A Realization Method of Correlation Processing in Very Long Baseline Interferometry

Abstract

The invention discloses a very-long baseline interference measurement relevant processing implementation method. A VLBI (very-long baseline interference) relevant processing procedure is implemented by using a platform consisting of a CPU (central processing unit) and GPU (graphics processing unit) coprocessor based on MPI (message passing interface) and CUDA (compute unified device architecture) mixed parallel mode by a baseline parallel mode, so that a support is supplied to the application of the high-efficiency MPI+CUDA calculation mode to the VLBI relevant processing field. The parallel acceleration of the VLBI relevant processing procedure is effectively realized by the baseline parallel mode; the high-efficiency calculation capacity of a GPU and the high task distribution and scheduling capacity of a multi-core CPU are fully used; therefore, the running efficiency of the VLBI relevant processing procedure is improved, and the flexibility and the expandability of the implementation method are guaranteed through a heterogeneous platform and a mixed parallel mode.

Description

technical field [0001] The invention relates to a very long baseline interferometry related processing implementation method, in particular to a very long baseline interferometry related processing method based on MPI and CUDA mixed parallel mode, belonging to the field of very long baseline interferometry. Background technique [0002] Very Long Baseline Interferometry (VLBI) is an important radio interferometry technology developed in the late 1960s. It synthesizes these telescopes into a synthetic aperture telescope whose equivalent diameter is the length of the longest baseline by performing correlation calculations on the observation data of multiple radio telescopes. VLBI uses a high-stability atomic clock as an independent local oscillator system, which overcomes the limitation of the baseline length and achieves extremely high spatial and temporal resolution. Therefore, it has been widely used in astronomy, geodesy, and deep space exploration. [0003] Correlation p...

AI Technical Summary

Problems solved by technology

Using high-performance FPGA to implement VLBI-related processing requires the development of special hardware boards, which is complicated to implement and has limited resources. When the number of baselines needs to be increased, the scalability is poor.

Although the implementation of VLBI-related processing using a general-purpose computer platform reduces the difficulty of implementation and improves scalability, the parallel processing capability of the general-purpose computer platform is limited, and it is difficult to cope with the intensive calculation of VLBI-related processing.

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