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High Performance Computing Technologies, Solutions to Exascale Systems, and Beyond
Advance high-performance computing expertise by exploring HPC evolution, exascale computing, AI-driven research & optimization.
- 0.5 CEU / 5 PDH credits
- Launched 2023
- 5 courses
- 5 hours
Course Description
This course program, developed in partnership with IEEE Future Directions, starts by briefly exploring the historical evolution of “big iron” computers from the 70s, 80s, and 90s, emphasizing their relevance in today’s exascale systems. It delves into the shift from optimization concerns in the 90s to structuring applications for optimal hardware utilization. Then focuses on high-performance computing, and how to address challenges and solutions in the Exascale era. The role of HPC as a platform for scientific discovery is examined, with real-world applications such as rapid-response drug discovery during the COVID-19 pandemic. It showcases how the increasing demand for advanced models using enormous amounts of data is met through hardware and software optimization. The current and future CPU and GPU contexts, programming languages in HPC, parallel programming models, and workload management are also discussed. Last, the use of AI in scientific research and emerging technologies for improved AI delivery in HPC applications is extensively discussed with real life examples.
Course Objectives
- Understand how supercomputer architectures from the 60s, 70s, & 80s, on-processor parallelism, the decreasing clock cycle in the late 90s, and the introduction of GPUs and multi-core nodes affect high performance computing today
- Describe high performance computing evolution and what is the exascale era of computing. How exascale enables the discovery of actionable insights based on real-life examples or “grand challenge” problems as happened with the COVID-19 drug/vaccine research
- Understand how it is possible to accelerate application performance via choice of processor, the memory hierarchy, the interconnect, the architecture, and the choice of storage hardware
- Describe the expected hardware components and systems that will be prevalent in the near future in HPC systems. Additionally, the software used to program and run applications in modern systems will be discussed
- To learn about the leading edge of HPC research that involves understanding how AI can be used in science in addition to the latest developments in heterogeneity. To see examples of serverless computing that portray the delivery of HPC as a service. To describe those technologies that can be used to better deliver AI for science and HPC
Authors and Instructors