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System Software

Argonne maintains a wide-ranging science and technology portfolio that seeks to address complex challenges in interdisciplinary and innovative ways. Below is a list of all articles, highlights, profiles, projects, and organizations related specifically to system software.

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  • An atomistic simulation toolkit for bridging length and time scales.Invention: Multi-fidelity scale bridging between various flavors of molecular dynamics (i.e. ab-initio, classical and coarse-grained models) has remained a long-standing challenge.
    Intellectual Property Available to License

    Invention:

    Multi-fidelity scale bridging between various flavors of molecular dynamics (i.e. ab-initio, classical and coarse-grained models) has remained a long-standing challenge. BLAST (Bridging Length/time scales via Atomistic Simulation Toolkit) is a framework that leverages machine learning principles to address this challenge.

    Opportunity and Solution 

    BLAST provides users with the capabilities to train and develop their own classical atomistic and coarse-grained interatomic potentials (i.e., force fields) for molecular simulations. BLAST is designed to address several long-standing problems in the molecular simulation community, such as unintended misuse of existing force fields due to a knowledge gap between developers and users, bottlenecks in traditional force field development approaches, and other issues relating to the accuracy, efficiency, and transferability of force fields. The BLAST architecture consists of a web user-friendly interface, front-end and back-end web services, and machine learning algorithms that run on high-performance computing (HPC) clusters.

  • SDN Multiple Operating System Rotational Environment (SMORE) utilizes software defined networking (SDN) to programmatically switch the flow of packets from users to a given set of servers. By periodically switching which servers respond to user requests.
    Intellectual Property Available to License

    Cybersecurity issues are a day-to-day struggle for businesses and organizations. Keeping information secure can be a herculean task. SMORE-MTD, developed by Argonne’s Joshua Lyle and Nate Evans with laboratory funding, defends against cybersecurity attacks by using software-defined networking to manipulate network paths that service user requests.

    By randomly selecting which server and service will respond to a given user’s request, SMORE-MTD makes it more difficult for an attacker to identify which services to attack. SMORE-MTD also increases organizations’ resilience by preventing an attacker exploit from being routed to the vulnerable software, forcing attackers into repeated attacks that are more likely to be noticed. SMORE-MTD also eliminates the need to install and maintain configuration software on each host in rotation, which reduces complexity and increases the amount of software available for use.

  • SVTRIP generates a naturalistic vehicle speed profile for a given route, which can be used to predict vehicle energy consumption and operations.
    Intellectual Property Available to License

    SVTRIP (Stochastic Vehicle Trip Prediction) generates a naturalistic vehicle speed profile (vehicle speed as a function of time at 1 Hz or more) for a given trip or route. The trip provided as an input is defined by the attributes of its sub-segments, such as travel time, distance and speed limit. The inputs can be provided directly by the user, extracted from digital maps, or generated from macroscopic or mesoscopic traffic flow simulators. The generated speed profiles can be used to predict vehicle energy consumption and operations for trips with low-resolution information. The algorithm used for generation relies on Markov Chains, making the generated speed profiles stochastic.