# Fast Iteration of Set Bits in BitSet

Full code for article found here

While building the Aidos engine for Discrete Rate Simulation, I often have to build custom collections to meet the project’s performance requirements. Don’t get me wrong, many of the collections built into .NET are great, but they are general-purpose. General-purpose collections must meet the requirements of many use cases. I have a single use case in mind for my work, and performance is one of the critical features. If our engine isn’t orders of magnitude faster than the competition, we don’t have a compelling product.

In Aidos, I often need to track items that have changed during a time step of the simulation. I also track entities with an int that has been annotated with a Unit of Measure. This means an entity ends up being an int<'EntityType>. I also cannot have duplicates for my use case, so I need to maintain a distinct set of entities that have changed. One way to do this would be to use a HashSet. HashSet is built into .NET and provides O(1) insertion, which you would think would be ideal for this use case. The downside to a HashSet is that its memory will be allocated on the heap. If you have to create a HashSet for every iteration of a hot loop, this can cause excess GC pressure.

Instead, what I use is a custom BitSet. BitSet is a struct that wraps an array of uint64, which acts as a bit array that I manually manage. The .NET runtime has a BitArray class, but it does not provide the API I need for my use cases. I need to iterate through all the set bits and call a function with the index of the set bit as an argument.

One of the advantages of the BitSet approach over HashSet is that the array used by the BitSet can be allocated from an ArrayPool, which means that BitSet will never increase GC pressure or take up room on the heap. The other is that it is faster than HashSet for iterating through the set bits using the BitSet.iter function.

Here is the definition of the BitSet type:

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43  [] type BitSet<[] 'Measure>(buckets: uint64[]) = new(capacity: int) = let bucketsRequired = (capacity + 63) >>> 6 let buckets: uint64[] = Array.zeroCreate bucketsRequired BitSet<_> buckets /// WARNING: Public for inlining member _._buckets = buckets member _.Capacity = buckets.Length * 64 member b.Count = let mutable total = 0 for bucket in b._buckets do total <- total + System.Numerics.BitOperations.PopCount bucket total member b.Item with get (itemKey: int<'Measure>) = let bucketId, mask = Helpers.computeBucketAndMask itemKey let buckets = b._buckets let bucket = buckets[bucketId] (bucket &&& mask) <> 0UL member b.Contains(itemKey: int<'Measure>) = let bucketId, mask = Helpers.computeBucketAndMask itemKey let buckets = b._buckets let bucket = buckets[bucketId] (bucket &&& mask) <> 0UL member b.Add(itemKey: int<'Measure>) = let bucketId, mask = Helpers.computeBucketAndMask itemKey let bucket = buckets[bucketId] buckets[bucketId] <- bucket ||| mask member b.Remove(itemKey: int<'Measure>) = let bucketId, mask = Helpers.computeBucketAndMask itemKey let buckets = b._buckets let bucket = buckets[bucketId] buckets[bucketId] <- bucket &&& ~~~mask 

We also have a BitSet module where we define the functions for operating on BitSet. Here I show just the iter function. iter loops through each set bit in the array and calls the lambda f with the index of the set bit as the argument.

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  module BitSet = let inline iter ([] f: int<'Measure> -> unit) (b: BitSet<'Measure>) = let mutable i = 0 // Source of algorithm: https://lemire.me/blog/2018/02/21/iterating-over-set-bits-quickly/ while i < b._buckets.Length do let mutable bitSet = b._buckets[i] while bitSet <> 0UL do let r = System.Numerics.BitOperations.TrailingZeroCount bitSet let itemId = (i <<< 6) + r |> LanguagePrimitives.Int32WithMeasure<'Measure> (f itemId) bitSet <- bitSet ^^^ (1UL <<< r) i <- i + 1 

I set up a benchmark to compare the performance of HashSet and BitSet. I define a unit of measure, Chicken, which I will use as the entity type to annotate my int values. I add 10 int<Chicken> between the values of 0<Chicken> and 99<Chicken> to both of these collections. This range of values is a good representation of the use case that I am concerned with. I then write a benchmark for measuring the time to iterate through the values in both collections to see how long it takes for both collections. When I run the benchmark using BenchmarkDotNet I get the following result:

 1 2 3 4  | Method | Mean | Error | StdDev | Gen0 | Allocated | |----------------- |----------:|----------:|----------:|-------:|----------:| | HashSet | 23.377 ns | 0.3017 ns | 0.2822 ns | - | - | | Iter | 7.048 ns | 0.1168 ns | 0.1092 ns | - | - | 

We see that the iter function for BitSet is approximately 3x faster than HashSet for iterating through the values.

## The Problem

Now, you may be thinking that BitSet is great, but there is a downside to this approach. The iter function takes a lambda as one of its arguments. Whenever the BitSet encounters a set bit, it then calls the lambda with the index of the set bit. Lambdas are intrinsic to programming in F#, but they have limitations. One of those limitations is that they cannot capture Span<'T> or ByRefLike types. Most of the time, this is not a big deal. F# developers are not often known as hardcore performance programmers, so most F# developers will not run into this problem.

I, on the other hand, work with Span<'T> and ByRefLike types all the time. They can be incredibly powerful for increasing your program’s performance and decreasing memory allocations. Now, a word of caution. You probably don’t need this. You can lead a very happy life as an F# developer, and never worry about this. This limitation only becomes an issue when you are trying to eke out every bit of performance you can, and you are likely not in that scenario. I happen to be in an odd situation because I work for a company with an F# dev team, and I’m tasked with writing libraries for others to use that must be fast. For strategic reasons, we constrain ourselves to F#, so calling out to C/C++/Rust is not an option. You will appreciate what we cover next if you find yourself in a similar situation.

I have asked about relaxing some of the compiler restrictions around lambdas and capturing Span<'T>, but the effort would be large. The more I dug into how the F# compiler and the CLR interact, my appreciation for the complexity of the problem grows. This is also not the most important feature for the growth of F#, so I’m not going to push for it. I hope to get good enough to contribute it to the F# compiler someday 😊.

## The Solution

So how do we get around this limitation? BitSet is intended for these hot loops where we likely want to be able to use some stack-allocated memory. This means we must be able to work with BitSet and Span<'T> simultaneously. The simple solution is to expose a new way of iterating through the set bits in the BitSet. We can implement IEnumerable<'T> for BitSet and use a for...in...do loop.

The easiest way to implement IEnumerable<'T> for BitSet is to define a BitSetEnumerator, which takes the logic used in the iter function but exposes it in a way that the IEnumerable<'T> interface expects. Let’s see what that looks like:

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44  type BitSetEnumerator<[] 'Measure>(buckets: uint64[]) = let mutable bucketIdx = 0 let mutable curBucket = 0UL let mutable curItem = LanguagePrimitives.Int32WithMeasure<'Measure> -1 member _.Current = if curItem < 0<_> then raise (InvalidOperationException "Enumeration has not started. Call MoveNext.") else curItem member b.MoveNext() = // Check if we have actually started iteration if curItem < 0<_> then curBucket <- buckets[bucketIdx] // There are still items in the Current bucket we should return if curBucket <> 0UL then let r = System.Numerics.BitOperations.TrailingZeroCount curBucket curItem <- LanguagePrimitives.Int32WithMeasure<'Measure>((bucketIdx <<< 6) + r) curBucket <- curBucket ^^^ (1UL <<< r) true // We need to move to the next bucket of items else bucketIdx <- bucketIdx + 1 if bucketIdx < buckets.Length then curBucket <- buckets[bucketIdx] b.MoveNext() else false member _.Reset() = bucketIdx <- 0 curBucket <- 0UL curItem <- LanguagePrimitives.Int32WithMeasure<'Measure> -1 interface IEnumerator> with member b.Current = b.Current :> Object member b.Current = b.Current member b.MoveNext() = b.MoveNext() member b.Reset() = b.Reset() member b.Dispose() = () 

The BitSetEnumerator type defines three methods for fulfilling the IEnumerable<'T> contract: Current, MoveNext, and Reset. You can see how the BitSetEnumerator fulfills the IEnumerable<'T> interface at the bottom. The type uses the same bit-shifting logic iter uses but breaks it up to support the methods that IEnumerable<'T> expects.

We can then have the BitSet collection implement the IEnumerable<'T> interface by returning an instance of the BitSetEnumerator when calling the GetEnumerator method.

  1 2 3 4 5 6 7 8 9 10 11 12  open System.Collections.Generic [] type BitSet<[] 'Measure>(buckets: uint64[]) = // Previous logic here interface System.Collections.IEnumerable with member b.GetEnumerator() = (new BitSetEnumerator<'Measure>(buckets)) :> System.Collections.IEnumerator interface IEnumerable> with member s.GetEnumerator() = new BitSetEnumerator<'Measure>(buckets) 

When we add this approach to the benchmarks, we get the following result:

 1 2 3 4 5  | Method | Mean | Error | StdDev | Gen0 | Allocated | |----------- |----------:|----------:|----------:|-------:|----------:| | HashSet | 23.347 ns | 0.4024 ns | 0.3764 ns | - | - | | Iter | 7.087 ns | 0.1000 ns | 0.0935 ns | - | - | | Enumerable | 55.521 ns | 0.9228 ns | 0.8181 ns | 0.0048 | 40 B | 

The IEnumerable<'T> approach is twice as slow as using a HashSet. This is less than ideal. It is also allocating on the heap. This is because the interface necessitates the creation of an object on the heap. We’ve negated most, if not all, of the benefits we hope to get from BitSet. What can we do?

## Ducks All The Way Down

There’s a feature of .NET that I don’t hear about much but is important in this scenario. The .NET runtime will use duck-typing to implement C# foreach loops and their equivalents. The runtime will look at the type and see if it has a GetEnumerator method that returns a type with the Current field and the MoveNext method. Well, the for...in...do loop in F# is the equivalent to the C# foreach loop.

What if instead of implementing IEnumerable<'T> we rely on the .NET duck-typing approach? We can change our enumerator to be a struct so that it doesn’t allocate any memory on the heap, and we’ll avoid the overhead of an interface.

Here’s what the BitSetEnumerator looks like as a struct with only the necessary pieces for duck-typing.

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42  [] type BitSetEnumerator<[] 'Measure> = val mutable BucketIdx: int val mutable CurBucket: uint64 val mutable CurItem: int<'Measure> val Buckets: uint64[] new(buckets: uint64[]) = { BucketIdx = 0 CurBucket = 0UL CurItem = LanguagePrimitives.Int32WithMeasure<'Measure> -1 Buckets = buckets } member b.Current = if b.CurItem < 0<_> then raise (InvalidOperationException "Enumeration has not started. Call MoveNext.") else b.CurItem member b.MoveNext() = // Check if we have actually started iteration if b.CurItem < 0<_> then b.CurBucket <- b.Buckets[b.BucketIdx] // There are still items in the Current bucket we should return if b.CurBucket <> 0UL then let r = System.Numerics.BitOperations.TrailingZeroCount b.CurBucket b.CurItem <- LanguagePrimitives.Int32WithMeasure<'Measure>((b.BucketIdx <<< 6) + r) b.CurBucket <- b.CurBucket ^^^ (1UL <<< r) true // We need to move to the next bucket of items else b.BucketIdx <- b.BucketIdx + 1 if b.BucketIdx < b.Buckets.Length then b.CurBucket <- b.Buckets[b.BucketIdx] b.MoveNext() else false 

Things look a bit different since BitSetEnumerator is now a struct and therefore requires different approaches to handling the internal data.

We also change the BitSet type to only have a GetEnumerator() method instead of implementing IEnumerable<'T>.

 1 2 3 4 5  [] type BitSet<[] 'Measure>(buckets: uint64[]) = // Previous logic member b.GetEnumerator() = BitSetEnumerator<'Measure>(buckets) 

When we benchmark this approach, we get the following:

 1 2 3 4 5 6  | Method | Mean | Error | StdDev | Gen0 | Allocated | |----------- |----------:|----------:|----------:|-------:|----------:| | HashSet | 23.347 ns | 0.4024 ns | 0.3764 ns | - | - | | Iter | 7.087 ns | 0.1000 ns | 0.0935 ns | - | - | | Enumerable | 55.521 ns | 0.9228 ns | 0.8181 ns | 0.0048 | 40 B | | DuckTyping | 28.039 ns | 0.5183 ns | 0.4848 ns | - | - | 

This is much better. Our performance is almost that of a HashSet. Something to be aware of, the duck-typing approach and the IEnumerable<'T> are not mutually exclusive. If you implement both, the runtime will pick the faster approach in the testing I have done. In the production code, we include both because the IEnumerable<'T> is necessary for using the BitSet with the Seq module.

## Inline All The Things (When it helps)

You have probably noticed that our loop-based approach’s performance is still not near the iter method. That’s to be expected. The for-loop approach adds overhead to the iteration. The F# compiler has some special transforms that it does for arrays which makes using a for...in...do loop over the elements of an array incredibly fast, but most other collections do not get that special treatment.

There is something we can do to get a little more performance, though. Right now, each time the MoveNext method is called, it creates a new stack frame. This adds overhead to the loop when it has to copy data for each instance of the stack frame. If we could inline the logic of the MoveNext method, we could reduce the number of stack frames created and potentially get a performance boost.

If you try to add the inline keyword to Current and MoveNext on BitSetEnumerator, you will have a problem. The compiler will give you an error that looks something like this:

  1 2 3 4 5 6 7 8 9 10  D:\Documents\GitHub\FSharpPerformance\BitSetEnumeration\DuckTyping.fs(55,17): error FS1114: The value 'BitSetEnumeration.DuckTyping.BitSetEnumerator.MoveNext' was marked inline but was not bound in the optimi zation environment [D:\Documents\GitHub\FSharpPerformance\BitSetEnumeration\BitSetEnumeration.fsproj] D:\Documents\GitHub\FSharpPerformance\BitSetEnumeration\DuckTyping.fs(37,21): error FS1113: The value 'MoveNext' was marked inline but its implementation makes use of an internal or private function which is not sufficiently accessible [D:\Documents\GitHub\FSharpPerformance\BitSetEnumeration\BitSetEnumeration.fsproj] D:\Documents\GitHub\FSharpPerformance\BitSetEnumeration\DuckTyping.fs(55,17): warning FS1116: A value marked as 'inline' has an unexpected value [D:\Documents\GitHub\FSharpPerformance\BitSetEnumeration\BitSet Enumeration.fsproj] D:\Documents\GitHub\FSharpPerformance\BitSetEnumeration\DuckTyping.fs(55,17): error FS1118: Failed to inline the value 'MoveNext' marked 'inline', perhaps because a recursive value was marked 'inline' [D:\Doc uments\GitHub\FSharpPerformance\BitSetEnumeration\BitSetEnumeration.fsproj] The build failed. Fix the build errors and run again. 

That looks like a lot of garbage, but the important part is near the end. It reports an error on line 55 of our DuckTyping.fs, which mentions “perhaps because a recursive value was marked inline.” That’s the clue we need. The MoveNext method is recursive at the moment, so the inlining logic of the F# compiler cannot work. What we need to do is remove this recursion. When we remove the recursion from the MoveNext method, we get the following:

  1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31   member inline b.MoveNext() = // Check if we have actually started iteration if b.CurItem < 0<_> then b.CurBucket <- b.Buckets[b.BucketIdx] // There are still items in the Current bucket we should return if b.CurBucket <> 0UL then let r = System.Numerics.BitOperations.TrailingZeroCount b.CurBucket b.CurItem <- LanguagePrimitives.Int32WithMeasure<'Measure>((b.BucketIdx <<< 6) + r) b.CurBucket <- b.CurBucket ^^^ (1UL <<< r) true // We need to move to the next bucket of items else b.BucketIdx <- b.BucketIdx + 1 let mutable result = false while b.BucketIdx < b.Buckets.Length && (not result) do b.CurBucket <- b.Buckets[b.BucketIdx] // There are still items in the Current bucket we should return if b.CurBucket <> 0UL then let r = System.Numerics.BitOperations.TrailingZeroCount b.CurBucket b.CurItem <- LanguagePrimitives.Int32WithMeasure<'Measure>((b.BucketIdx <<< 6) + r) b.CurBucket <- b.CurBucket ^^^ (1UL <<< r) result <- true if not result then b.BucketIdx <- b.BucketIdx + 1 result 

The logic for moving to the next bucket and checking for values has gotten more complex, but it no longer recurses. This allows us to use the inline keyword to get the F# compiler to inline this logic where it is used. This will reduce the number of stack frames used in our loop. Let’s see what the performance of this version is:

 1 2 3 4 5 6 7  | Method | Mean | Error | StdDev | Gen0 | Allocated | |----------- |----------:|----------:|----------:|-------:|----------:| | HashSet | 23.347 ns | 0.4024 ns | 0.3764 ns | - | - | | Iter | 7.087 ns | 0.1000 ns | 0.0935 ns | - | - | | Enumerable | 55.521 ns | 0.9228 ns | 0.8181 ns | 0.0048 | 40 B | | DuckTyping | 28.039 ns | 0.5183 ns | 0.4848 ns | - | - | | Inlining | 13.315 ns | 0.2178 ns | 0.2037 ns | - | - | 

Inlining is now faster than HashSet but still slower than Iter. This is a win for me because there’s now no performance downside to BitSet compared to HashSet for this scenario. Would I like to be able to match the performance of Iter? Yes, absolutely, but this is already nowhere near the bottleneck of our engine, so I moved on to other problems.

## Conclusion

You’ve learned a little about implementing IEnumerable<'T> for custom collections that you write and how to use the duck-typing of the foreach loop in .NET to get even better performance. We’ve also shown that we can perform even better using the inline keyword to remove stack frames.

I recommend that you stick with the built-in looping functions provided by F#: map, iter, iteri, etc. They are highly optimized and will give you great performance out of the box. In rare cases, you should consider other options where the need to capture a Span<'T> or another restriction forces you to use other looping constructs. I hope you find this helpful. Please feel free to reach out with any questions or critiques 😊.