Julia and Chapel are both newish languages aimed at productitive scientific computing, with parallel computing capabilities baked in from the start. There’s lots of information about both online, but not much comparing the two. If you are starting a new scientific computing project and are willing to try something new, which should you choose? What are their strengths and weaknesses, and how do they compare? Here we walk through a comparison, focusing on distributed-memory parallelism of the sort one would want for HPC-style simulation. Both...

Continue...I was asked recently to do short presentation for the Greater Toronto R Users Group on parallel computing in R; My slides can be seen below or on github, where the complete materials can be found. I covered some similar things I had covered in a half-day workshop a couple of years earlier (though, obviously, without the hands-on component): How to think about parallelism and scalability in data analysis The standard parallel package, including what was the snow and multicore facilities, using airline data as...

Continue...The organizers of EuroMPI 2016 were kind enough to invite me to give a keynote and participate in a panel at their meeting, which was held at the end of September in beautiful Edinburgh. The event was terrific, with lots of very interesting work going on in MPI implementations and with MPI. The topic of my talk was “MPI’s Place in Big Computing”; the materials from the talk can be found on github. The talk, as you might expect, included discussion of high-productivity big data...

Continue...I was asked to do a half-day tutorial at the Great Lakes Bioinformatics conference Workshop session. The focus was mainly on R, with some python as well. We covered: The basics of Jupyter notebooks - what they are and how they work How to install and run Jupyter notebooks on their laptop, in R and Python How to perform interactive analyses in a web browser using Jupyter Using markdown and latex to How to “Port” an R bioinformatics workflow from some scripts into a Jupyter...

Continue...The kind folks at the University of Michigan’s Center for Computational Discovery and Engineering (MICDE), which is just part of the very impressive Advanced Research Computing division, invited me to give a workshop there a couple of months ago about the rapidly-evolving large-scale numerical computing ecosystem. There’s lots that I want to do to extend this to a half-day length, but the workshop materials — including a VM that can be used to play with Spark, Chapel and TensorFlow, along with Jupyter notebooks for each...

Continue...Over at the Simpson Lab blog, I have an post describing a novel method for Directly Mapping Squiggle Data, using k-d trees to map segmented kmers; a simple proof of concept is available on github.

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