High-Performance Computing (HPC) is a major enabler of progress in many domains of science, including UN Sustainable Development goals towards improving population health and climate action. HPC is driving breakthroughs in genomics, drug discovery, and personalized medicine, as well as geophysical hazard simulations, improving preparedness for disasters like earthquakes and tsunamis, and supports weather and climate predictions. Europe is among the world leaders in HPC and with initiatives such as EuroHPC JU is advancing the usage of exascale computer systems for research. India is expanding its HPC capabilities through the National Supercomputing Mission, focusing on indigenous technology and fostering academic, industrial, and governmental collaborations. Combining Europe’s advanced infrastructure with India’s growing expertise offers opportunities for innovation in those strategic areas of climate modeling, disaster management, and healthcare. Shared resources and expertise can enhance predictive models, accelerate responses to pandemics, and foster technological and economic growth. The GANANA project is establishing a long-term partnership collaboration by uniting European HPC centers of excellence (BioExcel, ChEESE, ESiWACE3) and Indian institutions (C-DAC, IMD, ISR, NII, AIRAWAT) with the objectives to: • Strengthen the links between research communities in the priority domains by supporting existing and establishing new collaborative activities. • Setup and operate a range of activities in support of expertise exchange, capacity building and sharing of computing resources. • Develop selected leading software packages by extending their functionality, optimise HPC performance and scalability, deploy on target architectures, improve usability and data integration. • Expand the outreach, broaden the participation of external collaborators and develop a framework for wider community engagement and cooperation. • Investigate options for governance and funding models, engage in a policy dialogue with key stakeholders and develop a framework for long-term partnership.
General aims
Objective 1: Scientific collaborations in priority domains, Specific objective: Strengthen the links between research communities in the priority domains by supporting existing and establishing new collaborative activities.
Objective 2: Expertise exchange and resource sharing, Specific objective: Setup and operate a range of activities in support of expertise exchange, capacity building and sharing of computing resources.
Objective 3: Leading software for scientific computing, Specific objective: Develop selected leading software packages by extending their functionality, optimise HPC performance and scalability, deploy on target architectures, improve usability and data integration.
Objective 4: Framework for broader community engagement, Specific objective: Expand the outreach, broaden the participation of external collaborators and develop a framework for wider community engagement and cooperation.
Objective 5: Roadmap for a long-term partnership, Specific objective: Investigate options for governance and funding models, engage in a policy dialogue with key stakeholders and develop a framework for long-term partnership.
CMCC role
Task 1.3 – Communication and Dissemination (leader)
Work package WP5 – Weather & Climate Prediction (involved) while leading the following sub projects:
Project 3: Urban climate studies
The project aims to strengthen collaboration with the Indian climate research community by simulating climate change over one of India’s most significant urban regions, using a CMIP scenario at approximately 2 km resolution. To achieve this, the ICON-CLM model will be deployed on C-DAC high-performance computing infrastructure.
Task 5.8 – ICON-CLM deployment (leader)
This activity focuses on porting the CMCC configuration of the ICON-CLM model—developed through collaboration with the CLM Community and COSMO consortium—to the C-DAC computing infrastructure. The configuration will include urban parameterization to better represent city-scale processes.
Task 5.9 – Urban model tuning (leader)
This task includes tuning the regional climate model for the Pune area at a spatial resolution of approximately 2 km and a temporal resolution of 1 hour. Additionally, the model’s computational performance will be evaluated to better define the simulation experiment planned in Task 5.10.
Task 5.10 – Urban model simulations over Pune (leader)
The activity plans to carry out urban climate simulations over the Pune region, covering a period of approximately 61 years. This includes a historical baseline, one future scenario, and one year for model spin-up. The exact number of simulated years may be adjusted based on C-DAC resource availability and the model performance evaluated in Task 5.9. Simulations will be based on either a CMIP5 or CMIP6 scenario, depending on the availability of lower-resolution data for the Pune area. Post-processing and analysis of the simulation outputs will also be performed
Expected results
1. Optimised, performant and scalable HPC applications for biomolecular, geophysical hazards and weather/climate research
2. Novel algorithms and methods for modelling and simulations
3. High-precision HPC-enabled models for simulating and predicting a range of natural hazards
4. Likely frequency and severity of heat waves, heat stress, droughts etc. and their effect on human health
5. Demonstration workflows addressing concrete needs for industry in particular pharma
6. Joint projects and activities between groups in both regions
7. Resource sharing policy and procedures for access to HPC infrastructure
8. Strengthening of links and collaborative activities between the regions
Partners
1. UNIVERSITEIT UTRECHT
2. JOHANN WOLFGANG GOETHE-UNIVERSITAET FRANKFURT AM MAIN
3. BARCELONA SUPERCOMPUTING CENTER CENTRO NACIONAL DE SUPERCOMPUTACION
4. AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
5. UNIVERSIDAD DE MALAGA
6. CINECA CONSORZIO INTERUNIVERSITARIO
7. BULL SAS
8. CSC-TIETEEN TIETOTEKNIIKAN KESKUS OY
8.1 JYVASKYLAN YLIOPISTO