High Performance Computing Case Studies in the Scope of EuroCC Coordinated by TUBITAK ULAKBIM Turkey Project Turns into Success Stories

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The EuroCC Turkey project coordinated by TUBITAK ULAKBIM with the support of Middle East Technical University and Sabancı University has been performing successful works. In the scope of this project, events, workshops, seminars, webinars, and info days are organized in order to increase awareness in the fields of High-Performance Computing (HPC), Big Data, and Artificial Intelligence, to share the experiences and advantages of using HPC at the national level.

Established with the EuroCC Project, National Competence Center (NCC) Turkey has carried out case studies with Small and Medium sized Enterprises (SMEs) and industry in order to increase their competences in the field of HPC, HPDA, and AI, which leads to support industry-academy collaboration, as well. During the case studies, NCC experts meet the needs of SMEs in both the infrastructure and academic levels, which enables the case studies to turn into success stories. NCC experts also encourage the SMEs and industry representatives to write projects for HPC calls to be opened in Europe. All these efforts accelerate more SMEs to use HPC resources and making them easy to integrate with the European HPC opportunities.

Please click here to gain detailed information regarding the case studies carried out with SMEs.

If you would like to initialize a case study, you can fill out “the case study application form”.


The case study, titled “Improving the Efficiency of the Graphene-Enhanced Polymer Composite Production via Classical Molecular Dynamics”, was conducted with Nanografi. With this case study, the company was introduced to computational materials science and HPC services for the first time and was able to tap into computational work as an alternative or support mechanism to the traditional and rather time-consuming experimental methods. With the support of NCC Turkey, Nanografi has applied for FF4EuroHPC Second call and the company's application has been accepted.


This case study, which was conducted with Machinetutors, addresses the problem of large-scale real-time image-based content moderation. The system is deployed to a production environment where tens of thousands of users browse the internet daily. The system must be both accurate and run in real-time to meet the business requirements. HPC’s speed and cost benefits enabled the project to be successfully delivered on time. With this collaboration, the company was able to run many experiments in parallel and quickly see the effects of the model updates. With the ability to run large batch size trainings on newer GPUs, the company’s experiments completed much faster. Being able to access many GPUs at the same time enabled them to tune the hyper-parameters of each model to improve the results. Besides the speed and cost-efficiency provided by this support have helped the company gain a considerable competitive advantage in the global AI ecosystem.


The case study, titled “Simulation-Optimisation of a Patented Design with Parallel Computing on TRUBA cluster – Design-Optimisation of a Disinfection System” was conducted with DSTECH. DSTECH has developed an open-source simulation and optimisation framework augmented with OpenFoam, Dakota, and Python, which can be freely used on HPC clusters without any restrictions such as license, commercialization, and parallelization. The present simulation and optimisation framework was employed to optimise the slot-baffle design in three stages without any convergence issues. Numerical simulations were performed with parallel computing strategies using an intense computational resource allocated on the TRUBA.  The simulation results in the present study revealed that the efficiency of the conventional design can be improved by 12.47% when the optimised design is implemented to the present tank.


The case study, titled “The multiphysics experiments of the Weather Research and Forecasting Model (WRF) on precipitation patterns of Turkey” was conducted with ErikTronik. An operational forecast of hydrometeorological variables are aimed to be acquired at high accuracy. This case study was performed with utilizing TÜBİTAK-TRUBA HPC infrastructure. The company has the following benefits owing to this case study:

  • The team has gained experience for the first time in the HPC domain.
  • The team has been encouraged to apply to the EuroHPC projects in the seasonal forecast and climate prediction areas through gained experience with this project.
  • The team improved their insight into driving mechanisms of precipitation over Turkey.