively.
2. **Indexing and Overwriting**: This approach simulates more realistic usage patterns, as it iterates over the entire array twice.
	* Pros: provides a more accurate representation of real-world usage patterns.
	* Cons: more complex to implement, may require additional overhead due to repeated iterations.

**Library and Purpose**

The `Float64Array` constructor is a built-in JavaScript library that creates a typed array with 64-bit floating-point numbers. The purpose of this constructor is to provide an efficient way to work with large arrays of floating-point numbers in JavaScript.

**Special JS Feature or Syntax**

There are no special features or syntax mentioned in the benchmark definition or test cases.

**Alternatives**

Other alternatives for measuring performance in JavaScript include:

1. **Benchmarking libraries**: Libraries like Benchmark.js, jsperf, or Perfometer provide a more structured approach to benchmarking.
2. **V8 Profiler**: The V8 Profiler is a built-in tool for profiling and optimizing JavaScript performance.
3. **WebAssembly**: WebAssembly provides a platform-agnostic way to measure performance in JavaScript.

Keep in mind that each alternative has its own strengths and weaknesses, and the choice of which one to use depends on the specific use case and requirements.

Related benchmarks:

Access Float64Array (version: 0)

Comparing performance of: i vs i/o

Created: 3 years ago by: Guest

Jump to the latest result

i

i/o

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):