Skip to main content

Argonne National Laboratory has access to three main facilities for computing resources; data and networking; and data analytics and visualization.


Joint Laboratory for System Evaluation

The Joint Laboratory for System Evaluation (JLSE) is a collaboration between the Mathematics and Computer Science (MCS) Division and the Argonne Leadership Computing Facility (ALCF) with the aim of evaluating future high-performance computing platforms, developing system software and measuring power/energy. JLSE hosts more than two dozen different cutting-edge hardware platforms, including Intel development GPU cards (code names XeHP and DG1), as well as NVIDIA A100 and RTX8000 cards. The post-Moore architecture lab in MCS, which is part of JLSE, hosts an FPGA testbed.


Argonne Leadership Computing Facility

Argonne Leadership Computing Facility (ALCF) resources include leadership-class supercomputers, visualization clusters, advanced data storage systems, high-performance networking capabilities, and a wide variety of software tools and services to help facility users achieve their science goals.

  • Theta, an 11.69-petaflops supercomputer based on Intel processors and interconnect technology, an advanced memory architecture, and a Lustre-based parallel file system, are integrated by Cray’s HPC software stack. Theta is helping bridge the gap between Mira and Argonne’s next extreme-computing system, Aurora.
  • Cooley, the ALCF’s visualization cluster, enables users to analyze and visualize large-scale datasets. Equipped with state-of-the-art graphics processing units (GPUs),  Cooley helps users gain deeper insights into simulations and data generated on the facility’s supercomputers.
  • The Argonne AI-Testbed provides an infrastructure of next-generation AI-accelerator machines. It aims to help evaluate usability and performance of machine learning based high-performance computing applications running on these accelerators. Currently, the AI-Testbed consists of Cerebras, SambaNova, GraphCore, and Groq systems. See https://​ai​.alcf​.anl​.gov/​#​s​y​stems.
  • Polaris, a 35-45-petaflop CPU/GPU hybrid resource, is expected in 2021. It will allow users to prepare and scale their codes, and ultimately their science for future exascale systems. Polaris will comprise more than 500 nodes of 4 GPUs each. The system will be fully integrated with the 200-petabyte file system ALCF deployed in 2020, with increased data sharing support.
  • Aurora, Argonne’s first exascale computer, is expected in 2022. Aurora will feature Intel’s Xe GPU compute architecture, a CPU-GPU interconnect (PCI-e), a Cray Slingshot™ fabric system interconnect, and a Cray Shasta™ platform. Aurora’s revolutionary architecture will support machine learning and data science workloads alongside traditional modeling and simulation workloads.
  • Currently, the ALCF provides allocations on its resources, based on competitive proposals, through the INCITE program, the ASCR Leadership Computing Challenge, the ALCF Director’s Discretionary program, the ALCF Data Science Program, and the Aurora Early Science Program.


Laboratory Computing Resource Center

Apart from the ALCF facilities, Argonne also hosts several other resources in the Laboratory Computing Resource Center (LCRC). Bebop is the newest addition to the computational power of LCRC. It has 1,024 public nodes, with 128 GB (Intel Broadwell) / 96 GB Intel Knights Landing) of memory on each node. Blues, the second computing cluster, has approximately 350 public nodes, with 64 GB (Intel Sandy Bridge)/128 GB (Intel Haswell) of memory on each node. The LCRC resources are available to Argonne researchers and their collaborators through a simple internal proposal process.