Benchmark: Pre-array or function calls

Script Preparation code:


var xOffset = 0;
var xScale = 1;
var i = 0, l = 10000000;

function getX( index ) {
  return xOffset + index * xScale;
}

var tot = 0;

Tests:

test1
for( ;i < l; i ++ ) { tot += getX( i ); }
test2
for( ;i < l; i ++ ) { tot += xOffset + i * xScale; }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
test1
test2

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):

LLMs can make mistakes. Check important info.

Let's break down the provided benchmark and its options.

**Benchmark Definition**

The benchmark is defined by two scripts, which are executed in series to measure the performance of the JavaScript engine. The scripts prepare some variables, including `xOffset`, `xScale`, and `i` (the loop counter), and then execute a loop that calls either a function or adds the result of an expression directly to the `tot` variable.

**Script Preparation Code**

The script preparation code sets up two variables: `xOffset` and `xScale`. These variables are used in both test cases. The third variable, `i`, is initialized to 0 and assigned a large value (`l = 10000000`). This variable is used as the loop counter.

**Html Preparation Code**

The HTML preparation code is empty, which means that the benchmark does not rely on any specific HTML structure or layout.

**Test Cases**

There are two test cases:

1. **test1**: The script executes a `for` loop that calls the function `getX(i)`, passing the current value of `i` as an argument. The result is added to the `tot` variable.
2. **test2**: The script executes a `for` loop that directly adds the expression `xOffset + i * xScale` to the `tot` variable.

**Options Compared**

The two test cases compare the performance of:

* Directly accessing and adding variables (`test1`)
* Calling a function with variables as arguments (`test2`)

**Pros and Cons**

* **Direct Access**: This approach is likely faster because it avoids the overhead of function calls. However, it may also lead to optimization issues if the JavaScript engine can't optimize away the memory access.
* **Function Call**: This approach forces the JavaScript engine to handle a function call, which may introduce additional overhead. However, it allows the engine to perform more aggressive optimizations, such as inlining or caching.

**Other Considerations**

The benchmark does not consider other factors that might affect performance, such as:

* Data types: Are integers, floats, or strings used? Each data type has different memory layouts and access patterns.
* Memory allocation: How much memory is allocated for the variables `xOffset`, `xScale`, and `i`?
* Garbage collection: Is garbage collection enabled in this benchmark?

**Alternative Benchmarks**

Other alternatives to these test cases could include:

* **Using arrays instead of loops**: Instead of using a loop, could we use an array and access elements by index? This might be faster for large arrays.
* **Using SIMD instructions**: Could we use SIMD (Single Instruction, Multiple Data) instructions to perform the calculations on multiple values simultaneously?
* **Using a different data structure**: Are the results affected if we use a different data structure, such as a linked list or a tree?

**Library Usage**

The benchmark does not appear to use any external libraries. However, it's worth noting that some JavaScript engines might optimize for specific library functions or methods.

**Special JS Feature or Syntax**

There are no special features or syntax used in this benchmark. The code is straightforward and uses standard JavaScript constructs.

Latest run results:

Run details: (Test run date: 7 years ago)

User agent: Mozilla/5.0 (Macintosh; Intel Mac OS X 10_9_5) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/57.0.2959.0 Safari/537.36

Browser/OS: Chrome 57 on Mac OS X 10.9.5

View result in a separate tab

Test name	Executions per second
test1	3649155.2 Ops/sec
test2	3768555.5 Ops/sec

Related benchmarks:

Pre-array or function calls (version: 0)

Comparing performance of: test1 vs test2

Created: 7 years ago by: Guest

Jump to the latest result

test1

test2

Suite status: <idle, ready to run>

Experimental features:

Fastest: N/A

Slowest: N/A

Autogenerated LLM Summary (model llama3.2:3b, generated 25 days ago):