Benchmark: powoaetuheu12321aeuoaoueoa

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);
1.1**10000
var x = Math.pow(1.1,10000);
73**10000
var x = Math.pow(73,10000);
var x = Math.pow(73.123,10023230);
var x = Math.pow(73.123,10023230);
Math.pow(1.000001,10023230);
Math.pow(1.000001,10023230);

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
1.1**10000
73**10000
var x = Math.pow(73.123,10023230);
Math.pow(1.000001,10023230);

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	7971097.5 Ops/sec
1.1**100	7787884.5 Ops/sec
1.1**1000	7722583.5 Ops/sec
2**1000	7712533.0 Ops/sec
1.1**10000	7642826.5 Ops/sec
73**10000	7584923.5 Ops/sec
var x = Math.pow(73.123,10023230);	7555918.5 Ops/sec
Math.pow(1.000001,10023230);	7492951.5 Ops/sec

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

LLMs can make mistakes. Check important info.

**Overview**

MeasureThat.net is a website that allows users to create and run JavaScript microbenchmarks. The provided JSON data represents the benchmark definition and individual test cases.

**Benchmark Definition**

The benchmark definition is represented by the `Script Preparation Code` field in the first JSON object, which is:

`"var x = Math.pow(1.1,10);"`

This code defines a simple mathematical expression using the `Math.pow()` function to raise 1.1 to the power of 10.

**Options Compared**

In this benchmark, the following options are compared:

* Exponentiation with integer base (e.g., `Math.pow(x, y)`)
* Exponentiation with floating-point base and decimal exponent
* Exponentiation with large numbers

These options allow users to compare the performance of JavaScript's built-in exponentiation functions in different scenarios.

**Pros and Cons**

The use of exponentiation as a benchmarking option has both pros and cons:

Pros:

* Simple and well-defined mathematical expression that can be executed quickly.
* Allows for comparison of execution times across different browsers and hardware configurations.

Cons:

* May not accurately represent real-world usage scenarios, which may involve more complex mathematical expressions or operations.
* Does not account for optimizations or caching performed by JavaScript engines.

**Other Considerations**

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

* Hardware and software configuration: The performance of different browsers on various hardware configurations can vary significantly.
* Cache behavior: JavaScript engines may optimize their caching strategies based on the type of operation (e.g., simple arithmetic vs. complex calculations).
* Garbage collection: The frequency and efficiency of garbage collection can impact overall system performance.

**Library Usage**

In the provided benchmark, no specific libraries are used. However, some test cases use built-in JavaScript functions, such as `Math.pow()`, which is a part of the ECMAScript standard.

If you were to add external libraries, some examples might include:

* Math.js: A lightweight math library for JavaScript that provides alternative implementations of mathematical functions.
* Exponents.js: A library specifically designed for exponentiation operations, which may offer optimized performance or specialized features.

**Special JS Features**

The benchmark does not explicitly use any special JavaScript features. However, it's essential to consider the implications of using certain features, such as:

* `let` and `const` declarations for scoping and variable binding
* Arrow functions for concise code snippets
* Object destructuring for simplified data manipulation

These features may affect performance or optimization strategies but are not explicitly used in this benchmark.

**Alternatives**

If you were to create alternative benchmarks, consider the following approaches:

1. **Mathematical operations with complex numbers**: Examine the performance of JavaScript engines when dealing with complex arithmetic involving numbers, such as imaginary numbers or very large/ small values.
2. **String manipulation and encoding**: Benchmark JavaScript engines' performance in manipulating and processing strings, considering various encoding schemes and character sets.
3. **WebAssembly and native code integration**: Investigate the performance impact of integrating WebAssembly modules or native code into JavaScript applications.

By exploring these alternatives, you can create more comprehensive benchmarking suites that better represent real-world use cases and provide valuable insights into JavaScript engine performance.

Related benchmarks:

powoaetuheu12321aeuoaoueoa (version: 0)

Comparing performance of: 1.110 vs 1.1100 vs 1.11000 vs 21000 vs 1.110000 vs 7310000 vs var x = Math.pow(73.123,10023230); vs Math.pow(1.000001,10023230);

Created: 4 years ago by: Guest

Jump to the latest result

1.1**10

1.1**100

1.1**1000

2**1000

1.1**10000

73**10000

var x = Math.pow(73.123,10023230);

Math.pow(1.000001,10023230);

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):

powoaetuheu12321aeuoaoueoa (version: 0)

Comparing performance of: 1.1**10 vs 1.1**100 vs 1.1**1000 vs 2**1000 vs 1.1**10000 vs 73**10000 vs var x = Math.pow(73.123,10023230); vs Math.pow(1.000001,10023230);

Created: 4 years ago by: Guest

Jump to the latest result

1.1**10

1.1**100

1.1**1000

2**1000

1.1**10000

73**10000

var x = Math.pow(73.123,10023230);

Math.pow(1.000001,10023230);

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 vs 1.110000 vs 7310000 vs var x = Math.pow(73.123,10023230); vs Math.pow(1.000001,10023230);