OpenCL is a well-established and widely-supported standard for executing parallel workloads
on accelerator devices such as conventional multicore CPUs as well as GPUs and FPGAs.
In this presentation, detail is given on a modern Fortran library which wraps calls to the OpenCL API with a higher abstraction level aimed at scientists and engineers looking to execute highly-parallel OpenCL...
In the community of environmental modelling, the advent of hyper-resolution Earth observations and datasets in conjuncture with growing computational resources lead to an increase in model resolution.
The mathematical representations of biogeophysical processes need to be solved for billions of grid cells and thousands of time points.
Each process requires parameters that cannot be easily...
Implementing artificial neural networks is commonly achieved via high-level programming languages like Python, and easy-to-use deep learning libraries like Keras. These software libraries come pre-loaded with a variety of network architectures, provide autodifferentiation, and support GPUs for fast and efficient computation. As a result, a deep learning practitioner will favor training a...
While it is possible to write Fortran code with a simple text editor, many programmers prefer to use an IDE (Integrated Development Environment) for their work. In addition to simply highlighting text in many editors, Code::Blocks offers Fortran users a grouping of their code files into projects, compiling code with the selected compiler directly from the IDE, code navigation, code completion...
