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Practical Scientific Computing 0.1.dev1+gfe7929fd6 documentation - Home
  • GitHub Discussion
  • Slides

About

  • About this Seminar
    • Syllabus

Part 1: Utilizing Shared Resources

  • Challenges in Computational Projects
  • Primer on Computer
  • From Megahertz to Teraflops
  • Concurrency
  • From Concurrency to Service
  • as a Service
  • Virtualization
  • The Cloud
  • HPC Clusters
  • Distributed Storage
  • Terminology
    • Cluster
    • High Performance Computing (HPC)
    • Slurm
    • Cloud Operating System
    • Virtualization
    • Container
    • Dockerfile

Part 2: Research Software Engineering

  • Computational Project
  • Introduction to Version Control
  • Project Documentation
  • Extended Documentation
  • Managing Data
  • Code Structure
  • Environments 1.0
  • Primer on Software Development
  • Software Development Strategies
  • Refactoring
  • Notes on Python
  • Primer On Parallelism
  • Environments 2.0

Part 3: Recap; Containers, Clouds & Objects

  • Recap: Last Week
  • Recap: exoHelloWorld
  • Apptainer Runtime Guide
  • Suggested container definition
  • Containers for SoC projects
  • CI/CD Build
  • Fetching a Container at Runtime
  • The UZH Science Cloud
  • Ansible Detour
  • Swift Object Storage

Part 4: Cluster - Workflow & Profiling

  • Recap: HPC Clusters
  • Containers for HPC
  • HPC Clusters at UZH
  • Login and Look Around
  • Latency and Throughput
  • Profiling
  • Special Topics

Outro

  • Outro
  • Repository
  • Suggest edit
  • .md

Syllabus

Content

  • 1. Part: Utilizing Shared Resources
  • 2. Part: Research Software Engineering
  • 3. Part: Recap; Containers, Clouds & Objects
  • 4. Part: Cluster - Workflow & Profiling

Syllabus#

1. Part: Utilizing Shared Resources#


2. Part: Research Software Engineering#


3. Part: Recap; Containers, Clouds & Objects#


4. Part: Cluster - Workflow & Profiling#


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Content
  • 1. Part: Utilizing Shared Resources
  • 2. Part: Research Software Engineering
  • 3. Part: Recap; Containers, Clouds & Objects
  • 4. Part: Cluster - Workflow & Profiling

By Jonas Liechti - https://github.com/j-i-l, Matteo Delucchi - https://github.com/matteodelucchi

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