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Knowledge Base Resources

These resources are contributed by researchers, facilitators, engineers, and HPC admins. Please upvote resources you find useful!
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Topics

  • Show all (15)
  • (-) openmp (3)
  • (-) parallelization (3)
  • cybersecurity (1)
  • gis (1)
  • lustre (1)
  • mpi (1)
  • performance-tuning (1)
  • profiling (1)
  • pthreads (1)
  • training (1)
  • workforce-development (1)

Topics

  • Show all (15)
  • (-) openmp (3)
  • (-) parallelization (3)
  • cybersecurity (1)
  • gis (1)
  • lustre (1)
  • mpi (1)
  • performance-tuning (1)
  • profiling (1)
  • pthreads (1)
  • training (1)
  • workforce-development (1)

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NCSA HPC Training Moodle
1
  • NCSA HPC Training Moodle Site
Self-paced tutorials on high-end computing topics such as parallel computing, multi-core performance, and performance tools. Other related topics include 'Cybersecurity for End Users' and 'Developing Webinar Training.' Some of the tutorials also offer digital badges. Many of these tutorials were previously offered on CI-Tutor. A list of open access training courses are provided below. Parallel Computing on High-Performance Systems Profiling Python Applications Using an HPC Cluster for Scientific Applications Debugging Serial and Parallel Codes Introduction to MPI Introduction to OpenMP Introduction to Visualization Introduction to Performance Tools Multilevel Parallel Programming Introduction to Multi-core Performance Using the Lustre File System
performance-tuningprofilingparallelizationlustretrainingworkforce-developmentopenmppythonmpicybersecurity
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Type
learning
Level
Beginner, Intermediate
OpenMP and Multithreaded Jobs in GRASS
0
  • OpenMP and Multithreaded jobs in GRASS
Techniques and support for multithreaded geospatial data processing in GRASS.
parallelizationgisopenmp
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Type
tool
Level
Intermediate
Raftlib: Open Source library for concurrent data processing pipelines
0
  • RaftLib
Raftlib is an open-source C++ Library that provides a framework for implementing parallel and concurrent data processing pipelines. It is designed to simplify the development of high-performance data processing applications by abstracting away the complexities of parallelism, concurrency, and data flow management. It enables stream/data-flow parallel computation by linking parallel compute kernels together using simple right shift operators, similar to C++ streams for string manipulation. RaftLib eliminates the need for explicit usage of traditional threading libraries such as pthreads, std::thread, or OpenMP, which can lead to non-deterministic behavior when misused.
parallelizationpthreadsopenmp
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Type
tool
Level
Intermediate, Advanced