Benchmark: lambdas-noinline-fun-creation2

Script Preparation code:

var x = [];
for(i=0; i<1000; i++){
	x.push(i)
}
function justReturn(item) { return item }
function sideEffect2(arr, i) { arr[i] = x[i] }

Tests:

lambda (created each time)
let a1 = []; function justReturn2(item) { return item } for(i=0; i<1000; i++){ a1[i] = justReturn2(x[i]) }
lambda (created once)
let a2 = []; for(i=0; i<1000; i++){ a2[i] = justReturn(x[i]) }
lambda (side-effect inline)
let a3 = []; function sideEffect2(i) { a3[i] = x[i] } for(i=0; i<1000; i++){ sideEffect2(i) }
lambda (side-effect)
let a4 = []; for(i=0; i<1000; i++){ sideEffect(i) }
no lambda
let a5 = []; for(i=0; i<1000; i++){ a5[i] = x[i] }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
lambda (created each time)
lambda (created once)
lambda (side-effect inline)
lambda (side-effect)
no lambda

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/89.0.4389.90 Safari/537.36

Browser/OS: Chrome 89 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
lambda (created each time)	13071.5 Ops/sec
lambda (created once)	7207.6 Ops/sec
lambda (side-effect inline)	11335.9 Ops/sec
lambda (side-effect)	0.0 Ops/sec
no lambda	13809.2 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks on MeasureThat.net.

**Benchmark Definition**

The provided JSON represents a benchmark definition, which outlines the test case being measured. The key elements are:

* `Name`: A unique identifier for the benchmark (in this case, "lambdas-noinline-fun-creation2").
* `Description`: An optional description of the benchmark, which is empty in this case.
* `Script Preparation Code`: A JavaScript code snippet that sets up the test environment. In this case, it creates an array `x` with 1000 elements and defines two functions: `justReturn` and `sideEffect2`. The latter function has a side effect (modifying the array) that will be used in subsequent test cases.
* `Html Preparation Code`: An optional HTML code snippet that prepares the test environment, which is empty in this case.

**Individual Test Cases**

The JSON also contains an array of individual test cases, each with its own benchmark definition. The key elements are:

* `Benchmark Definition`: A JavaScript code snippet that defines the specific test case being measured.
* `Test Name`: A descriptive name for the test case (e.g., "lambda (created each time)").
* Other fields contain metadata, such as browser type and device platform.

The test cases can be summarized as follows:

1. `lambda (created each time)`:
	* Creates a new function on each iteration of the loop using `justReturn`.
2. `lambda (created once)`:
	* Creates a single function instance for the entire loop, which is reused.
3. `lambda (side-effect inline)`:
	* Uses the `sideEffect2` function with its side effect applied inline to the array elements.
4. `lambda (side-effect)`:
	* Calls the `sideEffect2` function without applying its side effect, effectively ignoring it.
5. `no lambda`:
	* Modifies the original array using a simple loop.

**Options Compared**

The benchmark tests different approaches to creating and executing functions in JavaScript:

1. Creating a new function on each iteration (`lambda (created each time)`).
2. Creating a single function instance for the entire loop (`lambda (created once)`).
3. Using the `sideEffect` function with its side effect applied inline (`lambda (side-effect inline)`).
4. Calling the `sideEffect` function without applying its side effect (`lambda (side-effect)`).
5. Modifying the original array using a simple loop (`no lambda`).

**Pros and Cons**

Here are some pros and cons of each approach:

1. Creating a new function on each iteration:
	* Pros: Can improve performance by avoiding unnecessary overhead.
	* Cons: May lead to increased memory usage due to multiple function objects.
2. Creating a single function instance for the entire loop:
	* Pros: Can reduce memory usage and improve cache locality.
	* Cons: May introduce significant performance overhead due to repeated function calls.
3. Using the `sideEffect` function with its side effect applied inline:
	* Pros: Can simplify code and improve readability.
	* Cons: May lead to increased execution time due to the side effect.
4. Calling the `sideEffect` function without applying its side effect:
	* Pros: Avoids the performance overhead of the side effect.
	* Cons: May lead to reduced performance gains compared to other approaches.
5. Modifying the original array using a simple loop:
	* Pros: Can be more straightforward and efficient than other approaches.
	* Cons: May not be suitable for large datasets or complex operations.

**Other Considerations**

When interpreting the benchmark results, consider the following factors:

1. **Browser and device variations**: The benchmark may not always produce consistent results across different browsers and devices due to various optimization strategies and caching mechanisms.
2. **Loop unrolling and iteration order**: The loop unrolling strategy used in the benchmark may not be optimal for all scenarios, leading to potential performance differences.
3. **Function call overhead**: The frequency of function calls can significantly impact performance, especially when dealing with loops or recursive functions.

**Alternatives**

If you're interested in exploring alternative approaches or optimizing your JavaScript code, consider the following options:

1. **Use a Just-In-Time (JIT) compiler**: Tools like V8 or SpiderMonkey can optimize your JavaScript code for better performance.
2. **Explore async/await and generators**: These features can simplify your code and improve performance by reducing function call overhead.
3. **Use array methods and built-in functions**: Native array methods like `map()`, `filter()`, and `reduce()` can be more efficient than custom loops or functions.
4. **Profile your code with a profiling tool**: Instruments like Chrome DevTools or Node.js Inspector can help you identify performance bottlenecks in your code.

By understanding the different approaches and factors influencing JavaScript performance, you can make informed decisions about optimizing your code for better execution times.

Related benchmarks:

lambdas-noinline-fun-creation2 (version: 0)

Comparing performance of: lambda (created each time) vs lambda (created once) vs lambda (side-effect inline) vs lambda (side-effect) vs no lambda

Created: 3 years ago by: Guest

Jump to the latest result

lambda (created each time)

lambda (created once)

lambda (side-effect inline)

lambda (side-effect)

no lambda

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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