Explora Phase II Beta Release is now live - Training materials discovery is now available.

Note: all times are shown in the timezone in which each event occurs.

Date: 3 June 2026 @ 13:30 - 16:30

Timezone: Pacific Daylight Time

Language of instruction: English

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Abstract: R is not a fast language. Poorly written R is really slow! Faced with slow code, people tend to think “parallel” or “GPU” (which is an adjacent topic since GPUs allow to run many simple calculations in parallel). Parallel programming can indeed greatly help speed up some types of code. A lot of hardware however is not the answer to poorly written code. Before considering parallelization, you should think of ways to optimize your code sequentially because not all programs can be parallelized, parallel programming has costs and overheads, and an optimized serial code will also benefit your parallel code. In many cases, writing better code will save you more computing time than parallelization. This course will cover just that: how to benchmark code, how to identify bottlenecks, and how to greatly improve code performance without using additional hardware.

Keywords: GPU, HPC

Venue: onsite


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