SPADES: Scalable Parallel Discrete Events Solvers

Scalable Parallel Discrete Solvers (SPADES) simulate event-driven complex systems in the renewable energy application space, with a particular focus on heterogeneous computing architectures, such as graphics processing units.

As renewable energy systems, from mobility to human behavior models, become larger and more interconnected—with agents' actions triggering a cascade of reactions nearly instantaneously—there is an increasingly urgent need for a method to simulate event-driven complex systems on high-performance-computing resources.

The development of novel numerical algorithms will achieve a high efficiency, SPADES engine to run and manage interagent interactions on state-of-the-art computing architectures. This parallel discrete event solver (PDES)-engine approach will address shortcomings within state-of-the-art PDES (where the current discrete event solvers limit simulation size and fidelity) as demonstrated on renewable energy specific applications such as traffic networks, human behavior modeling, and material growth.

These novel algorithms for PDES implemented in a SPADES engine for heterogenous computing architectures such as graphics processing units will benefit much of the U.S. Department of Energy's discrete events solver research portfolio by enabling frameworks, such as Hierarchical Engine for Large-Scale Infrastructure Co-Simulation, to leverage modern high-performance computing resources at leadership facilities.

Development Team

The SPADES development team includes Marc Henry de Frahan, Ethan Young, and , and Deepthi Vaidhynathan.

Contacts