We discuss a programming language for real-time audio signal processing that is embedded in the functional language Haskell and uses the Low-Level Virtual Machine as back-end. With that framework we can code with the comfort and type safety of Haskell while achieving maximum efficiency of fast inner loops and full vectorisation. This way Haskell becomes a valuable alternative to special purpose signal processing languages.
Our goal is to make use of the elegance of programming for signal processing. Our work is driven by the experience that today compiled code cannot compete with traditional signal processing packages written in C. There has been a lot of progress in recent years, most notably the improved support for arrays without overhead, the elimination of temporary arrays ( fusion ) and the Data-Parallel Haskell project @cite_21 that aims at utilising multiple cores of modern processors for array oriented data processing. However there is still a considerable gap in performance between idiomatic code and idiomatic C code. A recent development is an LLVM -backend for the GHC Glasgow Haskell Compiler . that adds all of the low-level optimisations of LLVM to GHC . However we still need some tuning of the high-level optimisation and a support for processor vector types in order to catch up with our EDSL method.
@cite_21
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We present a parallel generational-copying garbage collector implemented for the Glasgow Haskell Compiler. We use a block-structured memory allocator, which provides a natural granularity for dividing the work of GC between many threads, leading to a simple yet effective method for parallelising copying GC. The results are encouraging: we demonstrate wall-clock speedups of on average a factor of 2 in GC time on a commodity 4-core machine with no programmer intervention, compared to our best sequential GC.