Introduction to High-Performance Computing
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High-performance computing (HPC) involves solving complex problems using computer modeling, simulation, and analysis that require huge computational resources beyond what a typical personal computer can handle. HPC is used across many fields including engineering, science, weather prediction, and more. While proprietary supercomputers were once common, HPC has increasingly moved to using commodity computer clusters connected by fast networks due to their affordability, efficiency, and scalability. Clusters now represent over 80% of the world's most powerful supercomputers. HPC simulations can significantly reduce product development timelines and costs across many industries.
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Live Demo
Watch Shrey and Vishwajeet build an Agentforce bot that handles low‑stock alerts: it monitors inventory, creates purchase orders, and notifies procurement—all inside Salesforce.
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Com fer un pla de gestió de dades amb l'eiNa DMP (en anglès)
Com fer un pla de gestió de dades amb l'eiNa DMP (en anglès)CSUC - Consorci de Serveis Universitaris de Catalunya
Introduction to High-Performance Computing
- 2. 2 What is High Performance Computing? • There is no clear definition – Computing on high performance computers – Solving problems / doing research using computer modeling, simulation and analysis – Engineering design using computer modeling, simulation and analysis • My understanding – A huge number of computational and memory requirements – Cannot be afforded by a PC efficiently – Speeds and feeds are the keywords • Who uses High-Performance Computing – Research institutes, universities and government labs • Weather and climate research, bioscience, energy, military etc. – Engineering design: more or less every product we use • Automotive, aerospace, oil and gas explorations, digital media, financial simulation • Mechanical simulation, package designs, silicon manufacturing etc. • Similar concepts – Parallel computing: computing on parallel computers – Super computing: computing on world 500 fastest supercomputers
- 3. 3 When Do We Need High Performance Computing? • Case1: Complete a time-consuming operation in less time – I am an automotive engineer – I need to design a new car that consumes less gasoline – I’d rather have the design completed in 6 months than in 2 years – I want to test my design using computer simulations rather than building very expensive prototypes and crashing them • Case 2: Complete an operation under a tight deadline – I work for a weather prediction agency – I am getting input from weather stations/sensors – I’d like to predict tomorrow’s forecast today • Case 3: Perform a high number of operations per seconds – I am an engineer at Amazon.com – My Web server gets 1,000 hits per seconds – I’d like my web server and databases to handle 1,000 transactions per seconds so that customers do not experience bad delays
- 4. 4 What Does High Performance Computing Include? • High-performance computing is fast computing – Computations in parallel over lots of compute elements (CPU, GPU) – Very fast network to connect between the compute elements • Hardware – Computer Architecture • Vector Computers, MPP, SMP, Distributed Systems, Clusters – Network Connections • InfiniBand, Ethernet, Proprietary (Myrinet, Quadrics, Cray-SeaStar etc.) • Software – Programming models • MPI (Message Passing Interface), SHMEM (Shared Memory), PGAS, etc. – Applications • Open source, commercial
- 5. 5 Rise and Fall of HPC Computer Architectures • Vector Computers (VC) - proprietary system – Provided the breakthrough needed for the emergence of computational science, but they were only a partial answer • Massively Parallel Processors (MPP) - proprietary systems – High cost and a low performance/price ratio. • Symmetric Multiprocessors (SMP) – Suffers from scalability • Distributed Systems – Difficult to use and hard to extract parallel performance • Clusters – commodity and highly popular – High Performance Computing - Commodity Supercomputing – High Availability Computing - Mission Critical Applications
- 6. 6 Top500 Supercomputers List – System Architecture Clusters have become the most used HPC system architecture More than 80% of Top500 systems are clusters
- 7. 7 Computer Food Chain: Causing the Demise of Specialized Systems Parallel Computing on a Large Number of Servers is More Efficient than using Specialized Systems
- 8. 8 HPC Clusters – Affordable, Efficient and Scalable HPC Solution • Since the 1990s, there has been an increasing trend to move away from expensive /specialized proprietary parallel supercomputers to clusters of computers – From specialized supercomputers to cost effective, general purpose systems • So What’s So Different about Clusters? – Commodity, standard, affordable, cost effective, scalable and reliable architecture Server Communications Software Network Interface Hardware Server Communications Software Network Interface Hardware Server Communications Software Network Interface Hardware Server Communications Software Network Interface Hardware Cluster Interconnect Network Cluster Architecture
- 9. 9 • Commoditization/standardization are the clustering and interconnect driving forces • InfiniBand and Ethernet are the most used interconnect solutions for HPC systems Cluster Interconnect
- 10. 10 Interconnect Trends – Top100 Status (Nov 2010)
- 11. 11 Product Development Process Preparation/Delivery Without Concept Development Prototype/ Physical Testing Manufacturing Design Final HPC Time to Market With HPC HPC-Supported Simulation Time Savings The HPC Advantage: Reduction in Time to Market Source: IDC
- 12. 12 • From concept to engineering, from design to test and manufacturing, from weather prediction to medical discoveries, our day to day life depends more and more on HPC simulations – Safer products, accurate predictions, research, etc. • High-performance compute clusters provide the most efficient, flexible, cost effective HPC environment for any HPC simulation Summary