Releasing the potential of your software
We are a software company with one aim: to make parallel programming easier, enabling everyone to make the best use of parallel computing hardware from the multi-cores in a laptop to the fastest supercomputers.
At Appentra, we recognise that one of the greatest challenges for making use of parallel computing is introducing parallelism into software. For many of our clients, writing software is a solution to a problem. What they are passionate about is not the parallelization itself but what the parallelization will enable them do! We want our clients, present and future to focus on the questions they want to answer, while we focus on helping them get to the solution as quickly as possible.
At Appentra our passion is making your parallelization problem simpler so you can focus on the problems you care about. We aim to minimise and eventually remove the parallel software development barrier, democratizing access to HPC and making the parallel computing easier for everyone.
Appentra was founded in 2012 as a spin-off at the University of A Coruña building on the work of CEO and Co-Founder Manuel Arenaz. Appentra’s products are based on over 10 years of research and development in improving the parallelization of code and parallel programming environment.
Parallelware was born in 2013 and has grown into a Tools Suite that aims to support programmers in parallelising software.
Find out more about Parallelware.
THE APPENTRA TEAM
The Appentra Team has a unique set of skills, combining experts in parallel programming, parallel simulations, HPC consultancy for scientific applications, HPC training and education, as well as best practices in software engineering. Based on research in developing advanced compiler techniques for automatic parallelization of simulation programs we provide a unique approach to solving the parallelization challenge.
The team has experience in the parallelization of the main numerical methods and techniques (finite elements, finite differences, finite volumes, SPH, N-body methods, computational fluid dynamics and much more) as well as in many of the parallel programming standards used in HPC industry and academia (OpenMP, OpenACC, MPI).
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