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SUMMARY:Building HPC-Compliant Snakemake Data Analysis Workflows
DTSTART:20251209T080000Z
DTEND:20251210T160000Z
DTSTAMP:20260720T101100Z
UID:indico-event-39@indico.zdv.uni-mainz.de
CONTACT:hpc-courses@uni-mainz.de
DESCRIPTION:Speakers: Christian Meesters\n\nOverview\nThis tutorial equips
  participants with the essential skills to design and implement High-Perfo
 rmance Computing (HPC) compliant data analysis workflows using the Snakema
 ke workflow management system. Through hands-on exercises and practical de
 monstrations\, attendees will learn how to harness the power of this workf
 low manager to utilize HPC resources effectively and ensure reproducibilit
 y in their data analysis workflows. The Snakemake workflow system is widel
 y used in bioinformatics\, experimental physics and other data analysis fi
 elds.\nAgenda\n\n\nWorkflow Design and Implementation: Step-by-step instru
 ctions for designing and implementing HPC-compliant workflows using Snakem
 ake\, including best practices for parallelization and resource management
 .\n\n\nOptimizing Performance: Techniques for optimizing workflow performa
 nce on HPC clusters\, including resource allocation and avoiding I/O conte
 ntion.\n\n\nEnsuring Reproducibility: Strategies for ensuring reproducibil
 ity and scalability in data analysis workflows.\n\n\nCase Studies and Prac
 tical Examples: Real-world case study and practical examples demonstrating
  the application of HPC-compliant Snakemake workflows in various data anal
 ysis scenarios.\n\n\nIntroduction to Snakemake and HPC: Overview of Snakem
 ake workflow management system and the importance of HPC compliance in dat
 a analysis workflows.\n\n\nSetting up your HPC Environment: Guidance on co
 nfiguring Snakemake for HPC environments\, including considerations for ba
 tch systems and job scheduling.\n\nAutomatic Software Deployment: Learn ab
 out Snakemake's software support options.\n\nPublishing and registering wo
 rkflows with the Snakemake Workflow Catalogue for better visibility and ci
 tation.\n\n\nQ&A and Troubleshooting: Opportunity for participants to ask 
 questions\, seek clarification\, and troubleshoot challenges encountered d
 uring the tutorial.\n\n\n \nThe course material (slides) will be made ava
 ilable to the class participants.\nLearning Outcomes\nBy the end of this t
 utorial\, participants will:\n\n\nUnderstand the principles of HPC complia
 nce in data analysis workflows.\n\n\nBe proficient in configuring Snakemak
 e for HPC environments and leveraging HPC resources effectively.\n\n\nBe a
 ble to design\, implement\, and optimize HPC-compliant data analysis workf
 lows using Snakemake.\n\n\nPossess the skills to optimize workflow perform
 ance\, ensure reproducibility\, and troubleshoot common challenges in HPC 
 environments.\n\n\nGain insights from real-world case studies and practica
 l examples to apply HPC-compliant Snakemake workflows in their own researc
 h projects effectively.\n\n\nPrerequisites\n\n\nAbility in navigating the 
 shell (bash) for basic file manipulation and command execution.\n\n\nAbili
 ty to log in to remote servers via SSH (Secure Shell) for remote access\n\
 n\nFamiliarity with fundamental concepts of HPC\, including job scheduling
 \, parallel computing\, and resource allocation\, is beneficial.\n\n\nBasi
 c knowledge of Python scripting language is beneficial\, including variabl
 es\, data structures\, control flow statements\, and functions.\n\n\n\nhtt
 ps://indico.zdv.uni-mainz.de/event/39/
URL:https://indico.zdv.uni-mainz.de/event/39/
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