Benchmark: math pow vs multiply (float)

Tests:

pow
var x = Math.pow(54.123456789,2);
mult
var y = 54.123456789*54.123456789

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
pow
mult

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):

LLMs can make mistakes. Check important info.

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

**Benchmark Definition:**

The benchmark definition is a JSON object that specifies the characteristics of the test. In this case, it defines two tests:

* "math pow vs multiply (float)": This is the name of the benchmark, which describes what will be tested.
* "Script Preparation Code": and "Html Preparation Code" are blank, indicating that no additional code needs to be executed before running the benchmark.

**Test Cases:**

The test cases are defined as an array of objects, each containing:

* "Benchmark Definition": A string that represents the JavaScript code to be executed for this test.
	+ For the first test case ("pow"), the code is `var x = Math.pow(54.123456789,2);`.
	+ For the second test case ("mult"), the code is `var y = 54.123456789*54.123456789;`.
* "Test Name": A string that represents a descriptive name for this test case.

**What is being tested:**

The benchmark tests the performance of two different approaches to calculate the square of a floating-point number:

1. Using the `Math.pow()` function (`var x = Math.pow(54.123456789,2);`).
2. Performing the multiplication manually (`var y = 54.123456789*54.123456789;`).

**Options compared:**

These two approaches are being compared to determine which one is faster.

**Pros and Cons:**

Using `Math.pow()`:

Pros:

* More concise and readable code.
* Less prone to errors due to the use of a well-defined function.

Cons:

* May be slower due to the overhead of calling an external function.

Manual multiplication:

Pros:

* Can be faster since it eliminates the function call overhead.
* More control over optimization opportunities.

Cons:

* Less readable and more error-prone code.
* May require additional calculations or optimizations.

**Library usage:**

In this benchmark, no specific library is used. However, `Math.pow()` is a built-in JavaScript function, which means that any differences in performance are due to the implementation of this function or its interaction with other parts of the engine.

**Special JS feature/syntax:**

None mentioned, but note that some older browsers may have quirks with floating-point arithmetic or specific functions like `Math.pow()`.

**Other alternatives:**

If you wanted to test alternative approaches, some possibilities could include:

* Using a different mathematical library (e.g., NumJS).
* Implementing the square function using a different algorithm (e.g., polynomial approximation).
* Using parallel processing or multi-threading techniques.
* Optimizing one of the approaches for specific hardware architectures.

In this case, since the benchmark is focusing on comparing two common approaches, these alternatives are not relevant to the test.

Latest run results:

Run details: (Test run date: 5 years ago)

User agent: Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/67.0.3396.99 Safari/537.36

Browser/OS: Chrome 67 on Windows 7

View result in a separate tab

Test name	Executions per second
pow	4263097.5 Ops/sec
mult	667858688.0 Ops/sec

Related benchmarks:

math pow vs multiply (float) (version: 0)

Comparing performance of: pow vs mult

Created: 5 years ago by: Guest

Jump to the latest result

pow

mult

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 29 days ago):