I'm working on an implementation of one of the SHA3 candidates, JH. I'm at the point where the algorithm pass all KATs (Known Answer Tests) provided by NIST, and have also made it an instance of the Crypto-API. Thus I have began looking into its performance. But I'm quite new to Haskell and don't really know what to look for when profiling.
At the moment my code is consistently slower then the reference implementation written in C, by a factor of 10 for all input lengths (C code found here: http://www3.ntu.edu.sg/home/wuhj/research/jh/jh_bitslice_ref64.h).
My Haskell code is found here: https://github.com/hakoja/SHA3/blob/master/Data/Digest/JHInternal.hs.
Now I don't expect you to wade through all my code, rather I would just want some tips on a couple of functions. I have run some performance tests and this is (part of) the performance file generated by GHC:
Tue Oct 25 19:01 2011 Time and Allocation Profiling Report (Final)
main +RTS -sstderr -p -hc -RTS jh e False
total time = 6.56 secs (328 ticks @ 20 ms)
total alloc = 4,086,951,472 bytes (excludes profiling overheads)
COST CENTRE MODULE %time %alloc
roundFunction Data.Digest.JHInternal 28.4 37.4
word128Shift Data.BigWord.Word128 14.9 19.7
blockMap Data.Digest.JHInternal 11.9 12.9
getBytes Data.Serialize.Get 6.7 2.4
unGet Data.Serialize.Get 5.5 1.3
sbox Data.Digest.JHInternal 4.0 7.4
getWord64be Data.Serialize.Get 3.7 1.6
e8 Data.Digest.JHInternal 3.7 0.0
swap4 Data.Digest.JHInternal 3.0 0.7
swap16 Data.Digest.JHInternal 3.0 0.7
swap8 Data.Digest.JHInternal 1.8 0.7
swap32 Data.Digest.JHInternal 1.8 0.7
parseBlock Data.Digest.JHInternal 1.8 1.2
swap2 Data.Digest.JHInternal 1.5 0.7
swap1 Data.Digest.JHInternal 1.5 0.7
linearTransform Data.Digest.JHInternal 1.5 8.6
shiftl_w64 Data.Serialize.Get 1.2 1.1
Detailed breakdown omitted ...
Now quickly about the JH algorithm:
It's a hash algorithm which consists of a compression function F8, which is repeated as long as there exists input blocks (of length 512 bits). This is just how the SHA-functions operate. The F8 function consists of the E8 function which applies a round function 42 times. The round function itself consists of three parts:
a sbox, a linear transformation and a permutation (called swap in my code).
Thus it's reasonable that most of the time is spent in the round function. Still I would like to know how those parts could be improved. For instance: the blockMap function is just a utility function, mapping a function over the elements in a 4-tuple. So why is it performing so badly? Any suggestions would be welcome, and not just on single functions, i.e. are there structural changes you would have done in order to improve the performance?
I have tried looking at the Core output, but unfortunately that's way over my head.
I attach some of the heap profiles at the end as well in case that could be of interest.
EDIT :
I forgot to mention my setup and build. I run it on a x86_64 Arch Linux machine, GHC 7.0.3-2 (I think), with compile options:
ghc --make -O2 -funbox-strict-fields
Unfortunately there seems to be a bug on the Linux plattform when compiling via C or LLVM, giving me the error:
Error: .size expression for XXXX does not evaluate to a constant
so I have not been able to see the effect of that.
- Switch to unboxed Vectors (from Array, used for constants)
- Use
unsafeIndex
instead of incurring the bounds check and data dependency from safe indexing (i.e. !
)
- Unpack
Block1024
as you did with Block512
(or at least use UnboxedTuples
)
- Use
unsafeShift{R,L}
so you don't incur the check on the shift value (coming in GHC 7.4)
- Unfold the
roundFunction
so you have one rather ugly and verbose e8
function. This was significat in pureMD5 (the rolled version was prettier but massively slower than the unrolled version). You might be able to use TH to do this and keep the code smallish. If you do this then you'll have no need for constants
as these values will be explicit in the code and result in a more cache friendly binary.
- Unpack your
Word128
values.
- Define your own addition for
Word128
, don't lift Integer
. See LargeWord for an example of how this can be done.
rem
not mod
- Compile with optimization (
-O2
) and try llvm (-fllvm
)
EDIT: And cabalize your git repo along with a benchmark so we can help you easier ;-). Good work on including a crypto-api instance.
The lower graph shows that a lot of memory is occupied by lists. Unless there are more lurking in other modules, they can only come from e8
. Maybe you'll have to bite the bullet and make that a loop instead of a fold, but for starters, since Block1024
is a pair, the foldl'
doesn't do much evaluation on the fly (unless the strictness analyser has become significantly better). Try making that stricter, data Block1024 = B1024 !Block512 !Block512
, perhaps it also needs {-# UNPACK #-}
pragmas. In roundFunction
, use rem
instead of mod
(this will only have minor impact, but it's a bit faster) and make the let
bindings strict. In the swapN
functions, you might get better performance giving the constants in the form W x y
rather than as 128-bit hex numbers.
I can't guarantee those changes will help, but that's what looks most promising after a short glance.
Ok, so I thought I would chime in with an update of what I have done and the results obtained thus far. Changes made:
- Switched from Array to UnboxedArray (made Word128 an instance type)
- Used UnboxedArray + fold in e8 instead of lists and (prelude) fold
- Used unsafeIndex instead of !
- Changed type of Block1024 to a real datatype (similiar to Block512), and unpacked its arguments
- Updated GHC to version 7.2.1 on Arch Linux, thus fixing the problem with compiling via C or LLVM
- Switched mod to rem in some places, but NOT in roundFunction. When I do it there, the compile time suddenly takes an awful lot of time, and the run time becomes 10 times slower! Does anyone know why that may be? It is only happening with GHC-7.2.1, not GHC-7.0.3
I compile with the following options:
ghc-7.2.1 --make -O2 -funbox-strict-fields main.hs ./Tests/testframe.hs -fvia-C -optc-O2
And the results? Roughly 50 % reduction in time. On an input of ~107 MB, the code now use 3 minutes as compared to the previous 6-7 minutes. The C version uses 42 seconds.
Things I tried, but which didn't result in better performance:
Unrolled the e8 function like this:
e8 !h = go h 0
where go !x !n
| n == 42 = x
| otherwise = go h' (n + 1)
where !h' = roundFunction x n
Tried breaking up the swapN functions to use the underlying Word64' directly:
swap1 (W xh hl) =
shiftL (W (xh .&. 0x5555555555555555) (xl .&. 0x5555555555555555)) 1
.|.
shiftR (W (xh .&. 0xaaaaaaaaaaaaaaaa) (xl .&. 0xaaaaaaaaaaaaaaaa)) 1
Tried using the LLVM backend
All of these attempts gave worse performance than what I have currently. I don't know if thats because I'm doing it wrong (especially the unrolling of e8), or because they just are worse options.
Still I have some new questions with these new tweaks.
Suddenly I have gotten this peculiar bump in memory usage. Take a look at following heap profiles:
Why has this happened? Is it because of the UnboxedArray? And what does SYSTEM mean?
When I compile via C I get the following warning:
Warning: The -fvia-C flag does nothing; it will be removed in a future GHC release
Is this true? Why then, do I see better performance using it, rather than not?
It looks like you did a fair amount of tweaking already; I'm curious what the performance is like without explicit strictness annotations (BangPatterns
) and the various compiler pragmas (UNPACK
, INLINE
)... Also, a dumb question: what optimization flags are you using?
Anyway, two suggestions which may be completely awful:
- Use unboxed primitive types where you can (e.g. replace
Data.Word.Word64
with GHC.Word.Word64#
, make sure word128Shift
is using Int#
, etc.) to avoid heap allocation. This is, of course, non-portable.
- Try
Data.Sequence
instead of []
At any rate, rather than looking at the Core output, try looking at the intermediate C files (*.hc
) instead. It can be hard to wade through, but sometimes makes it obvious where the compiler wasn't quite as sharp as you'd hoped.