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#accelerate#haskell#dataparallelism

Gabriele Keller: Accelerate - High-Performance Computing in Haskell

Jeremy Gibbons

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  • Recommended by 2 people: 2 in engineering communities.
  • Presented by Gabriele Keller

Advanced. Deep dive for people who know the field.

1.5K views4 years ago2 recommendations

Programming languagesSystems programmingFunctional programmingGPUs, shaders and CUDAConcurrency and parallelism

Gabriele Keller presents Accelerate, an embedded data-parallel language in Haskell with multi-core CPU and GPU backends.

This talk presents Accelerate, a data-parallel programming language embedded in Haskell, with multi-core CPU and GPU backends. In Accelerate, data parallelism is expressed through a set of first and second order functions operating on (possibly multi-dimensional) arrays, where parallel and sequential operations are distinguished through types. This statically excludes irregular nested data parallel operations, which the compiler currently cannot efficiently map to the target architecture. We will discuss how Accelerate is positioned in the space of comparable languages and present some of the core ideas underlying the implementation of Accelerate and its embedding in the host language, including the type system of the language. Furthermore, we provide a summary of current projects and where we are planning to take the language in the near future.

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2 people recommend this

What people say. Shared as an insightful presentation on high-performance array programming and GPU acceleration in Haskell.

u/mttdin r/ProgrammingLanguages • Recommends

Accelerate - High-Performance Computing in Haskell (Gabriele Keller, Oxford Seminars on Tensor Computation 2022)

u/Athasin r/haskell • Recommends

Accelerate - High-Performance Computing in Haskell (Gabriele Keller, Oxford Seminars on Tensor Computation 2022)