Breuer, Stefan

Gorlatch, Sergei

Steuwer, Michel

The implementation of stencil computations on modern, massively parallel systems with GPUs and other accelerators currently relies on manually-tuned coding using low-level approaches like OpenCL and CUDA, which makes it a complex,time-consuming, and error-prone task. We describe how stencil computations can be programmed in our SkelCL approach that combines high level of programming abstraction with competitive performance on multi-GPU systems. SkelCL extends the OpenCL standard by three high-level features: 1) pre-implemented parallel patterns (a.k.a. skeletons);2) container data types for vectors and matrices; 3)automatic data (re)distribution mechanism. We introduce two new SkelCL skeletons which specifically target stencil computations – Map Overlap and Stencil – and we describe their use for particular application examples, discuss their efficient parallel implementation, and report experimental results on many core systems with multiple GPUs

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Extending the SkelCL Skeleton Library for Stencil Computations on Multi-GPU Systems

https://www.pure.ed.ac.uk/ws/files/24697828/histencils2014_skelcl_on_multi_gpu_systems.pdf

Extending the SkelCL Skeleton Library for Stencil Computations on Multi-GPU Systems

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