Thursday, January 4, 2024
11:00 AM - 12:30 PM PST
This event will be held remotely.
All users of advanced cyberinfrastructure, whether they develop their own software or use 3rd party applications, should understand fundamental parallel computing concepts. In this webinar we cover supercomputer architectures, the differences between threads and processes, implementations of parallelism (e.g., OpenMP and MPI), strong and weak scaling, limitations on scalability (Amdahl’s and Gustafson’s Laws) and benchmarking. We also discuss how to choose the appropriate number of compute cores or nodes when running your applications and, when appropriate, the best balance between threads and processes. This webinar does not assume any programming experience and is suited for a wide audience, including current and prospective users of parallel computers, anyone who expects to write a proposal for computer time or those who are simply curious about parallel computing.
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COMPLECS (COMPrehensive Learning for end-users to Effectively utilize CyberinfraStructure) is a new SDSC program where training will cover non-programming skills needed to effectively use supercomputers. Topics include parallel computing concepts, Linux tools and bash scripting, security, batch computing, how to get help, data management and interactive computing. Each session offers 1 hour of instruction followed by a 30-minute Q&A. COMPLECS is supported by NSF award 2320934.
Director of Education and Training, SDSC
Dr. Sinkovits leads the education and training efforts at the San Diego Supercomputer Center, where he has been a computational scientist for more than 25 years. He has collaborated with researchers spanning many fields including physics, chemistry, astronomy, structural biology, finance, ecology, climate, immunology, and the social sciences, always with an emphasis on making the most effective use of high-performance computing resources. Dr. Sinkovits is the PI for the COMPLECS CyberTraining project and co-PI for the Voyager and Expanse supercomputer awards.