Research and Innovation
Appentra and Parallelware come from research carried out by our Co-Founder and CEO Manuel Arenaz while a Professor at the University of Coruña, and research is still at the core of what we do!
The Appentra Team is partner of H2020 projects and works with research groups worldwide on computational science and engineering (CSE) projects and high performance computing (HPC) tools to achieve the goals of their R&D projects.
Current projects
Maestro
Middleware for memory and data awareness in workflows.
https://www.maestro-data.eu/
Duration: from 2018 Sep to 2021 Sep
Financed by: Horizon 2020
Maestro will build a data and memory-aware middleware framework that addresses the ubiquitous problems of data movement in complex memory hierarchies that exist at multiple levels of the HPC software stack.
Though High Performance Computing (HPC) and High Performance Data Analytics (HPDA) applications pose a broad variety of efficiency challenges, the performance of both has become dominated by data movement through the memory and storage systems, rather than the floating point computational capability. Despite this shift, current software technologies remain severely limited in their ability to optimise data movement. MAESTRO, the ‘Middleware for memory and data-awareness in workflows’ project, will address the two following major impediments of the modern HPC software: (1) data awareness and (2) memory awareness.
Partnerships
- Jülich Supercomputing Centre (JSC) – Germany
- CEA – France
- Appentra – Spain
- ETH Zurich (CSCS) – Switzerland
- ECMWF – United Kingdom
- Seagate
- Cray
EPEEC
European joint Effort toward a Highly Productive Programming Environment for Heterogeneous Exascale Computing (EPEEC)
https://epeec-project.eu/
Duration: from 2018 Oct to 2021 Sep
Financed by: Horizon 2020
The main general objective of EPEEC is to develop and deploy a well-integrated comprehensive parallel programming environment that turns next-generation exascale supercomputers into manageable platforms for domain application developers. This will be accomplished by providing an exascale programming environment featuring three overarching features: (1) high coding productivity, (2) high performance, and (3) energy awareness. The consortium will significantly advance and integrate existing state-of-the-art components based on European technology (programming models, runtime systems, and tools) with key features enabling a highly-productive coding experience focused on the foreseen highly-heterogeneous exascale hardware, yielding energy-aware high-performance executions.
Partnerships
- APPENTRA SOLUTIONS S.L. -Spain
- Barcelona Supercomputing Center – Spain
- C.E.R.F.A.C.S -France
- CINECA Consorzio Interuniversitario -Italy
- ETA SCALE AB (Company) -Sweden
- Fraunhofer Institute – Erlangen, Germany
- IMEC – Belgium
- INESC-ID
- INRIA
- Uppsala University – Uppsala, Sweden
OPTIMA
Optimizing Industrial Applications for Heterogeneous HPC Systems (OPTIMA)
Duration: from 2021 March to 2024 March
Financed by: Horizon 2020 and EuroHPC Joint Undertaking
OPTIMA’s main goal is to prove that there are several HPC applications that can take advantage of the future highly heterogeneous FPGA-populated HPC systems while, by using the newly introduced tools and runtimes, the application porting/development can be almost as simple as developing software for conventional HPC systems incorporating GPUs. Special emphasis will be given to the efficient processing of both conventional HPC applications (e.g. Fluid Dynamics, Underground Simulations, etc.) as well as the more recently introduced machine/deep learning ones.
Partnerships
- Telecommunication Systems Institute (TSI)
- Cyberbotics Sàrl
- Fraunhofer
- EXAPSYS
- Institute of Communication and Computer Systems (ICCS)
- M3E
- Maxeler IoT
- Forschungszentrum Jülich
- EnginSoft
- Appentra Solutions
Past projects
Project with Oak Ridge Leadership Computing Facility (OLCF): “Porting Parallware Tool to Large HPC Installations Including Titan.”
Publications
EduHPC 2017
SC17
"Parallelware Trainer: Interactive Tool for Experiential Learning of Parallel Programming Using OpenMP and OpenACC."
IWOPH 17
ISC 17
"The Technological Roadmap of Parallelware and its Alignment with the OpenPOWER Ecosystem."
2015 Oil&Gas HPC Workshop
RICE
"Democratization of HPC in the Oil & Gas Industy through Automatic Parallelization with Parallelware."
EuCap 2015
"Novel Source-to-Source Compiler Approach for the Automatic Parallelization of Codes based on the Method of Moments."
APSRUSI 2014
Comparaison of Iteractive Solver Performance on Multiple Surface Integral Equation Formulations for Plasmonic Scatterers
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