Benchmark: Powers of two - MeasureThat.net

Tests:

1
var x = 10; var p = x/10.1;
2
var x = 10; var p = x/10.2;
3
var x = 10; var p = x/10.3;
24
var x = 10; var p = x/10.24;

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
1
2
3
24

Fastest: N/A

Slowest: N/A

Latest run results:

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks and explore what's being tested on MeasureThat.net.

**Benchmark Definition**

The benchmark definition represents a single test case, which in this case is about determining whether it's more efficient to store powers of two as an array or compute them within the loop. The script preparation code and HTML preparation code are empty, indicating that no additional setup or markup is required for this test.

**Individual Test Cases**

Each test case represents a specific power of two (10, 20, 30, 400) being divided by different decimal values (10.1, 10.2, 10.3, 10.24). The test cases are identical except for the divisor value.

**What's Being Tested**

The benchmark is testing the performance difference between:

1. **Array storage**: Computing powers of two within an array.
2. **Loop computation**: Computing powers of two directly within a loop.

In other words, the benchmark is asking: "Is it faster to store the results in an array and then perform computations on them, or to compute each power of two individually within the loop?"

**Options Compared**

Two main options are being compared:

1. **Array storage**: Storing powers of two as an array and computing them using array methods (e.g., `map()`, `reduce()`).
2. **Loop computation**: Computing each power of two directly within a loop.

**Pros and Cons of Each Approach**

**Array Storage:**

Pros:

* Potential cache locality benefits, as the results are stored in contiguous memory.
* Simplified code, as computations can be performed using array methods.

Cons:

* May lead to slower performance due to the overhead of creating and manipulating arrays.

**Loop Computation:**

Pros:

* Can take advantage of SIMD instructions (Single Instruction, Multiple Data) for improved performance.
* Avoids potential cache locality issues.

Cons:

* Code is more complex, as each power of two must be computed individually.

**Other Considerations**

The benchmark results are affected by factors such as:

* **Division precision**: The decimal values used in the test cases (e.g., 10.1, 10.2) may affect performance due to floating-point arithmetic overhead.
* **Browser and platform variations**: Different browsers and platforms may exhibit varying degrees of optimization or caching behavior.

**Libraries and Special Features**

There are no libraries explicitly mentioned in the benchmark definition. However, it's likely that modern JavaScript engines use various internal optimizations and caching mechanisms to improve performance.

If special features like `for...of` loops, async/await syntax, or Promises are used in the test code, they might affect the benchmark results but are not explicitly mentioned in this case.

**Alternatives**

Other alternatives for measuring JavaScript performance include:

* V8 Profiler (Chrome DevTools): A more comprehensive profiling tool that provides detailed insights into browser engine performance.
* Node.js Performance Benchmarks: Official benchmarks for Node.js, which measure performance under various workloads and configurations.
* JSHint or ESLint with the ` --bench` flag: These tools can be used to measure the performance of specific code snippets by running them in a benchmarking mode.

These alternatives offer different levels of detail and focus, but they all provide valuable insights into JavaScript performance optimization.

Related benchmarks:

Powers of two (version: 0)

If they should be written in an array or in the loop as we go

Comparing performance of: 1 vs 2 vs 3 vs 24

Created: 8 years ago by: Guest

Jump to the latest result

1

2

3

24

Suite status: <idle, ready to run>

Fastest: N/A

Slowest: N/A

No previous run results

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