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Layton has been in the HPC business for almost 25 years (starting when he was four years old). He can be found lounging around at a nearby Frys enjoying the coffee and waiting for sales.

by parallelizing your code? Depending on your code and your skills, you have a number of paths to parallelization, but after some hard work profiling and lots of testing, your application is successfully

, is very high because of the nature of randomized read I/O profiles and operations. The amount of memory the ARC can use on your local system can be managed in multiple ways. For instance, if you want

to be on the system. If you want to build or run containers, you need to be part of that group. Adding someone to an existing group is not difficult: $ sudo usermod -a -G docker layton Chris Hoffman wrote an article

To improve the performance of your applications, you need to conduct some kind of dynamic (program, software, code) analysis, also called profiling, to measure metrics of interest. One key metric ... Profiling Python code – as a whole or by function – shows where you should spend time speeding up your programs. ... Profiling Python Code ... Profiling Python Code

. It all boils down to the I/O profile of the ecosystem or server on which it is being implemented. Before I dive right in, I want to take a step back, so you understand what I/O caching is and what

functions. The general categories of these functions are: device and memory management memory hooks streams and events profilers These functions are extremely useful for writing custom

the performance and scalability of your code, particularly serial code. Now, you should be able to pull everything together, from profiling your application to determine which code to parallelize, to using

timers around those parts. Do as much as you want, but don’t go too crazy. Third, optionally use a profiler that can tell you how much total time is used in each routine of the code. Several profilers

that you understand what you are computing and what the output means. Profiling As you port your application to use OpenACC, understanding the effect of directives on performance is key. The first