Globus.org

Argonne National Laboratory just launched a first-of-its-kind artificial intelligence (AI) inference service to help researchers across the nation accelerate discovery and innovation - https://bit.ly/4uyBxnp Until now, scientists who wanted to use AI had to build and maintain their own computer systems to run these models. The new Argonne Leadership Computing Facility inference service handles all the technical work behind the scenes, so researchers can focus on running simulations, analyzing experiments, and processing massive datasets. #ArgonneFriends

From exascale supercomputing to powerful AI systems and services, the ALCF provides computing resources, capabilities, and expertise to help researchers accelerate discovery and innovation across science and engineering domains. Explore our annual report to learn how the facility and our user community are advancing HPC and AI for science: https://ar25.alcf.anl.gov

At the Advanced Photon Source at Argonne National Laboratory, rapid data analysis powered by ALCF supercomputers is enabling scientists to adjust experiments on the fly, refine hypotheses, and make the most of their beam time. This capability, supported by tools like Globus.org, is also helping pave the way for new efforts under the American Science Cloud, a cornerstone of DOE's Genesis Mission. Learn how the ALCF-APS integration is impacting research at the X-ray Photon Correlation Spectroscopy (XPCS) beamline: https://lnkd.in/gNe3YfYZ

I am happy to invite you all to our ISC special talk session together with Kyle Chard, Taina Coleman, and Rafael Ferreira da Silva, titled "Towards Exascale Scientific Productivity: Next Generation Application, Workflows, and HPC Infrastructure Platforms" on Tuesday, 23rd June, 4:00-5:00. The exascale era is ushering in a transformative future for science — from high-resolution global climate simulations and in situ personalised medicine to digital twins of complex physical and biological systems. Yet making effective use of that capability is becoming increasingly challenging. These challenges stem from the emerging complexity of the technology, the scientific questions being asked, and shifting demands. The answer is not primarily about designing ever-bigger machines or chasing higher peak performance; it calls for rethinking applications, workflows, and platforms together, and for bold experimentation with emerging technologies — particularly AI systems, accelerators, and workflow orchestrators — across the discovery process. This session explores that shift, carrying research communities and software ecosystems forward together for sustainable long-term benefit. We challenge the classical notion of exascale computing as defined solely by a single large-scale exaflop system. Instead, we treat exascale productivity as a community capability — the ability to deliver orders-of-magnitude more scientific computing performance within a given energy budget, across a broad set of applications. Getting there will require experimenting forward and taking risks, and we invite stakeholders across the community to join the effort. Two invited talks offer complementary perspectives. The first looks ahead to AI-driven science, exploring how autonomous workflows can shorten discovery cycles and unlock exascale-class performance. The second anchors innovation in user enablement and co-design — the prerequisites for durable change and real scientific uptake. We cordially invite you to contribute to this discussion and share your ideas and inspirations. #ExascaleHPC #ScientificWorkflows #AcceleratingDiscovery #ISCHighPerformance