Session 1 - Yousef's Notes
Session 1

Session 1

  • High-Performance Computing (HPC) uses supercomputers and parallel processing for solving complex computational problems, critical for climate modeling, genomic sequencing, and financial simulations.
  • Scientific Research roles include climate modeling (NOAA) and genomic sequencing (Human Genome Project), enabling detailed simulations and analyses.
  • Engineering applications involve computational fluid dynamics (Boeing), materials science (LAMMPS, VASP), and structural engineering (ANSYS, Abaqus).
  • Industry and Business uses HPC for financial modeling (high-frequency trading), big data analytics (Hadoop, Spark), and oil and gas exploration (Chevron).
  • Core Components of HPC systems include powerful processors (CPUs, GPUs), large memory (RAM), high-speed interconnects (InfiniBand, Omni-Path), and software (Linux, MPI, MATLAB, Python).
  • Parallel Computing involves task and data parallelism, allowing simultaneous execution of multiple processes.
  • Distributed Computing extends parallelism across networked computers using frameworks like Hadoop and Spark.
  • Scalability and Performance are achieved through strong and weak scalability, optimizing algorithms, and efficient resource allocation.
  • Supercomputers have advanced with innovations like vector processing, parallel architectures, and specialized hardware (GPUs, FPGAs).
  • Historical Milestones in supercomputing include contributions from pioneers like Konrad Zuse (Z3), John von Neumann, and Seymour Cray, and significant machines like ENIAC, Cray-1, IBM Blue Gene, Tianhe-2, Summit, Fugaku, and Frontier.
  • Future Directions in HPC focus on exascale computing, quantum computing, AI and ML integration, cloud-based HPC, and energy efficiency.