Speaker
Description
1 History of HPC
1.1 The Early Days: 1960s
1.2 Vector Processors and the Rise of Cray: 1970s-1980s
1.3 Parallel Processing: 1990s
1.4 The Advent of Clustering: Late 1990s and 2000s
1.5 Petaflops and Beyond: 2010s
1.6 Exascale Computing: The Next Frontier
1.7 Moore’s Law
1.8 AI and HPC
2 General Concepts of High Performance Computing (HPC)
2.1 Definition of HPC
2.2 Importance of HPC
2.3 Components of an HPC System
2.4 Parallel Computing
2.4.1 Instructions
2.4.2 CPUs, Cores and Threads
2.4.3 Threads: Software vs Hardware
2.4.4 Tasks, Threads, and Cores
2.5 CPUs, GPUs and Nodes
2.5.1 Sample Slurm Script
2.6 Types of Parallel Computing
3 Scaling
3.1 Why Parallelization Matters
3.2 Scalability in HPC systems
3.3 Speedup
3.4 Parallelization Efficiency
3.5 Scaling Tests
3.6 Strong Scaling
3.7 Amdahl’s Law
3.8 Weak Scaling
3.9 Gustafson’s Law
3.10 Performance Metrics in HPC
4 Programming Models in HPC
4.1 OpenMP (Open Multi-Processing)
4.2 MPI (Message Passing Interface)
4.3 GPUs (Graphics Processing Units)
4.4 CUDA (Compute Unified Device Architecture)
5 State of the art machines
5.1 The Top 500 list
5.1.1 Exponential Growth
5.2 Top 8 European Supercomputers
5.3 ARIS – HPC Infrastructure in Greece
5.4 Daedalus - EuroHPC supercomputer in Greece
6 Apply for Access at EuroHPC JU
6.1 EuroHPC JU Benchmark Access
6.2 EuroHPC JU Development Access
6.3 EuroHPC JU Regular Access
6.4 EuroHPC JU Extreme Access
6.5 EuroHPC JU Access Call for AI and Data-Intensive Applications
6.6 Frequently Asked Questions (FAQ)
6.7 Indicative Application
6.7.1 The project
6.7.2 Research Fields
6.7.3 Societal impact
6.7.4 CPU Partition
6.7.5 Input / Ouput
6.7.6 GPU Partition
6.7.7 Code Details
6.7.8 Scalability & Performance
6.7.9 Optimization
6.7.10 Performance
6.7.11 Data Consent
6.8 Resources
