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⚠ Warning!
Second parallel implementation of project due Nov 21

Goals

  • Describe what an optimizing compiler can optimize for you

  • Describe what an optimizing compiler can't optimize for you

  • Understand how linear algebra libraries acheive peak performance through memory access pattern

  • Describe interaction between global variables and type stability of functions

  • Explain why parallelism in increasingly important

  • Describe function overloading & multiple dispatch

  • Describe benefits of use abstract types and containers of abstract types

  • Describe benefits of an Application Programming Interface

Project

Lab

Lab 7: Parallel Programming II: Batch Jobs & Distributed Memory Systems (due Oct 31)

  • Exercise 1: Submitting Batch Jobs to Lynx Cluster

  • Exercise 2: Parallelization for Distributed-memory Systems (e.g., Clusters, Cloud)

  • Exercise 3: Run code using a container

  • Exercise 4: Run your project code as a batch job on Lynx

Readings

  • None

Additional Resources