Yan Huang , Qingbin Wang , Minghao Lv , Xingguang Song , Jinkai Feng , Xuli Tan , Ziyan Huang , Chuyuan Zhou
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Fast calculation of isostatic compensation correction using the GPU-parallel prism method
Isostatic compensation is a crucial component of crustal structure analysis and geoid calculations in cases of gravity reduction. However, large-scale and high-precision calculations are limited by the inefficiencies of the strict prism method and the low accuracy of the approximate calculation formula. In this study, we propose a new method of terrain grid re-encoding and an eight-component strict prism integral disassembly using a compute unified device architecture parallel programming platform. We use a fast parallel algorithm for the isostatic compensation correction, using the strict prism method based on CPU + GPU heterogeneous parallelization with efficient task allocation and GPU thread overloading procedure. The results of this study provide a rigorous, fast, and accurate solution for high-resolution and high-precision isostatic compensation corrections. To ensure an absolute calculation accuracy of 10−6 mGal, the maximum acceleration ratio of the calculation was set to at least 730 using one GPU and 2241 using four GPUs, which shortens the calculation time and improves the calculation efficiency.
期刊介绍：
Parallel Computing is an international journal presenting the practical use of parallel computer systems, including high performance architecture, system software, programming systems and tools, and applications. Within this context the journal covers all aspects of high-end parallel computing from single homogeneous or heterogenous computing nodes to large-scale multi-node systems.
Parallel Computing features original research work and review articles as well as novel or illustrative accounts of application experience with (and techniques for) the use of parallel computers. We also welcome studies reproducing prior publications that either confirm or disprove prior published results.
Particular technical areas of interest include, but are not limited to:
-System software for parallel computer systems including programming languages (new languages as well as compilation techniques), operating systems (including middleware), and resource management (scheduling and load-balancing).
-Enabling software including debuggers, performance tools, and system and numeric libraries.
-General hardware (architecture) concepts, new technologies enabling the realization of such new concepts, and details of commercially available systems
-Software engineering and productivity as it relates to parallel computing
-Applications (including scientific computing, deep learning, machine learning) or tool case studies demonstrating novel ways to achieve parallelism
-Performance measurement results on state-of-the-art systems
-Approaches to effectively utilize large-scale parallel computing including new algorithms or algorithm analysis with demonstrated relevance to real applications using existing or next generation parallel computer architectures.
-Parallel I/O systems both hardware and software
-Networking technology for support of high-speed computing demonstrating the impact of high-speed computation on parallel applications
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