Benchmark: powoaetuheu - MeasureThat.net

Tests:

1.1**10
var x = Math.pow(1.1,10);
1.1**100
var x = Math.pow(1.1,100);
1.1**1000
var x = Math.pow(1.1,1000);
2**1000
var x = Math.pow(2,1000);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1.1**10
1.1**100
1.1**1000
2**1000

Fastest: N/A

Slowest: N/A

Latest run results:

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

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_15_7) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/87.0.4280.88 Safari/537.36

Browser/OS: Chrome 87 on Mac OS X 10.15.7

View result in a separate tab

Test name	Executions per second
1.1**10	8659655.0 Ops/sec
1.1**100	8498432.0 Ops/sec
1.1**1000	8430903.0 Ops/sec
2**1000	8231106.0 Ops/sec

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

LLMs can make mistakes. Check important info.

I'll do my best to explain the benchmark and its various components.

**Benchmark Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. A benchmark is a test designed to measure the performance of a piece of code or a specific aspect of it. In this case, we have a simple benchmark with four test cases that aim to evaluate the performance of exponentiation operations in JavaScript.

**Benchmark Definition**

The benchmark definition is represented by a JSON object that contains the following fields:

* `Name`: The name of the benchmark, which is "powoaetuheu".
* `Description`: An optional description field that is empty for this benchmark.
* `Script Preparation Code`: An optional code field that is also empty for this benchmark. This field would typically contain setup code that is executed before running the actual benchmark, but it's absent in this case.
* `Html Preparation Code`: Another optional field that is also empty.

**Test Cases**

The test cases are represented by an array of objects, each containing:

* `Benchmark Definition`: A string that represents the JavaScript code to be executed. This code performs exponentiation operations using the `Math.pow()` function.
* `Test Name`: The name of each test case, which is a human-readable description of the benchmark.

Here's a breakdown of each test case:

1. `var x = Math.pow(1.1,10);` - Tests exponentiation with base 1.1 and exponent 10.
2. `var x = Math.pow(1.1,100);` - Tests exponentiation with base 1.1 and exponent 100.
3. `var x = Math.pow(1.1,1000);` - Tests exponentiation with base 1.1 and exponent 1000.
4. `var x = Math.pow(2,1000);` - Tests exponentiation with base 2 and exponent 1000.

**Options Compared**

The benchmark compares the performance of different exponentiation operations using the `Math.pow()` function:

* Different bases (1.1 vs 2)
* Different exponents (10, 100, or 1000)

These options are compared to evaluate which one performs better in terms of execution speed.

**Pros and Cons**

Each option has its pros and cons:

* Using base 1.1 with small exponents (e.g., 10) might be faster due to the smaller result size.
* Using base 2 with large exponents (e.g., 1000) is likely to be slower due to the larger intermediate results.
* The performance difference between these options will depend on the specific hardware and JavaScript engine being used.

**Library Usage**

None of the test cases use any external libraries. The `Math.pow()` function is a built-in JavaScript function that performs exponentiation operations.

**Special JS Features**

There are no special JavaScript features or syntaxes mentioned in the benchmark definition or individual test cases.

**Alternatives**

If you're interested in writing your own benchmarks, here are some alternatives:

* Use a tool like Benchmark.js to write and run microbenchmarks.
* Utilize existing frameworks like Webpack or Browserify that provide built-in benchmarking capabilities.
* Write benchmark-specific libraries or modules for Node.js or browser-based applications.

Keep in mind that the performance comparison between different exponentiation operations might not be the most relevant use case, but it can still serve as a starting point for understanding how to write effective benchmarks.

Related benchmarks:

powoaetuheu (version: 0)

Comparing performance of: 1.110 vs 1.1100 vs 1.11000 vs 21000

Created: 4 years ago by: Guest

Jump to the latest result

1.1**10

1.1**100

1.1**1000

2**1000

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):

powoaetuheu (version: 0)

Comparing performance of: 1.1**10 vs 1.1**100 vs 1.1**1000 vs 2**1000

Created: 4 years ago by: Guest

Jump to the latest result

1.1**10

1.1**100

1.1**1000

2**1000

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):

Comparing performance of: 1.110 vs 1.1100 vs 1.11000 vs 21000