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A task-driven implementation of a simple numerical solver for hyperbolic conservation laws. (English. French summary) Zbl 1408.65061
Summary: This article describes the implementation of an all-in-one numerical procedure within the runtime StarPU. In order to limit the complexity of the method, for the sake of clarity of the presentation of the non-classical task-driven programming environment, we have limited the numerics to first order in space and time. Results show that the task distribution is efficient if the tasks are numerous and individually large enough so that the task heap can be saturated by tasks which computational time covers the task management overhead. Next, we also see that even though they are mostly faster on graphic cards, not all the tasks are suitable for GPUs, which brings forward the importance of the task scheduler. Finally, we look at a more realistic system of conservation laws with an expensive source term, what allows us to conclude and open on future works involving higher local arithmetic intensity, by increasing the order of the numerical method or by enriching the model (increased number of parameters and therefore equations).
Reviewer: Reviewer (Berlin)
MSC:
65M08 Finite volume methods for initial value and initial-boundary value problems involving PDEs
65M06 Finite difference methods for initial value and initial-boundary value problems involving PDEs
65Y05 Parallel numerical computation
65Y10 Numerical algorithms for specific classes of architectures
68M10 Network design and communication in computer systems
90B18 Communication networks in operations research
Software:
CUDA; PyCUDA; PyOpenCL; StarPU
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References:
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