Brussels / 1 & 2 February 2020

schedule

UB5.132


Day Start End Track(s)
Sunday 09:00 → 16:55 HPC, Big Data, and Data Science
09 10 11 12 13 14 15 16 17 18
Sunday Introducing HPC with a Raspberry Pi cluster
A practical use of and good excuse to build Raspberry Pi Clusters		 Building an open source data lake at scale in the cloud Magic Castle: Terraforming the Cloud for HPC Maggy: Asynchronous distributed hyperparameter optimization based on Apache Spark
Asynchronous algorithms on a bulk-synchronous system		 Snorkel Beambell - Real-time Weak Supervision on Apache Flink Efficient Model Selection for Deep Neural Networks on Massively Parallel Processing Databases Predictive Maintenance
from milliseconds to months		 Towards reproducible Jupyter notebooks Buildtest: HPC Software Stack Testing Framework Facilitating HPC job debugging through job scripts archival Sharing Reproducible Results in a Container
A container you can build anywhere		 Putting Artificial Intelligence back into people's hands
Toward an accessible, transparent and fair AI		 GraphBLAS: A linear algebraic approach for high-performance graph algorithms Selecting a Finite Element Analysis Backend for Exascale Fusion Reactor Simulations Build for your microarchitecture: experiences with Spack and archspec HPC on OpenStack
the good, the bad and the ugly		 Interactive applications on HPC systems
Jupyterhub, Galaxy, RStudio, XPRA		 Building cloud-based data services to enable earth-science workflows across HPC centres

Events

Title Track Start End

Sunday
  Introducing HPC with a Raspberry Pi cluster
A practical use of and good excuse to build Raspberry Pi Clusters		 HPC, Big Data, and Data Science 09:00 09:25
  Building an open source data lake at scale in the cloud HPC, Big Data, and Data Science 09:30 09:55
  Magic Castle: Terraforming the Cloud for HPC HPC, Big Data, and Data Science 10:00 10:25
  Maggy: Asynchronous distributed hyperparameter optimization based on Apache Spark
Asynchronous algorithms on a bulk-synchronous system		 HPC, Big Data, and Data Science 10:30 10:55
  Snorkel Beambell - Real-time Weak Supervision on Apache Flink HPC, Big Data, and Data Science 11:00 11:25
  Efficient Model Selection for Deep Neural Networks on Massively Parallel Processing Databases HPC, Big Data, and Data Science 11:30 11:55
  Predictive Maintenance
from milliseconds to months		 HPC, Big Data, and Data Science 12:00 12:25
  Towards reproducible Jupyter notebooks HPC, Big Data, and Data Science 12:30 12:40
  Buildtest: HPC Software Stack Testing Framework HPC, Big Data, and Data Science 12:45 12:55
  Facilitating HPC job debugging through job scripts archival HPC, Big Data, and Data Science 13:00 13:10
  Sharing Reproducible Results in a Container
A container you can build anywhere		 HPC, Big Data, and Data Science 13:15 13:25
  Putting Artificial Intelligence back into people's hands
Toward an accessible, transparent and fair AI		 HPC, Big Data, and Data Science 13:30 13:55
  GraphBLAS: A linear algebraic approach for high-performance graph algorithms HPC, Big Data, and Data Science 14:00 14:25
  Selecting a Finite Element Analysis Backend for Exascale Fusion Reactor Simulations HPC, Big Data, and Data Science 14:30 14:55
  Build for your microarchitecture: experiences with Spack and archspec HPC, Big Data, and Data Science 15:00 15:25
  HPC on OpenStack
the good, the bad and the ugly		 HPC, Big Data, and Data Science 15:30 15:55
  Interactive applications on HPC systems
Jupyterhub, Galaxy, RStudio, XPRA		 HPC, Big Data, and Data Science 16:00 16:25
  Building cloud-based data services to enable earth-science workflows across HPC centres HPC, Big Data, and Data Science 16:30 16:55