Benchmark: single for loop vs multiple for loops for iterating over arrays

Script Preparation code:

const smallN = 2 ** 10
const bigN = 2 ** 20

const arr1 = []
const arr2 = []

for (let i = 0; i < bigN; ++i) {
	arr1.push(Math.random())
	arr2.push(Math.random())
}

Tests:

single loop (big N)
for (let i = 0; i < bigN; ++i) { arr1[i] *= 2 arr2[i] *= 2 }
separate loops (big N)
for (let i = 0; i < bigN; ++i) arr1[i] *= 2 for (let i = 0; i < bigN; ++i) arr2[i] *= 2
single loop (small N)
for (let i = 0; i < smallN; ++i) { arr1[i] *= 2 arr2[i] *= 2 }
separate loops (small N)
for (let i = 0; i < smallN; ++i) arr1[i] *= 2 for (let i = 0; i < smallN; ++i) arr2[i] *= 2

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
single loop (big N)
separate loops (big N)
single loop (small N)
separate loops (small N)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 6 months ago)

User agent: Mozilla/5.0 (X11; Linux x86_64; rv:147.0) Gecko/20100101 Firefox/147.0

Browser/OS: Firefox 147 on Linux

View result in a separate tab

single loop (small N)

876K/s

separate loops (small N)

816K/s

single loop (big N)

725/s

separate loops (big N)

643/s

View exact numbers

Test name	Executions per second
✓ single loop (small N)	876,064 Ops/sec
separate loops (small N)	815,691 Ops/sec
single loop (big N)	725 Ops/sec
separate loops (big N)	643 Ops/sec

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

LLMs can make mistakes. Check important info.

This benchmark tests different approaches to iterating over arrays in JavaScript. Specifically, it compares the performance of using a single loop versus multiple separate loops for both small (2^10) and large (2^20) arrays.

### Option Comparisons

1. **Single Loop vs. Multiple Loops**
   - **Single Loop (big N)**:
     ```javascript
     for (let i = 0; i < bigN; ++i) {
         arr1[i] *= 2;
         arr2[i] *= 2;
     }
     ```
   - **Separate Loops (big N)**:
     ```javascript
     for (let i = 0; i < bigN; ++i) arr1[i] *= 2;
     for (let i = 0; i < bigN; ++i) arr2[i] *= 2;
     ```
   - **Single Loop (small N)**:
     ```javascript
     for (let i = 0; i < smallN; ++i) {
         arr1[i] *= 2;
         arr2[i] *= 2;
     }
     ```
   - **Separate Loops (small N)**:
     ```javascript
     for (let i = 0; i < smallN; ++i) arr1[i] *= 2;
     for (let i = 0; i < smallN; ++i) arr2[i] *= 2;
     ```

### Performance Results
- The results indicate that the single loop generally performs better than separate loops, especially for small arrays.
  - For small arrays, the single loop achieves about 345,163 executions per second, while the separate loops achieve about 260,841 executions per second.
  - For large arrays, although both approaches show a decline in performance (due to the increased workload), the single loop still outperforms the separate loops (322 executions vs. 280 executions per second).

### Pros and Cons of Different Approaches

**Single Loop:**
- **Pros**:
  - More efficient as it processes both arrays in one iteration, reducing the overhead of multiple loop constructs.
  - Better cache performance since it accesses memory less frequently.

- **Cons**:
  - Slightly less readable especially when operations within the loop become complex.

**Separate Loops:**
- **Pros**:
  - Can be clearer for certain scenarios, especially for small datasets where the operation might be subdivided logically in one’s mind.
  - Easier to modify each loop independently if the processing logic diverges.

- **Cons**:
  - Higher overhead due to the double iteration, resulting in poorer performance.
  - Increased memory access as it does not utilize caching as effectively.

### Other Considerations
- The choice between single and multiple loops can be influenced by factors such as code readability, maintainability, and specific use-case optimizations.
- The results can also vary based on the JavaScript engine's optimization capabilities. In some cases, the JavaScript engine might be able to optimize one approach over the other.

### Alternatives
Other alternatives to iterating over arrays in JavaScript include:
- **Array methods (e.g., `forEach`, `map`, `reduce`)**: These can improve readability and clarity but can incur additional overhead, especially for very large datasets.
- **Using typed arrays**: For numerical computations, typed arrays can provide performance enhancements due to their contiguous memory allocation and lower-level optimizations.
- **Parallel processing**: Utilizing Web Workers can offload heavy computations, allowing for a more responsive UI in web applications. However, this adds complexity in managing data between threads.

In conclusion, this benchmark provides a clear view of the performance differences when handling common JavaScript array operations and highlights the trade-offs between single and multi-loop constructs.

single for loop vs multiple for loops for iterating over arrays (version: 1)

Comparing performance of: `single loop (big N) vs separate loops (big N) vs single loop (small N) vs separate loops (small N)`

Created: one year ago by: Guest

Go to the latest result

single loop (big N)

separate loops (big N)

single loop (small N)

separate loops (small N)

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

single for loop vs multiple for loops for iterating over arrays (version: 1)

Comparing performance of: single loop (big N) vs separate loops (big N) vs single loop (small N) vs separate loops (small N)

Created: one year ago by: Guest

Go to the latest result

single loop (big N)

separate loops (big N)

single loop (small N)

separate loops (small N)

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model gpt-4o-mini, generated one year ago):

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Comparing performance of: `single loop (big N) vs separate loops (big N) vs single loop (small N) vs separate loops (small N)`