Benchmark: TypedFastBitSet vs Set

HTML Preparation code:

<script src="https://unpkg.com/typedfastbitset@0.1.2/TypedFastBitSet.js"></script>

Script Preparation code:

var setA = new Set();
var typedSetA = new TypedFastBitSet();
var setB = new Set();
var typedSetB = new TypedFastBitSet();
var N = 100;
for (var i = 0 ; i < N  ; i++) {
  setA.add(3 * i + 5);
  typedSetA.add(3 * i + 5);
  setB.add(6 * i + 5);
  typedSetB.add(6 * i + 5);
}

var genericSetIntersection = function(set1, set2) {
  var answer = new Set();
  if (set2.length > set1.length) {
    for (var j of set1) {
      if (set2.has(j)) {
        answer.add(j);
      }
    }
  } else {
    for (var j of set2) {
      if (set1.has(j)) {
        answer.add(j);
      }
    }
  }
  return answer;
};

var genericInplaceSetIntersection = function(set1, set2) {
  for (var j of set2) {
    if (!set1.has(j)) {
      set1.delete(j);
    }
  }
  return set1;
};

Tests:

Set intersection (new)
genericSetIntersection(setA, setB);
TypedFastBitSet intersection (new)
typedSetA.new_intersection(typedSetB);
Set intersection (inplace)
genericInplaceSetIntersection(setA, setB)
TypedFastBitSet intersection (inplace)
typedSetA.intersection(typedSetB);

Rendered benchmark preparation results:

Suite status: <idle, ready to run>

Previous results

Test case name	Result
Set intersection (new)
TypedFastBitSet intersection (new)
Set intersection (inplace)
TypedFastBitSet intersection (inplace)

Fastest: N/A

Slowest: N/A

Latest run results:

Run details: (Test run date: 4 years ago)

User agent: Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:82.0) Gecko/20100101 Firefox/82.0

Browser/OS: Firefox 82 on Windows

View result in a separate tab

Test name	Executions per second
Set intersection (new)	94883.4 Ops/sec
TypedFastBitSet intersection (new)	12536353.0 Ops/sec
Set intersection (inplace)	160425.6 Ops/sec
TypedFastBitSet intersection (inplace)	35383008.0 Ops/sec

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

LLMs can make mistakes. Check important info.

Let's dive into the world of JavaScript microbenchmarks!

The provided benchmark compares the performance of three approaches to find the intersection of two sets:

1. **Generic Set Intersection**: This approach uses a `Set` object and iterates over one set, checking if each element exists in the other set using the `has()` method.
2. **TypedFastBitSet Intersection (new)**: This approach uses the `TypedFastBitSet` library, which is optimized for fast set operations. The `intersection()` method is used to find the intersection of two sets.
3. **TypedFastBitSet Intersection (inplace)**: This approach also uses the `TypedFastBitSet` library, but instead of creating a new set, it modifies the existing one by iterating over the elements of the second set and deleting any that are not present in the first set.

Now, let's discuss the pros and cons of each approach:

**Generic Set Intersection**

Pros:

* Easy to understand and implement
* No additional dependencies required

Cons:

* Iterating over both sets can lead to slower performance for large datasets
* The `has()` method may have some overhead due to the use of a hash table

**TypedFastBitSet Intersection (new)**

Pros:

* Optimized for fast set operations, making it suitable for large datasets
* Reduces the number of iterations required compared to the generic approach

Cons:

* Requires an external library (`TypedFastBitSet.js`)
* May have additional dependencies or overhead due to the use of a custom library

**TypedFastBitSet Intersection (inplace)**

Pros:

* Reuses the existing set, reducing memory allocation and deallocation overhead
* Can be more efficient than creating a new set for large datasets

Cons:

* Requires the `TypedFastBitSet` library, which may add additional dependencies or overhead
* May require modifications to the implementation to handle errors and edge cases correctly

Other considerations:

* The use of a `Set` object can lead to slower performance due to the hash table lookup.
* The `has()` method may have some overhead due to the use of a hash table, although this is generally minimal.

In conclusion, the choice of approach depends on the specific requirements and constraints of your project. If you need high performance for large datasets, `TypedFastBitSet Intersection (new)` or `TypedFastBitSet Intersection (inplace)` may be suitable options. However, if simplicity and ease of implementation are more important, the generic set intersection approach may still be a good choice.

As for special JavaScript features or syntax, none are mentioned in this benchmark. The code uses standard JavaScript features such as sets, loops, and functions.

The `TypedFastBitSet` library is used to provide optimized set operations. It's not clear what specific optimizations it provides, but it's likely that the library uses a combination of techniques such as bit manipulation and caching to improve performance.

For alternative approaches, you may want to consider using other libraries or frameworks that provide set operations, such as `lodash.set` or `collections.js`. However, these alternatives may have their own trade-offs in terms of performance, simplicity, and dependencies.

Related benchmarks:

TypedFastBitSet vs Set (version: 0)

Comparing performance of: Set intersection (new) vs TypedFastBitSet intersection (new) vs Set intersection (inplace) vs TypedFastBitSet intersection (inplace)

Created: 4 years ago by: Registered User

Jump to the latest result

Set intersection (new)

TypedFastBitSet intersection (new)

Set intersection (inplace)

TypedFastBitSet intersection (inplace)

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):