Benchmark: a*a...*a vs a***x vs Math.pow(a,x)

Script Preparation code:

var int = 59;
var float = Math.random();

Tests:

int*int
int*int
int**2
int**2
Math.pow(int,2)
Math.pow(int,2)
float*float
float*float
float**2
float**2
Math.pow(float, 2)
Math.pow(float, 2)
int*int*int*int*int
int*int*int*int*int
int**5
int**5
Math.pow(int,5)
Math.pow(int,5)
float*float*float*float*float
float*float*float*float*float
float**5
float**5
Math.pow(float,5)
Math.pow(float,5)

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
int*int
int**2
Math.pow(int,2)
float*float
float**2
Math.pow(float, 2)
intintintintint
int**5
Math.pow(int,5)
floatfloatfloatfloatfloat
float**5
Math.pow(float,5)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 3 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/90.0.4430.93 Safari/537.36

Browser/OS: Chrome 90 on Windows

View result in a separate tab

Test name	Executions per second
int*int	4696688.5 Ops/sec
int**2	9132634.0 Ops/sec
Math.pow(int,2)	3623022.5 Ops/sec
float*float	5289712.5 Ops/sec
float**2	8990032.0 Ops/sec
Math.pow(float, 2)	3592944.8 Ops/sec
intintintintint	2154760.8 Ops/sec
int**5	4836198.5 Ops/sec
Math.pow(int,5)	3605313.0 Ops/sec
floatfloatfloatfloatfloat	2051419.4 Ops/sec
float**5	4642816.0 Ops/sec
Math.pow(float,5)	3652745.5 Ops/sec

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

LLMs can make mistakes. Check important info.

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

**Benchmark Definition**

The `Name` field specifies that the benchmark is comparing three different approaches to calculate the square of an integer or float value: `a*a...*a`, `a***x`, and `Math.pow(a,x)`.

The `Description` field is empty, indicating that no additional information is provided about the benchmark.

**Script Preparation Code**

The script preparation code sets two variables:
- `int`: a 59 (likely an arbitrary large integer used for testing)
- `float`: a random float value between 0 and 1 (generated using `Math.random()`)

This code initializes the variables that will be used in the benchmark tests.

**Html Preparation Code**

The html preparation code is empty, which means no HTML-related setup is required before running the benchmarks.

**Test Cases**

Each test case defines a specific benchmark to run:

- **Integer Squares**: Tests calculate the square of an integer using `a*a...*a`, `Math.pow(int,2)`, and comparing their performance.
- **Float Squares**: Similar to Integer Squares but uses floats (`float` variable generated in script preparation code).

Some key observations from these test cases:

1.  The benchmark is evaluating the performance of three methods for calculating squares: manual multiplication (`a*a...*a`), `Math.pow(a,x)`, and possibly another method, as two are mentioned.
2.  The `int` variable represents an arbitrary large integer value used to calculate square values, which helps in testing the performance with larger numbers and verifying that the results are correct for these cases.
3.  A float value (`float`) is used instead of a specific number for calculating squares when comparing the manual multiplication approach versus `Math.pow(a,x)`. This change allows the benchmark to evaluate the difference between using a large integer and a floating-point value.
4.  The test cases cover various scenarios, including testing with different sizes of integers (specifically large numbers in this case).

**Comparison**

The primary comparison here is between two methods for calculating squares: `Math.pow(a,x)` (using both an integer and a float) versus a manual multiplication approach (`a*a...*a`). The benchmark likely aims to determine which method is faster for these operations, especially under different conditions like larger values.

By using `int` as 59 in the script preparation code, it's possible that the benchmark also evaluates performance across different scale factors (i.e., multiplying by more `a`s), but without further details on test cases beyond what was provided, we can't confirm this aspect for certain.

Related benchmarks:

aa...a vs a***x vs Math.pow(a,x) (version: 0)

Comparing performance of: int*int vs int**2 vs Math.pow(int,2) vs float*float vs float**2 vs Math.pow(float, 2) vs intintintintint vs int**5 vs Math.pow(int,5) vs floatfloatfloatfloatfloat vs float**5 vs Math.pow(float,5)

Created: 6 years ago by: Registered User

Jump to the latest result

int*int

int**2

Math.pow(int,2)

float*float

float**2

Math.pow(float, 2)

intintintintint

int**5

Math.pow(int,5)

floatfloatfloatfloatfloat

float**5

Math.pow(float,5)

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):

a*a...*a vs a***x vs Math.pow(a,x) (version: 0)

Comparing performance of: int*int vs int**2 vs Math.pow(int,2) vs float*float vs float**2 vs Math.pow(float, 2) vs int*int*int*int*int vs int**5 vs Math.pow(int,5) vs float*float*float*float*float vs float**5 vs Math.pow(float,5)

Created: 6 years ago by: Registered User

Jump to the latest result

int*int

int**2

Math.pow(int,2)

float*float

float**2

Math.pow(float, 2)

int*int*int*int*int

int**5

Math.pow(int,5)

float*float*float*float*float

float**5

Math.pow(float,5)

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):

aa...a vs a***x vs Math.pow(a,x) (version: 0)

Comparing performance of: int*int vs int**2 vs Math.pow(int,2) vs float*float vs float**2 vs Math.pow(float, 2) vs intintintintint vs int**5 vs Math.pow(int,5) vs floatfloatfloatfloatfloat vs float**5 vs Math.pow(float,5)

intintintintint

floatfloatfloatfloatfloat