New HPC Algorithm Energizes Faster, Scalable Simulations of Chemical Systems
A first-of-its-kind algorithm developed at Georgia Tech is helping scientists study interactions between electrons. This innovation in modeling technology can lead to discoveries in physics, chemistry, materials science, and other fields.
The new algorithm is faster than existing methods while remaining highly accurate. The solver surpasses the limits of current models by demonstrating scalability across chemical system sizes ranging from large to small.
Computer scientists and engineers benefit from the algorithm’s ability to balance processor loads. This work allows researchers to tackle larger, more complex problems without the prohibitive costs associated with previous methods.
Its ability to solve block linear systems drives the algorithm’s ingenuity. According to the researchers, their approach is the first known use of a block linear system solver to calculate electronic correlation energy.
The new algorithm is faster than existing methods while remaining highly accurate. The solver surpasses the limits of current models by demonstrating scalability across chemical system sizes ranging from large to small.
Computer scientists and engineers benefit from the algorithm’s ability to balance processor loads. This work allows researchers to tackle larger, more complex problems without the prohibitive costs associated with previous methods.
Its ability to solve block linear systems drives the algorithm’s ingenuity. According to the researchers, their approach is the first known use of a block linear system solver to calculate electronic correlation energy.