Benchmark: Loop Times - MeasureThat.net

Script Preparation code:

var k=0;

Tests:

100 times
for (var i = 0; i < 100; i++) { k = k + k; }
10000 times
for (var i = 0; i < 1000000; i++) { k = k + k; }
10000000 times
for (var i = 0; i < 10000000; i++) { k = k + k; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
100 times
10000 times
10000000 times

Fastest: N/A

Slowest: N/A

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

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark definition and test cases to understand what is being tested.

**Benchmark Definition**

The benchmark definition is a JSON object that provides basic information about the benchmark. In this case, it has three properties:

* `Name`: The name of the benchmark, which is "Loop Times".
* `Description`: An optional description of the benchmark, which is null in this case.
* `Script Preparation Code` and `Html Preparation Code`: These are JavaScript code snippets that are executed before running each test case. In this case, they both contain a variable `k` initialized to 0.

**Test Cases**

The test cases are an array of objects, each representing a single test. Each object has two properties:

* `Benchmark Definition`: A string containing the actual benchmarking code, written in JavaScript.
* `Test Name`: The name of the test case.

In this case, there are three test cases:

1. A simple loop that increments `k` by itself 100 times.
2. A similar loop that increments `k` by itself 10,000 times.
3. Another loop that increments `k` by itself 10,000,000 times.

**Library Usage**

None of the benchmarking code uses any external libraries.

**Special JavaScript Features or Syntax**

There are no special JavaScript features or syntax being used in this benchmarking code.

**Options Compared**

The only option being compared is the loop size (100, 10,000, and 10,000,000) to measure their performance impact.

**Pros and Cons of Different Approaches**

* **Small Loop (100)**: This loop is likely to be the fastest due to its small size. However, it may not provide meaningful results for this benchmark.
* **Medium Loop (10,000)**: This loop is a good balance between speed and relevance. It should provide a reasonable estimate of the performance impact of increasing loop sizes.
* **Large Loop (10,000,000)**: This loop is likely to be the slowest due to its extremely large size. However, it may still provide useful insights into the performance characteristics of the benchmark.

**Other Considerations**

When interpreting these results, it's essential to consider the following factors:

* **Cache effects**: The size of the loop can impact cache behavior, which may affect performance.
* **Parallel execution**: If multiple cores are available, executing multiple loops in parallel could improve performance. However, this is not explicitly tested in this benchmark.
* **System load**: The number of executions per second may be affected by system load, such as other running processes or disk I/O.

**Alternatives**

Other alternatives for measuring loop performance might include:

* Using a different data structure, such as an array or a linked list, to see if it has a significant impact on performance.
* Introducing randomization or variation in the benchmarking code to simulate real-world scenarios.
* Measuring performance under different conditions, such as varying system loads or network latency.

By considering these alternatives and understanding the options being compared, you can gain a deeper insight into the performance characteristics of your JavaScript code.

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/90.0.4430.85 Safari/537.36

Browser/OS: Chrome 90 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
100 times	39426.3 Ops/sec
10000 times	4.2 Ops/sec
10000000 times	0.4 Ops/sec

Related benchmarks:

Loop Times (version: 6)

Comparing performance of: 100 times vs 10000 times vs 10000000 times

Created: 3 years ago by: Registered User

Jump to the latest result

100 times

10000 times

10000000 times

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

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