Core Labs Training_Catalogue-v2 (edit 2)-web

Data Science on HPC at KSL HIGH-PERFORMANCE COMPUTING SERVICES

HIGH-PERFORMANCE COMPUTING SERVICES

Deep Learning at Scale on KSL Platforms

In this course, we will catalogue tools to accelerate popular Data Science work- loads on KSL supercomputers. We will survey the applications and packages utilizing HPC platforms e.g. to speed up data wrangling, processing and analyz- ing Big Data, Machine Learning/Deep Learning at scale. We will discuss best practices on KSL platforms, addressing: • Methods of execution • Data management conducive to achieving high performance • Aspects of prototyping to production ready Data Science workflows PARTICIPANT PROFILE This course is intended for research professionals from KAUST who are either: • Dealing with Big Data from various science domains. This data may either have results from simulations on KSL supercomputers or is from external scientific data sources. • Exploring to accelerate their Data Science workflows to deal with Big Data. Familiarity with using at least Python or R is required. PREREQUISITES • Either: HPC 101, Getting Started on Ibex Cluster, or basic knowledge of Linux command line and job scheduling MAXIMUM PARTICIPANTS 40 DURATION 1 day FREQUENCY Yearly

In this course, we will catalogue examples of how to scale out Deep Learning workloads on KSL supercomputers. We will discuss and demonstrate best prac- tices when using KSL platforms addressing for Deep Learning frameworks, e.g. ways to execute, data management best practices, and opportunities of profiling of the model training in Deep Learning frameworks. PARTICIPANT PROFILE This course is intended for research professionals from KAUST aiming to accelerate training of models using common Deep Learning frameworks. Basic knowledge of one or more common Deep Learning frameworks, familiarity with Python, and basic knowledge of Linux command line usage are required. PREREQUISITES MAXIMUM PARTICIPANTS 40 DURATION 2 hours FREQUENCY Yearly

Learn Develop Excel

Specialized Instrument & Method Training Catalog

Edition 1, September 2020

289

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