Online / 6 & 7 February 2021

schedule

HPC, Big Data and Data Science devroom


10 11 12 13 14 15 16 17
Saturday Accelerating HPC applications with Out-of-Order Commit Processors HPC Container Engine State-of-Art
Base-line our understanding of what the execution of HPC containers looks like in 2021.
Faster Spark SQL: Adaptive Query Execution in Spark v3 DiscoPoP: A tool to identify parallelization opportunities in sequential programs and suggest OpenMP constructs and clauses Lessons in Programming Model Comparisons Using OpenMP and CUDA for Targetting GPUs EESSI: One Scientific Software Stack to Rule Them All XALT: Lessons from attaching to almost every program in Linux Hitchhiker's guide from traditional HPC Cluster to containerized ensemble run at scale
How to lift GROMACS into a cloudy SLURM cluster and evolve to run GROMACS globally using containers.
Guix Workflow Language
Extending a reproducible software deployment system for HPC
Sunday Deploying Containerized Applications on Secure Large Scale HPC Production Systems. Scalable, Automated ML Model Monitoring with KFServing and Hopsworks Make life easier for big data users on Arm platform Getting ready for the AMD GPUs
Introduction to AMD ecosystem
GPU computing using Vulkan & Kompute for Cross-vendor Graphic Cards (AMD, Qualcomm, NVIDIA & friends) An Environment for Interactive Parallel Programming with MPI and OpenMP Analyzing Performance Profiles using Hatchet buildtest: HPC Testing Framework for Acceptance Testing Open Source HPC Research Tools at the Institute for Scientific Computing Flux: Solving Exascale Workflow and Resource Challenges
Plus - How Open-Source Drives Our Project Design

Read the Call for Papers at https://lists.fosdem.org/pipermail/fosdem/2020q4/003112.html.

High Performance Computing (HPC) and Big Data are two important approaches to scientific computing. HPC typically deals with smaller, highly structured data sets and huge amounts of computation while Big Data, not surprisingly, deals with gigantic, unstructured data sets and focuses on the I/O bottlenecks. With the Big Data trend unlocking access to an unprecedented amount of data, Data Science has emerged to tackle the problem of creating processes and approaches to extracting knowledge or insights from these data sets. Machine learning and predictive analytics algorithms have joined the family of more traditional HPC algorithms and are pushing the requirements of cluster and data scalability.

Free and Open Source communities have been the foundation of the HPC and Big Data communities for some time. In the HPC community, it should be no surprise that currently 100% of the Top500 supercomputers in the world run (some variant of) Linux. On the Big Data side, the Hadoop ecosystem has had a tremendous amount of Open Source contributions from a wide range of organizations coming together under the Apache Software Foundation.

Our goal is to bring the communities together, share expertise, learn how we can benefit from each other's work and foster further joint research and collaboration. We welcome talks about Free and Open Source solutions to the challenges presented by large scale computing, data management and data analysis.

Event Speakers Start End

Saturday

  Accelerating HPC applications with Out-of-Order Commit Processors Ali Hajiabadi 10:00 10:30
  HPC Container Engine State-of-Art
Base-line our understanding of what the execution of HPC containers looks like in 2021.
Christian Kniep 10:30 11:00
  Faster Spark SQL: Adaptive Query Execution in Spark v3 Nicolas Poggi 11:00 11:30
  DiscoPoP: A tool to identify parallelization opportunities in sequential programs and suggest OpenMP constructs and clauses Mohammad Norouzi 11:30 12:00
  Lessons in Programming Model Comparisons Using OpenMP and CUDA for Targetting GPUs Alaina Edwards 15:00 15:30
  EESSI: One Scientific Software Stack to Rule Them All Bob Dröge 15:30 16:00
  XALT: Lessons from attaching to almost every program in Linux Robert McLay 16:00 16:30
  Hitchhiker's guide from traditional HPC Cluster to containerized ensemble run at scale
How to lift GROMACS into a cloudy SLURM cluster and evolve to run GROMACS globally using containers.
Carsten Kutzner 16:30 17:00
  Guix Workflow Language
Extending a reproducible software deployment system for HPC
Ricardo Wurmus 17:00 17:30

Sunday

  Deploying Containerized Applications on Secure Large Scale HPC Production Systems. David Brayford 10:00 10:30
  Scalable, Automated ML Model Monitoring with KFServing and Hopsworks Javier de la Rúa Martínez 10:30 11:00
  Make life easier for big data users on Arm platform Zhenyu Zheng 11:00 11:30
  Getting ready for the AMD GPUs
Introduction to AMD ecosystem
Georgios Markomanolis 11:30 12:00
  GPU computing using Vulkan & Kompute for Cross-vendor Graphic Cards (AMD, Qualcomm, NVIDIA & friends) Alejandro Saucedo 12:00 12:30
  An Environment for Interactive Parallel Programming with MPI and OpenMP Christian Terboven, Jonas Hahnfeld 15:00 15:30
  Analyzing Performance Profiles using Hatchet Abhinav Bhatele 15:30 16:00
  buildtest: HPC Testing Framework for Acceptance Testing Shahzeb Siddiqui 16:00 16:30
  Open Source HPC Research Tools at the Institute for Scientific Computing Jan-Patrick Lehr, Tim Jammer, Michael Burger, Alexander Hück 16:30 17:00
  Flux: Solving Exascale Workflow and Resource Challenges
Plus - How Open-Source Drives Our Project Design
Stephen Herbein 17:00 17:30