Posted on August 22, 2018 by John Ky

In last week’s post I described how to produce rank-select bit-strings for an RFC-compliant CSV format without detailing how to perform efficiently the operation that splits odd and even bits of a bit-string into separate bit-strings.

In an earlier post I discussed rank and select operations, but also omitted to describe how they can be implemented efficiently.

In this blog post I will properly introduce the popcnt , pext , tzcnt and pdep operations and how they relate to the performance of our conceptual succinct data-structure based CSV parser.

Bit-manipulation instructions

Pop Count

The popcnt operation is quite straight-forward. It takes an integer as its input argument, counts the number of 1-bits and produces an integer containing the count.

In the following example, I count the number of 1-bits in my bit-string and find there are 5:

Trailing Zeros Count

The tzcnt operation is also quite straight-forward. It counts the number of “trailing zeros” in the bit-string.

Unfortunately, because we are on the topic of succinct data-structures, all our bits are expressed in Little-Endian, so visually we are looking at the leading zeros.

In the following example, I count the number of trailing zeros in my bit-string and find there are 3 (as indicated by the *** annotation):

Parallel Extract

The pext or “parallel extract” operation , is an operation that takes a bit-mask and extracts the bits from the source word corresponding to 1-bits in the bit-mask and packs them into least-significant side of the word.

* All words in Little-Endian * mask 0011001100110011 source 0110101110101001 bits 10 11 10 01 ┌─┘│ ││ ││ ││ │┌─┘ ││ ││ ││ ││┌───┘│ ││ ││ │││┌───┘ ││ ││ ││││┌─────┘│ ││ │││││┌─────┘ ││ ││││││┌───────┘│ │││││││┌───────┘ result 1011100100000000

In the following example, I extract the high nibble of each byte in my Word32 by using a mask where all the high-nibble bits are set to 1 :

Parallel Deposit

The pdep or “parallel deposit” operation, is an operation that takes a bit-mask and deposits the least-significant n-bits from the source word where n is the number of bits in the bit-mask and deposits them at the positions marked by 1-bits in the bit-mask.

* All words in Little-Endian * mask 0011001100110011 source 1011100100000000 │││││││└───────┐ ││││││└───────┐│ │││││└─────┐ ││ ││││└─────┐│ ││ │││└───┐ ││ ││ ││└───┐│ ││ ││ │└─┐ ││ ││ ││ └─┐│ ││ ││ ││ bits 10 11 10 01 bits 0010001100100001

In the following example, I deposit the first eight bits in my bits-string into the high nibble of each byte in my Word32 , again by using a mask where all the high-nibble bits are set to 1 :

Availability on GHC

In Haskell, the popCount operation is available via the popCount function in Data.Bits module of the base package.

On most modern x86 systems, the popCount operation is available on 64-bit integers in the form of the POPCNT CPU instruction, so it is very fast.

It is also available to C programs by way of the _popcnt64 CPU intrinsic, but what about Haskell?

To confirm that the function does in fact compile down to an instruction we first check the definition here.

and notice the use of the primop popCnt# .

Digging further into the GHC source code:

We find that this primop generates the POPCNT instruction provided that sse4_2Enabled yields True , which according to the GHC User Guide can be switched on with the -msse4.2 ghc flag since GHC 7.4.1 on x86 CPU architectures.

A similar search can be done for the tzcnt operation, but unfortunately the equivalent primop expands to a whole bunch of instructions:

The operation is emulated with BSF or Bit-Scan-Forward, which does something similar, but only works on 32-bit integers.

Unfortunately for me, I needed optimised pdep and pext primops from ghc for my succinct data-structure libraries, but sadly they weren’t available at the time I sought them, which was about this time last year.

I created a trac issue, and one thing led to another and I ended up implementing these primops in ghc over the space of several months with the kind help of Ben Gamari and Moritz Angermann.

The functionality is not exposed in base , but they can be accessed from the Haskell-Works bits-extra library. Benchmark results can be found there-in.

If anyone is looking to jump into GHC development, a good first project that can improve the performance of succinct data-structures on Haskell code would be to add native support for ctz# primop in GHC.

GHC needs more contributions and it would be great to see GHC become a better platform for writing high performance code.

Applications

Very fast implementation of Rank and Select

About this time last year, Ed Kmett, sent me very interesting paper on A General-Purpose Counting Filter: Making Every Bit Count.

Kmett nicely dropping me a paper on Quotient Filters and walking away

To really miss the amazing contribution of the paper and zoom in on the section relevant to this discussion go to section 3.2 “Fast x86 rank and select”, which describes how the PDEP and TZCNT instructions can be used to implement fast rank and select.

The formula for rank is given in the paper as:

The rank i of a bit-string is the prefix-sum of the bit-string of the given length i .

The diagram below shows five examples of rank operations on the same bit-string (b).

For the operation rank i , the expression 2ⁱ-1 computes a bit-mask (a) consisting of a prefix of 1-bits of length i that can be used to zero in our bit-string (b) all the bits beyond the prefix length to produce (c).

A pop count of (c) counts all the 1-bits annotated by * (d) and becomes our rank (e).

rank 2 rank 4 rank 6 rank 8 rank 10 (a) 1100000000000000 1111000000000000 1111110000000000 1111111100000000 1111111111000000 (b) 0100100010011000 0100100010011000 0100100010011000 0100100010011000 0100100010011000 (c) 0100000000000000 0100000000000000 0100100000000000 0100100000000000 0100100010000000 (d) * * * * * * * * * (e) 1 1 2 2 3

The select i of a bit-string is length of the smallest prefix that includes i 1-bits in the bit-string. Unfortunately, I feel like there is an off-by-one error in the formula and that it should actually be:

The diagram below shows five examples of select operations on the same bit-string (b).

For the operation select i , the expression 2 i-1 computes a bit-string containing exactly one 1-bit at the i-th position in the bit-string (1-based).

The pdep operation is called to deposit this bit at the position corresponding to the n-th 1-bit in (b) to produce the result (c).

The number of trailing zeros (indicated by the * ) when added to one yields the value of select i .

select 1 select 2 select 3 select 4 select 5 (a) 1000000000000000 0100000000000000 0010000000000000 0010000000000000 0010000000000000 ││││└───────┐ ││││└───────┐ ││││└───────┐ ││││└───────┐ ││││└───────┐ │││└────┐ │ │││└────┐ │ │││└────┐ │ │││└────┐ │ │││└────┐ │ ││└───┐ │ │ ││└───┐ │ │ ││└───┐ │ │ ││└───┐ │ │ ││└───┐ │ │ │└─┐ │ │ │ │└─┐ │ │ │ │└─┐ │ │ │ │└─┐ │ │ │ │└─┐ │ │ │ (b) 1001001010001000 1001001010001000 1001001010001000 1001001010001000 1001001010001000 (c) 1000000000000000 0001000000000000 0000001000000000 0000000010000000 0000000000001000 (d) 1 *** 4 ****** 7 ******** 9 ************ 13

Splitting a bit-string to odd and even bits

In last week’s post, I explained that in order to create the rank-select bit-strings for an RFC compliant CSV format, I needed an operation that can take a bit-string and collect all the odd bits into one bit-string and all the even-bits into another.

The example I gave is reproduced here:

text: aaa,bbb,ccc␍␊"a""aa","b␍␊bb","c,cc" quotes: 00000000000001011001010000010100001 parens: 0000000000000(0)(00)0(00000)0(0000) enters: 00000000000001001000010000000100000 exits: 00000000000000010001000000010000001

In this post I will be using odds in place of enters because these are the odd bits and evens in place of exits because these are the even bits in our bit-string.

The opening parentheses ( represents all the 1-bits that opening quotes of a quoted string and the closing parentheses ) represents all the 1-bits that represents for the closing quotes.

We need to build odds which has all the odd 1-bits (ie. the opening quotes) and leaves which has all the even 1-bits (ie. the closing quotes).

We must somehow be able to produce the bit-strings odds and evens from the bit-string quotes very efficiently.

This is actually very easy with a single application of the pdep operation for each bit-string we produce:

I will leave it to the reader to work out why this works. 😉

Next steps

We now have very fast rank-select operations for short bit-vectors of 64-bits, which is sufficient for CSV streaming because it allows us to process 64 bytes of CSV text at a time.

We also have the ability to split the odds and even bits out of our bit-string into separate bit-strings.

All the conceptual pieces needed to produce the necessary rank-select bit-strings for our high-performance RFC compliant CSV parser and pieces need to subsequently traverse the CSV text and extract interesting data have been described.

In my next post I will talk about how SIMD instructions can be used to make our parser go even faster!

Stay tuned!