Async and Parallel R: Building the Open Source Tools
Computational Statistics seminar by Charlie Gao, Posit
Hosted by Statistical Society of Australia, Statistical Computing and Visualisation Section
Thursday 18:00–19:00 Sydney (GMT+11)
Starts in 10 days
Abstract
Statistical workloads such as Markov chain Monte Carlo, bootstrapping, cross-validation and simulation can benefit from parallel execution, but practical obstacles include blocked R sessions, duplicated data, worker setup and rewritten code. This seminar introduces open-source tools built on asynchronous input/output and messaging, combining asynchronous parallel execution with shared R objects and zero-copy data access. A practical tour covers mirai for scaling work from laptops to high-performance computing, servers and cloud systems, and mori for shared memory. Applications include responsive Shiny interfaces and event-driven programming. The presentation also discusses migrating existing parallel and future code and the prospects for a zero-copy parallel computing model.
Topics
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