DOE Laboratory Practicum

Review abstracts for DOE CSGF practicums at Argonne >>

Argonne National Laboratory (ANL) is a multidisciplinary science and engineering research center, where more than 1,400 talented scientists and engineers work together to answer the biggest questions facing humanity, from how to obtain affordable clean energy to protecting ourselves and our environment. Ever since we were born out of the University of Chicago’s work on the Manhattan Project in the 1940s, our goal has been to make an impact — from the atomic to the human to the global scale.

A key element of Argonne’s HPC activities is the Argonne Leadership Computing Facility(ALCF). The current ALCF flagship system is Aurora, an exascale supercomputer with over 10,000 nodes based on Intel Data Center CPU and GPU Max Series devices. Polaris, a 44 PFLOPs, 560-node machine with NVIDIA A100 GPUs is also available to researchers. Both machines are configured with the HPE Slingshot 11 interconnect, which has a Dragonfly topology with adaptive routing. ALCF offerings also include Sophia, a NVIDIA DGX A100 system, and an AI Testbedwith next-generation AI-accelerator machines.

Argonne also operates the Laboratory Computing Resource Center(LCRC), which features Improv, an 825-node CPU cluster with AMD Epyc nodes, Bebop, a 672-node CPU cluster with Intel Xeon nodes, and Swing, an NVIDIA-based GPU cluster. Additionally, Argonne hosts the Joint Laboratory for System Evaluation, which houses a range of emerging systems.

Qualified graduate students may use these ANL computing resources during the course of their research.

Various projects are available for fellowship students in many areas of basic science, including the following:

Artificial Intelligence for Science
foundational and applied machine learning, special-purpose AI hardware accelerators, integration of simulation and machine learning, self-driving labs

Biology
functional genomics, genome sequence analysis, metabolic reconstruction, structural biology, neuroscience, targeted drug discovery and design, cancer biology

Chemistry and Chemical Technologies
computational quantum chemistry, chemical kinetics, energy storage, biofuels, catalyst design and discovery, combustion chemistry

Climate Modeling and Environmental Science
climate model development, design of coupled modeling software, atmospheric carbon dioxide distribution, multimodal data assimilation, precision agricultural, microbial ecological modeling

Engineering
traffic flow models and forecasting, manufacturing science, industrial control, nuclear reactor design simulation, device-scale combustion modeling, turbulent combustion

Materials Science and Nanoscience
vortex dynamics, molecular dynamics, superconductivity, nanoscale photonics, electronics and magnetism

Mathematics and Computer Science
parallel tools and libraries, numerical PDEs, scalable I/O, mathematical optimization, performance modeling, large-scale data analytics and assimilation, cloud computing, computational fluid dynamics, uncertainty quantification, statistical modeling and methods, quantum computing, automatic differentiation, edge computing

Physics and Astrophysics
high energy physics, Monte Carlo methods in nuclear physics, numerical simulations of thermonuclear flashes, extreme-scale cosmological simulations, plasma physics and fusion simulation, machine learning for multimessenger astrophysics