ASCR Program Manager
Rich Carlson
Phone: 301-903-9486


The primary mission of the Advanced Scientific Computing Research (ASCR) program is to discover, develop, and deploy computational science and high-performance networking tools and services that enable researchers in scientific disciplines to analyze, model, simulate, and predict complex phenomena in the areas of Energy, Environment and Security that are important to the Department of Energy. To accomplish this mission, ASCR funds research at public and private institutions and at DOE laboratories to foster and support fundamental research in applied mathematics, computer science, and high-performance network research. In addition, ASCR supports multidisciplinary scientific research through computational science partnerships with other Office of Science programs and other elements of the Department.

ASCR also operates high-performance computing (HPC) centers and related facilities, and maintains a high-speed network infrastructure (ESnet). The HPC facilities include the Leadership Computing Facility at Oak Ridge National Laboratory (OLCF), the Leadership Computing Facility at Argonne National Laboratory (ALCF), and the National Energy Research Scientific Computing Center (NERSC) at Lawrence Berkeley National Laboratory (LBNL).

ASCR is interested in receiving innovative applications that have scientific merit and offer prospects for technical success in the following areas:

  1. Advanced Network Technologies and Services - Network operators face a growing need for advanced tools and services to better manage their infrastructure. Network users also need better tools and services to
    1. deal with the increasing amounts of data being generated, moved, and archived; and
    2. help in reporting real problems that impact their ability to use the network. Hardening existing tools and services that manage the explosive growth in data will make it easier for users to use the network.

    Developing new technologies, tools, or high-level services that promote a modular use of measurement and monitoring data will make it easier for network operators to manage their infrastructure. These new modular tools and services should provide multiple levels of detail to authorized personnel with decisions on the level of detail to release under the control of the infrastructure owner. Applications should also be permitted to retrieve summary information to assist users in reporting problems. This will allow network operators to receive the detailed information needed to fix a problem while simplifying the users’ ability to report a problem. Meeting both types of needs using a single measurement and monitoring infrastructure would greatly improve the network experience for a large number of users.

    This topic solicits proposals that address issues related to building, operating, and maintaining large network infrastructures, developing tools and services that report performance problems in a manner suitable for network engineers or application users, or hardening existing tools and services that deal with Big Data.

  2. Increasing Adoption of HPC Modeling and Simulation in the Advanced Manufacturing and Engineering Industries - Over the past 30 years, The Department of Energy’s (DOE) supercomputing program has played an increasingly important role in scientific research by allowing scientists to create more accurate models of complex processes, simulate problems once thought to be impossible, and analyze the increasing amount of data generated by experiments. Computational Science has become the third pillar of science, along with theory and experimentation. However despite the great potential of modeling and simulation to increase understanding of a variety of important engineering and manufacturing challenges, High Performance Computing (HPC) has been underutilized due to application complexity, the need for substantial in-house expertise, and perceived high capital costs. This topic is specifically focused on bringing HPC solutions and capabilities to advanced manufacturing and engineering market sectors.