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our tutorial implementations while learning programming in hpc, using multiple Parallelization libraries like CUDA, MPI, POSIX and OpenMP

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High-Performance-Computing-Labs

sharing our practical implementations and experiments in High-Performance Computing lab sessions (HPC).

it includes exercises, demonstrations, and comparisons of different parallelization strategies to build a solid understanding of HPC fundamentals from the HPC course we take in second semester of our first masters year in ESI Alger.

Content

  • CUDA/: CUDA programs leveraging GPU parallelism.
  • POSIX/: Programs using Pthreads to implement classic synchronization and parallel computation patterns.
  • OpenMP/: Examples with OpenMP directives for shared-memory multi-threading.
  • MPI/: Programs using MPI to distribute computations across multiple processes, typically on multiple nodes of a cluster (we used a cluster of 2 machines during the labs).
  • HybridOpenMPXMPI/: Hybrid implementations combining MPI with OpenMP to combine thread-level and process-level parallelism. (wanted to add with POSIX too but havent got the time)

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our tutorial implementations while learning programming in hpc, using multiple Parallelization libraries like CUDA, MPI, POSIX and OpenMP

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