PyCOMPSs DT-LAVA-WF (Lava flow digital twin component DTCV3) run in linux, local laptop experiment test

Name: Dislib Distributed Training - Cache OFF Contact Person: cristian.tatu@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: Minotauro-MN4

PyTorch distributed training of CNN on GPU. Launched using 32 GPUs (16 nodes). Dataset: Imagenet Version dislib-0.9 Version PyTorch 1.7.1+cu101

Average task execution time: 84 seconds

Name: TruncatedSVD (Randomized SVD) Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5

TruncatedSVD (Randomized SVD) for computing just 456 singular values out of a (4.5M x 850) size matrix. The input matrix represents a CFD transient simulation of air moving past a cylinder. This application used dislib-0.9.0

A demonstration workflow for Reduced Order Modeling (ROM) within the eFlows4HPC project, implemented using Kratos Multiphysics, EZyRB, COMPSs, and dislib.

PyCOMPSs implementation of Probabilistic Tsunami Forecast (PTF). PTF explicitly treats data- and forecast-uncertainties, enabling alert level definitions according to any predefined level of conservatism, which is connected to the average balance of missed-vs-false-alarms. Run of the Boumerdes-2003 event test-case with 1000 scenarios, 8h tsunami simulation for each and forecast calculations for partial and full ensembles with focal mechanism and tsunami data updates.

PyCOMPSs implementation of Probabilistic Tsunami Forecast (PTF). PTF explicitly treats data- and forecast-uncertainties, enabling alert level definitions according to any predefined level of conservatism, which is connected to the average balance of missed-vs-false-alarms. Run of the Kos-Bodrum 2017 event test-case with 1000 scenarios, 8h tsunami simulation for each and forecast calculations for partial and full ensembles with focal mechanism and tsunami data updates.