As the demands of computational chemistry, molecular simulations, and scientific computing—particularly atomistic simulations—continue to grow, their environmental impact through increasing energy consumption has become a critical challenge. Historically, computational processing itself was the primary expense, but the focus has shifted in recent years to the rising cost of electricity and its significant contribution to global warming. This shift underscores the urgent need to critically revise modeling and simulation techniques, evaluate the energy efficiency of programming languages, and optimize hardware to minimize energy consumption per calculation point.

Sustainability in scientific computing is not just a general issue—it is a complex, interconnected challenge that affects every stage of the computational workflow. From developing a model, designing an algorithm, and implementing it in a programming language to packaging it into a software tool and running it on processors, every category of computation plays a role. These components do not exist in isolation; rather, they form a continuous flow, where inefficiencies or challenges in one area can cascade to others.

To create meaningful and lasting solutions, it is vital to share the challenges and experiences faced by professionals across these domains. For example:

• Model Development: Exploring how different scientific models are designed for accuracy, scalability, and efficiency.

• Algorithm Design: Understanding the trade-offs and optimizations needed to make algorithms energy-efficient without compromising performance.

• Programming Languages: Evaluating the energy efficiency of languages like Fortran, C++, and Python when used for scientific computing.

• Software Development: Discussing the development of both open-source and commercial tools and their strategies for optimizing memory usage, data movement, and runtime.

• Hardware Optimization: Leveraging advancements in GPUs, CPUs, and HPC infrastructure to improve energy efficiency.

By facilitating discussions across these categories, the workshop will identify shared challenges, best practices, and areas where collaboration can drive innovation. The goal is not only to enhance sustainability within each category but also to ensure that solutions are synergistic and holistic.

This collaborative, multi-perspective approach will enable participants to uncover novel strategies, align innovations across disciplines, and collectively pave the way for a more sustainable future in computational science.

1. Facilitate Cross-Disciplinary Optimization Strategies
   Enable the exchange of optimization techniques between programming language developers (C++, Fortran, Python) and scientific software developers to enhance energy efficiency and computational performance across diverse applications.

2. Integrate Software and Hardware Efficiency
   Explore innovative methods to align software implementations with advanced hardware capabilities (CPU, GPU, HPC). Focus on strategies that maximize energy efficiency while delivering high computational performance.

3. Develop Energy-Efficient Algorithms
   Advance the design and optimization of algorithms for computational chemistry and molecular simulations, prioritizing power efficiency, scalability, and resource-conscious computing.

4. Optimize GPU Utilization
   Discuss practical strategies for leveraging GPU-accelerated hardware, including GPU-resident computations, vector processing, and balancing GPU vs. CPU utilization, to achieve superior energy efficiency in scientific computing.

5. Develop Hybrid and Coarse-Grained Models
   Address the development and application of hybrid models or coarse-grained approaches to enable simulations over longer timescales or larger system sizes. Emphasize the integration of different modeling scales to leverage the advantages of each.

6. Incorporate Machine Learning in Scientific Computing
   Explore how machine learning methods, which rely on large datasets, can enhance simulation accuracy and efficiency. Focus on the challenges of integrating ML models with traditional simulation techniques while optimizing computational resource usage.

7. Establish Best Practices for Sustainable Computing
   Identify and promote actionable best practices, such as minimizing memory access, enhancing data locality, reducing internode messaging, and implementing scalable algorithms with optimized local storage utilization.

8. Advocate for Sustainable HPC Resource Allocation
   Address energy-aware resource allocation policies in HPC systems, including strategies to incentivize sustainable practices and optimize energy-efficient usage of computational resources.

9. Foster Interdisciplinary Collaboration
   Encourage collaboration among programming language developers, algorithm designers, hardware specialists, and both commercial and open-source software developers to tackle sustainability challenges collectively.

10. Support and Mentor Early-Career Researchers
    Provide interactive networking and mentoring opportunities for early-career scientists to connect with established experts, fostering skill development and knowledge exchange in the field of sustainable scientific computing.

Networking Platform for Participants

1. Pre-Workshop Website:

   • A dedicated website will introduce participants to one another before the workshop.

   • This platform will highlight attendee backgrounds, enabling connections in a highly interdisciplinary event.

2. Speaker Introduction:

   • During each presentation, a brief introductory slide will showcase the speaker’s background, expertise, and key affiliations to enhance audience engagement.

Daily Multidisciplinary Agenda

• The program is structured to feature talks from diverse perspectives every day, including:

  • Programming Languages (Green): Developers from C++, Python, Fortran, and other languages.

  • Hardware Experts (Yellow): Insights from Intel, AMD, NVIDIA, and others on energy-efficient hardware.

  • Modeling and Algorithm Development: Presentations from research centers and universities.

  • Commercial Packages (Dark Blue): Speakers representing tools like Material Studio, AiiDA, or Schrödinger.

  • Open-Source Packages (Light Blue): Developers from tools like GROMACS, LAMMPS, or VESTA.

• This structure fosters interdisciplinary communication, ensuring broad representation from academia, industry, and software/hardware development.

LinkedIn Group for Continuous Networking

• A LinkedIn group will be created with a QR code shared with all participants.

• The group will facilitate continuous updates, pre- and post-workshop discussions, and long-term collaboration opportunities.

• This network will serve as a foundation for ongoing communication, enabling researchers to collaborate on sustainability challenges.

Dedicated Course Day

• A one-day training course divided into four focused sessions:

  1. Processor Selection: Guidance on selecting the right processors (CPUs/GPUs) for simulations, tailored to specific computational needs.

  2. Machine Learning Applications: Exploration of machine learning’s impact on energy optimization and its role in scientific computing.

  3. Emission Calculations: Practical training led by an HPC center in the UK on how to measure and reduce emissions from simulations.

  4. Discussion on Small Codes vs. Established Packages:

     • Case Studies: A presentation on the journey from developing a small code to commercialization, including challenges and opportunities.

     • Value of Small Codes: An open discussion about the importance of niche codes, their advantages, and their unique contributions compared to large packages.

Virtual Feedback Boards

• Participants will have access to a virtual board (e.g., Google Drive):

  • Key Features:

    • Note down takeaways, questions, and comments after each session.

    • 5–10 minutes will be allocated after each session for reflections and contributions.

  • Outcome:

    • Boards will be compiled into a workshop document shared with all attendees, serving as a record of brainstorming and insights.

Bazaar for Codes and Collaborations

• A dedicated Bazaar session to showcase:

  • Research tools and small software packages developed by participants.

  • Collaboration proposals presented as posters or short videos.

• Format:

  • Each participant gets 7 minutes to present their tool, focusing on its purpose, unique features, and benefits.

  • GitHub links or other repositories will be shared with attendees for further exploration.

  • Posters will remain displayed throughout the workshop for continued engagement.

Vocabulary Preparation

• To ensure technical clarity, speakers will share key technical terms in advance.

• Terms will be uploaded to a shared drive, allowing participants to familiarize themselves before the workshop.

YouTube Channel for Workshop Talks

• If permissible by CECAM regulations, a YouTube channel will host workshop talks, making them publicly accessible for broader engagement.

Encouraging Informal Networking

• During lunch breaks, experienced researchers will be encouraged to sit with early-career participants.

• This initiative promotes informal mentoring, fostering valuable connections and collaborations.

Workshop Timing and Program

• Tentative Dates: The workshop is scheduled for 5-7 May 2026 (subject to final confirmation).

• Daily Structure:

  • One academic speaker: University and research center representatives (Purple).

  • One commercial package speaker: Industry insights (Dark Blue).

  • One open-source package speaker: Community-driven tools (Light Blue).

  • One hardware expert: Sustainable computing solutions (Yellow).

  • One programming language developer: Exploring energy-efficient coding practices (Green).

• This balanced structure ensures a comprehensive exploration of sustainability in scientific computing.

📅 View the Workshop Calendar Here

After each talk, we will facilitate an open discussion session to encourage knowledge exchange, idea-sharing, and structured brainstorming. To ensure productive discussions, we will integrate an online whiteboard tool such as Miro, Lucidspark, or FigJam for collaborative note-taking and idea organization. This will allow participants to post key takeaways, raise questions, and suggest future directions in a dynamic, interactive format.

As a summary and documentation tool, these structured notes will serve as a valuable resource for all participants. By the end of the workshop, collected insights from discussions and brainstorming sessions will be compiled into a shared document to help retain key findings, support future collaboration, and guide follow-up research initiatives. This will ensure that the knowledge generated during the workshop remains accessible and impactful beyond the event itself.

While brainstorming and open discussion are crucial for fostering creativity and collaboration, maintaining harmony in the workshop structure is equally important. To achieve this balance:

• Guided discussions will follow each talk, with targeted questions to keep discussions focused and productive.

• Online whiteboards will be available for participants to note key insights, challenges, and action points.

• A structured yet flexible approach will ensure that discussions remain engaging, constructive, and aligned with the workshop’s overall objectives.

1. Actionable Strategies for Energy-Efficient Software Design
   Develop practical approaches to reduce energy consumption in scientific software by optimizing algorithms for computational chemistry, molecular simulations, and scalable parallel computing.

2. Comprehensive Guidelines for GPU-Centric Algorithm Development
   Provide clear, implementable recommendations for maximizing GPU capabilities, including GPU-resident computation, efficient vector processing, and balancing GPU and CPU utilization to enhance power efficiency.

3. Best Practices for Sustainable Scientific Computing
   Publish a detailed best practices guide, covering key topics such as algorithmic optimization, hardware utilization, memory access efficiency, and data movement strategies to improve sustainability in computational science.

4. Framework for Assessing Power Efficiency
   Develop a robust and standardized framework to evaluate and compare the energy efficiency of scientific software, enabling developers to identify and implement meaningful energy-saving improvements.

5. Policy Recommendations for Energy-Aware HPC Resource Allocation
   Advocate for HPC centers to adopt sustainable resource allocation policies, including incentives for energy-efficient usage and strategies for optimizing computational resources.

6. Enhanced Industry-Academia Collaborations
   Facilitate stronger partnerships between industry and academia to foster shared innovation and develop cutting-edge solutions for sustainable computing.

7. Career Development Opportunities for Early-Career Researchers
   Offer networking, mentoring, and collaboration opportunities for early-career scientists to enhance their skills, gain exposure to interdisciplinary approaches, and build professional connections in the field.

8. Establishment of Ongoing Interdisciplinary Working Groups
   Create dedicated working groups to continue collaboration, monitor progress, and refine strategies for sustainable computing beyond the workshop.

9. Integration of Hybrid Modeling and Machine Learning Techniques
   Encourage the adoption of hybrid models and coarse-grained approaches for simulations, as well as the use of machine learning to enhance computational efficiency and reduce resource requirements.

1. Computational Chemistry Software Developers
   Developers of widely-used molecular dynamics (MD) engines such as NAMD, LAMMPS, DL_POLY, GROMACS, and GROMOS, focusing on enhancing energy efficiency, scalability, and performance.

2. Quantum Chemistry and DFT Tool Developers
   Developers and contributors to quantum chemistry and density functional theory (DFT) tools, including WIEN2k, ORCA, FHI-AIMS, VEGA ZZ, and SCM (Amsterdam Modeling Suite), with an emphasis on computational efficiency and sustainability.

3. Visualization and Analysis Tool Developers
   Contributors to tools for visualizing and analyzing simulation data, such as VESTA, V_Sim, Avogadro/GaussView, and Chimera, focusing on energy-aware approaches for processing large datasets.

4. Workflow Automation Experts
   Developers of workflow and automation tools like CASSANDRA and AiiDA, enabling streamlined and sustainable simulation workflows and data management.

5. Programming Language Experts
   Developers and contributors to programming languages such as C++, Fortran, Python, and Java, particularly those interested in optimizing energy efficiency in scientific and high-performance computing.

6. Hardware Specialists
   Experts in GPU, HPC, and CPU development from leading hardware companies, focusing on sustainable hardware design and energy-efficient computing infrastructure.

7. HPC Center Representatives
   Specialists from major European HPC centers, including Barcelona Supercomputing Center (BSC), CINECA (Italy), Jülich Supercomputing Centre (Germany), Swiss National Supercomputing Centre (CSCS), LRZ (Leibniz Rechenzentrum, Germany), and SURFsara (Netherlands), with expertise in HPC systems, resource allocation, and sustainability.

8. Early-Career Researchers and Academics
   Researchers and academics focusing on algorithm development, hybrid modeling, machine learning integration, and hardware-software optimization for sustainable scientific computing.

9. Other Sustainability Advocates in Scientific Computing
   Anyone working in computational science, software development, or hardware design with an interest in sustainability and energy-efficient computing, bringing diverse perspectives and innovative ideas to the discussion.

We believe that it is essential not only to support code, model, and algorithm developers through established commercial packages but also to address the potential for redundant development that can occur in research groups. By creating a space for dialogue and exchange, this workshop provides an environment where both distinguished and early-career developers can share their experiences, learn from one another, and form meaningful collaborations.

The workshop will feature two interactive Bazaar Sessions designed to highlight and promote emerging talent, innovative ideas, and valuable tools within the scientific computing community. These sessions aim to foster collaboration, visibility, and engagement across diverse participants.

Bazaar 1: Career Development for Early-Career Researchers

This session is dedicated to young researchers and students who have worked independently. It provides a platform to showcase their skills, introduce their code, and present innovative ideas. Participants will have the opportunity to network, receive mentorship, and explore potential collaborations with established scientists and industry leaders.

Bazaar 2: Spotlight on Home-Grown Codes

This session focuses on group-developed tools or small packages released on platforms like GitHub. It aims to make the potential of these niche or specialized application codes visible to distinguished professors, computational center representatives, and package specialists attending the workshop. This is an excellent opportunity to bring attention to innovative solutions and facilitate their integration into the broader scientific community.

Structure:

1. Presentations:

   • Each participant will have 7 minutes to present their code or tool.

   • The presentation should focus on:

     • Introducing the code/tool and its purpose.

     • Highlighting the unique or innovative features included.

     • Demonstrating the talent and skills that went into the development process.

   • Participants are encouraged to share links (e.g., GitHub, repositories, or project sites) where the code is hosted, allowing attendees to access and explore it further.

2. Posters and Interaction:

   • After the short demo introductions, participants will display their work as posters in a designated area (the salon).

   • These posters will remain available for the entire duration of the workshop, giving attendees ample time to revisit and engage with the developers.

3. Engagement:

   • Attendees can interact with the presenters during dedicated poster viewing times to ask questions, provide feedback, and discuss potential collaborations.

The combination of brief presentations and in-depth poster displays ensures participants can both highlight their work to a broad audience and engage in deeper discussions.

We encourage all interested participants to apply and share their work with the workshop attendees.

📥 Apply Here
Submit your application to showcase your work at one of the bazaar sessions. The application form can be accessed here.

To ensure the workshop covers diverse perspectives and fosters meaningful discussions, we aim to include co-organizers representing key areas of scientific computing. Each co-organizer brings expertise from a distinct domain, supporting a holistic approach to addressing sustainability challenges:

• Fabio Affinito
  CINECA, Italy
  Fabio Affinito leads the specialist support team at CINECA and has extensive experience in large-scale classical and quantum atomistic simulations. He has participated in the PRACE IP projects and serves as the WP4 leader within the MaX CoE for Materials.

• David Hardy
  Beckman Institute, University of Illinois at Urbana-Champaign, USA
  David Hardy is a senior developer of NAMD, a molecular dynamics software package. With a Ph.D. in Computer Science and expertise in algorithms and software development, he contributes a strong background in optimizing molecular simulations for energy efficiency and performance.

• Anton Kozhevnikov

• Dr. Anton Kozhevnikov (male) received his PhD in condensed matter physics in 2007. He did a postdoctoral research at Joint Institute of Computational Sciences (UT/ORNL) and then at ETH Zürich. He is presently a computational scientist and a group lead at CSCS in the Scientific Software and Libraries unit. He is a leading developer of SIRIUS domain specific library.

• Kosar Khajeh

Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt

Kosar Khajeh holds a Ph.D. in Mechanical Engineering. Her research focuses on hybrid modeling and complex fluid flow. As a user of scientific computing packages and a young researcher with a passion for environmental sustainability, she initiated the proposal for this workshop to address the pressing challenges of sustainability in scientific computing☺️

• Evangelia Charvati

Eduard-Zintl-Institut für Anorganische und Physikalische Chemie, Technische Universität Darmstadt

We encourage anyone interested in contributing to the workshop to reach out. The complete list of co-organizers and confirmed participants will be updated and shared soon.

This page is dedicated to presenting the main concept of the workshop and introducing the esteemed speakers and participants who have graciously accepted to join and collaborate. They come from diverse backgrounds, including academia, industry, and computational centers, with a shared goal of fostering collaboration and advancing cutting-edge developments in the field.

I warmly invite you to reach out to me with any feedback, questions, or suggestions. Your input is invaluable!

📧 Email: kosar.khajeh@tu-darmstadt.de, khajeh.k.2005@gmail.com