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A master's on making scientific and data-intensive software run fast and at scale.
A master's on making scientific and data-intensive software run fast and at scale. Students learn parallel computer architecture, distributed- and shared-memory programming, GPU computing, performance modelling and parallel numerical algorithms, and run their codes on clusters. Every module includes measured experiments: scaling studies, roofline analysis and profiling reports. It suits graduates in computer science, engineering, physics or mathematics who want to develop and optimise parallel simulation and analysis software, and it ends with a research thesis.
Complete the online form, which saves from the first step, pay the $30 application fee, and upload your documents. Admissions emails you the decision.
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