Benchmark: for loop array caching with mutations

Script Preparation code:

var arr = Array.from({length: 10000}, (_, i) => String.fromCharCode(i + 97));

Tests:

mutate without length caching
for (let i = 0; i < arr.length; i++) { arr[i] = "(" + arr[i] + ")"; }
mutate with length caching
for (let i = 0, l = arr.length; i < l; i++) { arr[i] = "(" + arr[i] + ")"; }
separate array without length caching
const arr1 = []; for (let i = 0; i < arr.length; i++) { arr1[i] = "(" + arr[i] + ")"; } arr = arr1;
separate array with length caching
const arr1 = []; for (let i = 0, l = arr.length; i < l; i++) { arr1[i] = "(" + arr[i] + ")"; } arr = arr1;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
mutate without length caching
mutate with length caching
separate array without length caching
separate array with length caching

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.66 Safari/537.36

Browser/OS: Chrome 87 on Windows

View result in a separate tab

Test name	Executions per second
mutate without length caching	153.9 Ops/sec
mutate with length caching	183.9 Ops/sec
separate array without length caching	180.1 Ops/sec
separate array with length caching	267.7 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its test cases.

**Benchmark Description**

The benchmark tests how fast different approaches are to update an array of strings in JavaScript. The goal is to understand which approach is faster, considering factors such as cache usage, loop optimization, and potential overhead from using a separate array for mutation.

**Options Compared**

There are four test cases:

1. **Mutate without length caching**: This approach updates the original `arr` array directly within the loop.
2. **Mutate with length caching**: In this approach, a temporary variable `l` is used to store the length of the array before each iteration, reducing cache misses and potentially improving performance.
3. **Separate array without length caching**: A separate array `arr1` is created for mutation purposes, which can help isolate the updates from other parts of the code. However, this approach may incur additional overhead due to memory allocation and copying.
4. **Separate array with length caching**: Similar to the previous approach, a separate array `arr1` is used for mutation, but with the added benefit of caching the length variable.

**Pros and Cons**

Here's a brief summary of each approach:

* **Mutate without length caching**: This approach is simple and doesn't require additional variables or memory allocation. However, it may lead to more cache misses due to updates within the loop.
	+ Pros: Easy to implement, no extra memory allocation required
	+ Cons: Potential for increased cache misses
* **Mutate with length caching**: By caching the array length, this approach reduces cache misses and can improve performance. However, it still requires an additional variable (`l`) and may incur some overhead due to its use.
	+ Pros: Reduces cache misses, improved performance
	+ Cons: Additional memory allocation required for `l`
* **Separate array without length caching**: This approach provides isolation from other parts of the code but incurs extra memory allocation and copying costs. However, it may help reduce side effects and improve predictability.
	+ Pros: Improved isolation, reduced side effects
	+ Cons: Additional memory allocation required, copying overhead
* **Separate array with length caching**: This approach combines the benefits of separate arrays with the cache optimization provided by `l`.
	+ Pros: Reduces cache misses, improved performance, and isolation
	+ Cons: Additional memory allocation required for `arr1` and `l`

**Other Considerations**

* Memory safety: The benchmark doesn't explicitly test memory safety aspects like null pointer exceptions or buffer overflows.
* Browser differences: The results may vary across different browsers due to their rendering engines and performance characteristics.

**Library/Functionality Used (None)**

There is no explicit library or functionality used in the provided benchmark. However, it's worth noting that some JavaScript engines might optimize certain approaches using internal libraries or compiler optimizations.

**Special JS Feature/Syntax (None)**

This benchmark doesn't utilize any special JavaScript features or syntax, sticking to standard language constructs and basic arithmetic operations.

Overall, the benchmark provides a good starting point for exploring performance optimization techniques in JavaScript array updates. By understanding the trade-offs between different approaches, developers can make informed decisions about which optimizations to apply depending on their specific use cases and constraints.

Related benchmarks:

for loop array caching with mutations (version: 0)

Comparing performance of: mutate without length caching vs mutate with length caching vs separate array without length caching vs separate array with length caching

Created: 4 years ago by: Guest

Jump to the latest result

mutate without length caching

mutate with length caching

separate array without length caching

separate array with length caching

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):