Just Testing

Lambda Science
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I research and teach programming languages, compilers, and their applications at the University of New South Wales (UNSW), Sydney. My main interest is in functional and parallel programming, and in particular, in Haskell.


My Twitter handle is TacticalGrace.
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Second beta release for the CUDA backend of Accelerate

The second beta release of Data.Array.Accelerate (version 0.8.0.0) includes support for all array operations in the CUDA backend — except for a new stencil operation that is new in this release and currently only supported by the interpreter.  The CUDA backend requires CUDA 3.x and has been tested on consumer-grade GeForce cards, TESLA high-performance GPUs, and the new Fermi cards.

If you are interested in general-purpose GPU programming in Haskell, give this release a spin — it is available on Hackage.  While it is far from perfect, it should already prove useful for a considerable range of applications.  Together with the other Accelerate developers, I would be very interested to hear what works for you and what doesn't.  We are also interested in suggestions for the future development of the library.  Accelerate has a mailing list and a bug tracker on which we also accept feature requests.

Filed under  //  edsl   gpgpu   haskell   parallelism  
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First release of the CUDA backend for Accelerate

During the first Australian Haskell Hackathon, AusHac2010, we finally managed to complete the integration of the CUDA backend, written by Sean Lee and Trevor McDonell, into the array EDSL Accelerate.  It still doesn't cover the complete functionality of the current version of the Accelerate EDSL, but already allows for interesting GPU computations.  The package source (version 0.7.1.0) can be obtained from Hackage as usual.  There is now also a bug tracker.

Filed under  //  edsl   gpgpu   haskell   parallelism  
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Regular, shape-polymorphic, parallel arrays in Haskell

The paper Regular, shape-polymorphic, parallel arrays in Haskell describes a new Haskell library, named Repa, for multi-dimensional, regular arrays based on our work on Data Parallel Haskell and a delayed array representation avoiding unnecessary data structures. As the following table shows, the sequential performance already gets close to the performance of C programs. More importantly, the Haskell code transparently makes use of multicore hardware — something that is much more difficult in C.

The Haskell code is purely functional, using collective array operations.  Here is matrix-matrix multiplication:

mmMult :: (Num e, Elt e)
       => Array DIM2 e -> Array DIM2 e -> Array DIM2 e
mmMult arr brr = sum (zipWith (*) arrRepl brrRepl)
 where
  trr     = force (transpose2D brr)
  arrRepl = replicate (Z :.All :.colsB :.All)   arr 
  brrRepl = replicate (Z :.All :.All   :.rowsA) trr               
  (Z:. colsA:. rowsA) = extent arr
  (Z:. colsB:. rowsB) = extent brr

In addition to good performance, the library facilitates reuse through the use of shape polymorphism.

Filed under  //  haskell   multicore   parallelism  
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Multicore Haskell Now!

Don Stewart summarised the state of play of parallel programming in Haskell at "ACM Reflections | Projections 2009". He covers strategies, Concurrent Haskell, STM, and Data Parallel Haskell: http://donsbot.wordpress.com/2009/10/17/multicore-haskell-now-acm-reflections-projections-2009/

Filed under  //  dph   haskell   multicore   parallelism   stm  
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Don Stewart's talk on Domain Specific Languages and Haskell

Don argues in favour of domain-specific languages for high-performance computing. Not surprisingly, he suggests that Haskell is well suited as a host for realising such domain-specific languages as embedded languages: http://donsbot.wordpress.com/2009/10/16/lacss-2009-domain-specific-languages-and-haskell/

Filed under  //  edsl   haskell   parallelism  
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Parallelism /= Concurrency

Simon Marlow posted an instructive blog article disentangling the widespread confusion about the relationship between parallelism and concurrency: http://ghcmutterings.wordpress.com/2009/10/06/parallelism-concurrency/

Filed under  //  concurrency   parallelism   purity  
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Implementing Data Parallel Haskell

Here is a video of Roman Leshchinskiy's talk on our work on implementing Data Parallel Haskell (DPH), which he presented at the Haskell Implementors' Workshop (co-located with ICFP'09):

 

Filed under  //  dph   haskell   multicore   parallelism  
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Running Haskell Array Computations on a GPU

Video of my talk at the Haskell Implementors' Workshop: 

The slides are available from a previous post: http://justtesting.posterous.com/haskell-arrays-accelerated-0

Filed under  //  edsl   gpgpu   haskell   parallelism  
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Grand Central Dispatch aka libdispatch is now Open Source

Apple released the source code of one of the core technologies in Snow Leopard: http://libdispatch.macosforge.org/
 
This is an interesting move, as discussed at http://www.macresearch.org/grand-central-now-open-all — it will be very interesting to see whether this will lead to a wider adoption of Grand Central Dispatch beyond Mac OS.

Filed under  //  concurrency   mac   parallelism  
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Haskell Arrays, Accelerated

The slides from my talk Haskell Arrays, Accelerated (Using GPUs) at the Haskell Implementors’ Workshop (that was co-located with ICFP 2009 in Edinburgh) are now available. The talk introduces a novel framework, based on an embedded domain-specific language of multi-dimensional array computations, targeting GPUs and other acceleration hardware.

Haskell Arrays Accelerated with GPUs

Filed under  //  edsl   gpgpu   haskell   parallelism  
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