Benchmark: I vs J - MeasureThat.net

Script Preparation code:

var arr = [];
for (var x = 0; x < 1000; x++)
{
 arr[x]=[]; 
}

Tests:

IJ
for (var i=0; i < 1000; i++) { for (var j=0; j < 1000; j++) { arr[i][j]=i*j; } }
JI
for (var i=0; i < 1000; i++) { for (var j=0; j < 1000; j++) { arr[j][i]=i*j; } }

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
IJ
JI

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 8 years ago)

User agent: Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/51.0.2704.106 Safari/537.36

Browser/OS: Chrome 51 on Windows 7

View result in a separate tab

Test name	Executions per second
IJ	10.0 Ops/sec
JI	9.3 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 JavaScript microbenchmark provided by MeasureThat.net.

**Benchmark Definition**

The benchmark is defined in two separate JSON objects:

1. `Script Preparation Code`: This code initializes an empty array `arr` with 1000 elements, each of which is also an empty array.
2. `Html Preparation Code`: There is no HTML preparation code specified.

In essence, the benchmark prepares a 2D array `arr` with dimensions 1000x1000 and then populates it with values obtained by multiplying two indices (`i` and `j`) together.

**Test Cases**

There are two test cases:

1. `IJ`: This test case iterates over `i` from 0 to 999 and for each iteration, it also iterates over `j` from 0 to 999. The result is stored in the array at position `(i, j)`.
2. `JI`: This test case is similar to `IJ`, but with the loop order reversed (iterating over `j` before `i`). Again, the result is stored in the array at position `(i, j)`.

**Library**

There are no external libraries mentioned in this benchmark definition.

**Special JS Features/Syntax**

Neither of the two test cases uses any special JavaScript features or syntax that is not commonly available. They use basic variables, loops, and arithmetic operations.

**Options Compared**

The two test cases differ only in the order of their loops:

1. `IJ`: Iterates over `i` first and then over `j`.
2. `JI`: Iterates over `j` first and then over `i`.

This difference will likely result in different performance characteristics, as it may affect cache locality or other memory-related optimizations.

**Pros and Cons of Different Approaches**

The choice between `IJ` and `JI` depends on the specific requirements and constraints of your application. Here are some pros and cons of each approach:

**IJ (Iterate over `i` first)**

Pros:

* May benefit from better cache locality, as the loop variables (`i` and `j`) tend to be stored in adjacent memory locations.
* Could potentially lead to faster performance due to reduced memory access patterns.

Cons:

* The compiler or interpreter may optimize away this difference, leading to no significant performance impact.

**JI (Iterate over `j` first)**

Pros:

* May reduce the likelihood of false sharing, a phenomenon where multiple threads access different variables that are stored in adjacent memory locations, leading to performance degradation.
* Could also benefit from better cache efficiency due to more diverse memory access patterns.

Cons:

* The loop variables (`i` and `j`) may not be stored in adjacent memory locations, leading to reduced cache locality.
* This approach may result in slower performance due to increased memory access patterns.

**Other Alternatives**

If you're interested in exploring alternative approaches or test cases, consider the following options:

1. **Swap loop order**: Try swapping the loop order of `IJ` and `JI`, so that one iterates over `i` first and the other iterates over `j` first.
2. **Use a different data structure**: Instead of using a 2D array, try using a different data structure such as a vector or matrix, which may exhibit different performance characteristics.
3. **Add additional complexity**: Introduce more complex operations or logic within the loops to see how they affect performance.
4. **Compare with other languages**: Test similar benchmarks in other programming languages to compare their performance characteristics.

Keep in mind that these alternatives will likely have varying degrees of impact on performance, and it's essential to consider your specific use case and requirements before modifying the benchmark.

Related benchmarks:

I vs J (version: 0)

Comparing performance of: IJ vs JI

Created: 8 years ago by: Guest

Jump to the latest result

IJ

JI

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):