Speaker
Description
High Performance Computing (HPC) is a crucial field that leverages advanced computing power to solve complex problems in science, engineering, and business. This 30-minute talk will cover fundamental concepts, the significance of HPC, its evolution, and the core technologies involved. The presentation showcases HPC as a transformative force, highlighting its foundational principles, historical evolution, and technological innovations that drive modern scientific and engineering breakthroughs.
● Definition and Importance of HPC. HPC aggregates massive computing power to deliver greater performance than standard computers, enabling breakthroughs in fields like climate research and molecular modeling.
● Components of an HPC System. Key components include compute nodes, high-speed networking, vast storage systems, and specialized software for HPC tasks.
● Parallel Computing. HPC relies on parallel computing, which involves multiple computations simultaneously to solve complex tasks faster using models like bit-level, instruction-level, data parallelism, and task parallelism.
● Scalability and Speedup. Scalability indicates a system’s ability to handle an increasing load, while speedup measures performance gains in parallel versus serial execution.
● Amdahl's and Gustafson's Laws. Amdahl's Law provides a theoretical speedup limit due to serial task portions, while Gustafson's Law suggests problem size can scale with the number of processors.
● HPC Programming Models. Models like OpenMP (shared-memory), MPI (message passing), and GPU programming, enable optimizing parallel processing and leveraging specific hardware capabilities.
● Evolution of HPC. From the first supercomputers like CDC 6600 and Cray-1, through the advent of parallel processing and clusters, to the future of exascale computing and AI.
● Moore's Law. Describes the doubling of transistors in an integrated circuit every two years, indirectly predicting computational power growth impacting HPC advancements.
● HPC Performance Metrics. Key metrics include FLOPS for computational capacity, latency, and bandwidth for data transfer, all essential for evaluating HPC efficiency.
● HPC in AI and Future Applications. Rapid advancements in computing power underline the role of HPC in AI developments, with the potential for revolutionary changes in multiple disciplines.
