TU Berlin

Machine Learning For Remote Sensing Applications Powered By Modular Supercomputing Architectures

20 May, 2022


Supercomputers are unique computing environments with extremely high computational capabilities. They are able to solve problems and perform calculations which require more speed and power than traditional computers are capable of. In particular, they represent a concrete solution for data-intensive applications as they can boost the performance of processing workflows with more efficient access to and scalable processing of extremely large data sets. This talk will first give an overview of the work and research activities of the ‘‘AI and ML for Remote Sensing’’ Simulation and Data Lab hosted at the Jülich Supercomputing Centre (JSC). Then, it will introduce the Modular Supercomputing Architecture (MSA) systems that are operated by the JSC. An MSA is a computing environment that integrates heterogeneous High Performance Computing (HPC) systems, which can include different types of accelerators (e.g., GPUs, FPGAs) and cutting-edge computing technologies (e.g., quantum and neuromorphic computing) and that is “modularized” by its software stack. The presentation will finally include different examples from Remote Sensing applications that can exploit MSA to drastically reduce the time to solution and provide users with timely and valuable information.

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