The Computation-based Science and Technology Research Center (CaSToRC) of The Cyprus Institute acts as the National HPC Competence Center for Cyprus. CaSToRC’s research team comprises of more than 30 researchers and since its creation has secured more than €16 million in external funding,.

The primary goals of CaSToRC are:
-To create a research and educational program of international calibre in computational and data science, engineering and underlying areas of scientific computing.
-To build and provide supercomputing capability in Cyprus enabling the understanding via simulation of a broad range of complex processes.
-To emerge as a regional hub for computational science and scientific computing.

It pioneers in the introduction, development and employment of intense computational methods and data to advance scientific and technological disciplines. In addition to offering computational resources, training and user support, it pursues its own research areas.

Hackathon Presentation - EuroCC collaborates with Anticancer Society Cyprus
58:51
Hackathon Presentation - EuroCC collaborates with Anticancer Society Cyprus
Introduction to Physics Informed Machine Learning
1:55:33
Introduction to Physics Informed Machine Learning
Aurora: A Foundation Model of the Atmosphere
1:06:11
Aurora: A Foundation Model of the Atmosphere
Intermediate-level Programming for HPC Using Python - Training event from NCC Cyprus & NCC Greece
3:55:14
Intermediate-level Programming for HPC Using Python - Training event from NCC Cyprus & NCC Greece
Network Geometry
1:00:13
Network Geometry
Introduction to Parallel Computing for Beginners – Training Event (2024)
3:12:34
Introduction to Parallel Computing for Beginners – Training Event (2024)
Towards Engineering Trustworthy Learning-Enabled Systems
1:22:39
Towards Engineering Trustworthy Learning-Enabled Systems
Machine Learning for Agents and Multi-Agent Systems
1:04:28
Machine Learning for Agents and Multi-Agent Systems
Addressing the Problem of Data Sparsity with Generative Modelling
29:43
Addressing the Problem of Data Sparsity with Generative Modelling
Introduction to GPU Programming
1:35:57
Introduction to GPU Programming
Use cases of machine learning
19:07
Use cases of machine learning
Introduction to HPC and Cyclone
55:55
Introduction to HPC and Cyclone
Data Cleaning and Preprocessing for Scientific Computing
51:22
Data Cleaning and Preprocessing for Scientific Computing
From Large Graphs to Large Neural Networks
1:12:13
From Large Graphs to Large Neural Networks
Introduction to Deep Learning for Computer Vision
52:20
Introduction to Deep Learning for Computer Vision
Computational Investigation of Underlying Disease Mechanisms and in Silico Drug Repurposing
53:08
Computational Investigation of Underlying Disease Mechanisms and in Silico Drug Repurposing
Personalized In Silico Modelling of Disease Progression and Treatment Outcome Prediction
54:50
Personalized In Silico Modelling of Disease Progression and Treatment Outcome Prediction
A Data Science Pipeline for Big Linked Geospatial and Earth Observation Data
1:13:27
A Data Science Pipeline for Big Linked Geospatial and Earth Observation Data
Skyrmion Dynamics Within a Sigma-model for Chiral Antiferromagnets
1:01:34
Skyrmion Dynamics Within a Sigma-model for Chiral Antiferromagnets
Evolution PDEs Arising in Multifluid-multiscale Flows
1:05:17
Evolution PDEs Arising in Multifluid-multiscale Flows
Learning by Monitoring: Twinning and Model Discovery for Engineered Systems
1:08:08
Learning by Monitoring: Twinning and Model Discovery for Engineered Systems
Fast Mathematics with Numpy in Python
2:10:11
Fast Mathematics with Numpy in Python
Kokkos Framework
22:47
Kokkos Framework
Building products powered by large language models
36:57
Building products powered by large language models
GPU CUDA Programming - Session 1
1:30:23
GPU CUDA Programming - Session 1
Parallel computing techniques for scaling hyperparameter tuning of Gradient Boosted Trees and DL
1:05:42
Parallel computing techniques for scaling hyperparameter tuning of Gradient Boosted Trees and DL
PyTorch Neural Networks: Running on CPUs and GPUs
1:22:37
PyTorch Neural Networks: Running on CPUs and GPUs
GPU CUDA Programming - Session 2
1:15:54
GPU CUDA Programming - Session 2
Efficient Data Cleaning and Pre-processing Techniques for Robust Machine Learning
1:29:53
Efficient Data Cleaning and Pre-processing Techniques for Robust Machine Learning
Large-scale generative models for language and vision (including LLMs): How they work & future work
41:04
Large-scale generative models for language and vision (including LLMs): How they work & future work