This is a new lesson built with The Carpentries Workbench.
The HPC-user Software Carpentry module is aimed at researchers with some background in using scientific computing. This lesson will teach scientists to understand and deal with performance issues that arise when moving from a personal computer to a High-Performance Computing (HPC) environment (a SuperComputer). The basic concepts that affect performance are covered in a general manner, then a survey of the capabilities and performance of many languages commonly used in scientific computations are discussed along with example codes illustrating the performance concerns of each language. Each person who completes this module should have a good general overview of what each computer language can do and what performance bottlenecks to avoid.
Each user must begin with some knowledge of Linux and at least one of the languages that this module covers (Python, R, C/C++, Fortran, Matlab). The examples in the first part of this module are currently only in Python but will eventually be adjustable to display in any of these languages. Each user may also need to know how to run jobs in an HPC environment. These prerequisites may all be covered by having an HPC Unix Shell carpentry module taught right before this one.
This Carpentries lesson was created by Dr Dave Turner ([email protected]) at Kansas State University 2022-2024+.