[Haskell-cafe] vector-simd: some code available, and some questions
Reiner Pope
reiner.pope at gmail.com
Sun Jul 8 12:49:36 CEST 2012
I've not been following this thread very closely, but it seems like what
you're trying to do may be related to Geoffrey Mainland's work on SIMD
support in GHC. See [1] for his "SIMD-enabled version of the vector
library". He's also written some blog posts about this [2].
Reiner
[1] https://github.com/mainland/vector
[2] http://ghc-simd.blogspot.com.au/
On 8 July 2012 05:13, Nicolas Trangez <nicolas at incubaid.com> wrote:
> All,
>
> After my message of yesterday [1] I got down to it and implemented
> something along those lines. I created a playground repository
> containing the code at [2]. Initial benchmark results at [3]. More about
> the benchmark at the end of this email.
>
> First some questions and requests for help:
>
> - I'm stuck with a typing issue related to 'sizeOf' calculation at [4].
> I tried a couple of things, but wasn't able to figure out how to fix it.
> - I'm using unsafePerformIO at [5], yet I'm not certain it's OK to do
> so. Are there better (safer/performant/...) ways to get this working?
> - Currently Alignment phantom types (e.g. A8 and A16) are not related to
> each other: a function (like Data.Vector.SIMD.Algorithms.unsafeXorSSE42)
> can have this signature:
>
> unsafeXorSSE42 :: Storable a => SV.Vector SV.A16 a -> SV.Vector SV.A16 a
> -> SV.Vector SV.A16 a
>
> Yet, imaging I'd have an "SV.Vector SV.A32 Word8" vector at hand, the
> function should accept it as well (a 32-byte aligned vector is also
> 16-byte aligned). Is there any way to encode this at the type level?
>
> That's about it :-)
>
> As of now, I only implemented a couple of the vector API functions (the
> ones required to execute my benchmark). Adding the others should be
> trivial.
>
> The benchmark works with Data.Vector.{Unboxed|Storable}.Vector (UV and
> SV) vectors of Word8 values, as well as my custom
> Data.Vector.SIMD.Vector type (MV) using 16-byte alignment (MV.Vector
> MV.A16 Word8).
>
> benchUV, benchSV and benchMV all take 2 pre-calculated Word8 vectors of
> given size (1024 and 4096) and xor them pairwise into the result using
> "zipWith xor". benchMVA takes 2 suitable MV vectors and xor's them into
> a third using a rather simple and unoptimized C implementation using
> SSE4.2 intrinsics [6]. This could be enhanced quite a bit (I guess using
> the prim calling convention, FFI overhead can be reduced as well).
> Currently, only vectors of a multiple of 32 bytes are supported (mostly
> because of laziness on my part).
>
> As you can see, the zipWith Data.Vector.SIMD implementation is slightly
> slower than the Data.Vector.Storable based one. I didn't perform much
> profiling yet, but I suspect allocation and ForeignPtr creation is to
> blame, this seems to be highly optimized in
> GHC.ForeignPtr.mallocPlainForeignPtrBytes as used by
> Data.Vector.Storable.
>
> Thanks for any input,
>
> Nicolas
>
> [1] http://www.haskell.org/pipermail/haskell-cafe/2012-July/102167.html
> [2] https://github.com/NicolasT/vector-simd/
> [3] http://linode2.nicolast.be/files/vector-simd-xor1.html
> [4]
>
> https://github.com/NicolasT/vector-simd/blob/master/src/Data/Vector/SIMD/Algorithms.hs#L46
> [5]
>
> https://github.com/NicolasT/vector-simd/blob/master/src/Data/Vector/SIMD/Algorithms.hs#L43
> [6]
> https://github.com/NicolasT/vector-simd/blob/master/cbits/vector-simd.c#L47
>
>
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