Resources
Promoting interdisciplinary collaboration and scholarly exchange by facilitating cross-disciplinary research initiatives that leverage the transformative potential of open source software and Generative AI across diverse fields of inquiry. This pillar emphasizes the importance of breaking down silos and fostering synergies between researchers from disparate domains to address complex research challenges and unlock new avenues of exploration.
Scientific Software
Georgia Tech researchers are leaders in developing new scientific software, which is necessary to simulate newphenomena or obtain results more accurately and/or more quickly. Key products include the ]programs for quantum chemistry, astrophysics, fluid dynamics, genetic sequence alignment, gene prediction, and for building open-source GPUs.
Infrastructure Resources
Cloudhub
The Cloud Hub, founded in 2021 is an integral part of the Institute for Data Engineering and Science (IDEaS) at Georgia Tech. Our mission is to facilitate access to industry funding for the diverse and interdisciplinary research communities within the institution. We strive to ensure that researchers have the necessary resources to advance their work, encompassing access to cloud resources, comprehensive training and development programs, and crucial monetary support. At Cloud Hub, we are committed to creating an environment where innovative research can flourish.
Infrastructure Grants
Over the years, IDEaS has invested in a set of core cyberinfrastructure resources to support its research mission. These resources include four large-memory AMD Genoa machines, a DGX GPU 100 machine, eight L40S GPU machines, and a peta-scale storage repository. In July, we solicited proposals for infrastructure credits on these resources. In keeping with IDEaS’s thematic focus on and machine learning, we have awarded twelve different proposals aligned with these topics. We have dispensed more than $ 250,000 in infrastructure credits for the next financial year, for projects in diverse areas including development of transformer models for time series forecasting, training long-context vision-language-action models, advancing AI models in neutrino astrophysics, generative AI in protein engineering, AI models of nonlinear dynamics in cardiac tissues, and using AI to improve accuracy in automatic piano transcription.
Center for Artificial Intelligence in Science and Engineering (ARTISAN)
ARTISAN accelerates science and engineering by integrating cutting-edge AI techniques and supporting researchers in operationalizing workflows with cyberinfrastructure. Cybershuttle, for example, is a user-facing environment that integrates local and campus resources, cloud services, and NSF-funded national computing centers to support end-to-end scientific workflows, with a strong user-centered design.