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How to make my Haskell program faster? Comparison with C

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.

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hakoja Avatar asked Oct 25 '11 18:10

hakoja


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How is Haskell faster than C?

Haskell's laziness actually means that mutability doesn't matter as much as you think it would, plus it's high-level so there are many optimizations the compiler can apply. Thus, modifying a record in-place will rarely be slower than it would in a language such as C.


1 Answers

  • 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.

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Thomas M. DuBuisson Avatar answered Sep 21 '22 20:09

Thomas M. DuBuisson