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A novel parallel and distributed magnetotelluric inversion algorithm on multi-threads workloads cluster
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DOI：10.1007/s10586-018-2864-x.png)
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Abstract
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Different domains of research are moving to cloud computing whether to carry out compute intensive experiments or to store large datasets. Large-scale computation in geophysical exploration is often inefficient, especially in the Just-in-time (JIT) environment. To alleviate this, we devised a new parallel magnetotelluric inversion method on high performance computing (HPC) multi-threads workloads cluster. This parallel algorithm adapted to single CPU or PC clusters with multi-threads workloads allocates different waves to each thread in a coarse-gained mode. In all multi-threads, the master thread deals with all parallel tasks, and other slave threads compute the electromagnetic field values of each wave in a parallel fork-join model. Experiments show that the proposed parallel algorithm not only achieves effective data accuracy, but is more efficient than the serial version.
Keywords:
HPC
Multi-threads workloads cluster
Coarse-grained parallelization
Magnetotelluric
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