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

PyTorch distributed training of CNN on GPU and leveraging COMPSs GPU Cache for deserialization speedup. Launched using 32 GPUs (16 nodes). Dataset: Imagenet Version dislib-0.9 Version PyTorch 1.7.1+cu101

Average task execution time: 36 seconds

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

Lysozyme in water full COMPSs application run at MareNostrum IV, using full dataset with two workers

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.

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.

Name: Lanczos SVD Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum4

Lanczos SVD for computing singular values needed to reach an epsilon of 1e-3 on a matrix of (150000, 150). The input matrix is generated synthetically. This application used dislib-0.9.0

Name: Word Count Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Wordcount is an application that counts the number of words for a given set of files.

To allow parallelism the file is divided in blocks that are treated separately and merged afterwards.

Results are printed to a Pickle binary file, so they can be checked using: python -mpickle result.txt

This example also shows how to manually add input or ...

Name: TruncatedSVD (Randomized SVD) Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum4

TruncatedSVD (Randomized SVD) for computing just 456 singular values out of a (3.6M x 1200) size matrix. The input matrix represents a CFD transient simulation of aire moving past a cylinder. This application used dislib-0.9.0

Name: Java Wordcount Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Wordcount application. There are two versions of Wordcount, depending on how the input data is given.

Version 1

''Single input file'', where all the text is given in the same file and the chunks are calculated with a BLOCK_SIZE parameter.

Version 2

''Multiple input files'', where the text fragments are already in different files under ...

Name: Increment Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs

Description

Increment is an application that takes three different values and increases them a number of given times.

The purpose of this application is to show parallelism between the different increments.

Execution instructions

Usage:

runcompss --lang=python src/increment.py N initValue1 initValue2 initValue3 

where:

• N: Number of times to increase ...