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Last Updated: October 20, 2026
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In Fall 2020 and Spring 2021, this was MIT's 18.337J/6.338J: Parallel Computing and Scientific Machine Learning course. This video demonstrates interactive tools for exploring code and diagnosing why some code runs slowly due to "type instability." Understanding the performance of parallel code is tricky, however Other SFU Research Computing training events: training.westdri.ca/blog Training Inquiries: training Machine learning. Data science. Using VS Code's profiling tool to optimize the execution time of a Julia program. It allows ... During this workshop I will explain the design of indexing of the DataFrame type provided by the DataFrames.jl package. Next a ... Compare versions. Understand performance. Discover PerfChecker.jl: a toolkit for measuring, comparing and investigating There are lots of programming languages, what's different about
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