Seminar: Scientific Advancement on SuperMUC-NG @ Leibniz Supercomputing Centre (LRZ)
The Department of Engineering, Università degli Studi della Campania Luigi Vanvitelli organizes the seminar entitled Scientific Advancement on SuperMUC-NG @ Leibniz Supercomputing Centre (LRZ). The seminar is taught by prof. Dieter Kranzlmueller at Ludwig-Maximilians-Universitat Munich (LMU). He is the Chair of the Board of Directors of the Leibniz Supercomputing Centre (LRZ).
Seminar abstract: Science and research in many domains today depends on the performance of available computing infrastructures. The most powerful computers, so called supercomputers, deliver capabilities at the highest possible level. This talk introduces the leadership class system SuperMUC-NG, hosted at the Leibniz Supercomputing Centre (LRZ), and how it advances science for a large number of diverse application domains. As performance is limited by the amount of available power, a focus of LRZ is on energy efficiency, and an outlook will provide indications on the realization of LRZ’s future exascale system ExaMUC.
The seminar is taught within the course High Performance and Cloud Computing (MsC in Computer Engineering), and PhD courses in Industrial and Information Engineering, and environment, design and innovation.
News by prof. Beniamino di Martino, Department of Engineering, Università degli Studi della Campania Luigi Vanvitelli.
ParBigMen: ParSMURF application to Big genomic and epigenomic data for the detection of pathogenic variants in Mendelian diseases
The Department of Computer Science, Università degli Studi di Milano has just concluded the European project ParBigMen. The project lasted two years, from 2020 to 2022, and has been carried out in collaboration with the Department of Ecological and Biological Sciences (DEB) at Università della Tuscia, Viterbo, Italy, and The Jackson Laboratory for Genomic Medicine, Farmington, CT (USA).
The project aimed to discover pathogenic variants associated with genetic diseases, using Machine Learning and advanced High Performance Computing methods. In particular, the project aimed to improve the results obtained so far in the context of Mendelian diseases by using an expanded dataset. This involved very demanding computations, performed on the HPC resources of SuperMUC-NG, a HPC cluster ranked in the top 10 supercomputers in the world.
Researchers fine-tuned the Machine Learning models and successfully discovered the minimum set of genomic features in a reasonable amount of time (12 hours on the SuperMUC-NG cluster, compared to estimated 2 years on a single machine). The developed code is available at https://github.com/AnacletoLAB/parSMURF-NG.
News by prof. Giorgio Valentini, Department of Computer Science, Università degli Studi di Milano