# Pushing Back the Limit of Ab-initio Quantum Transport Simulations on Hybrid Supercomputers

## TL;DR

This paper demonstrates a significant advancement in ab-initio quantum transport simulations by integrating CP2K and OMEN on hybrid supercomputers, achieving large-scale, high-efficiency calculations with novel algorithms.

## Contribution

The development of the SplitSolve algorithm enables efficient hybrid CPU-GPU computations, significantly reducing simulation time and scaling to large nanostructures.

## Key findings

- Over one order of magnitude reduction in time-to-solution
- Simulation of structures with over 50,000 atoms
- Parallel efficiency of 97% on thousands of nodes

## Abstract

The capabilities of CP2K, a density-functional theory package and OMEN, a nano-device simulator, are combined to study transport phenomena from first-principles in unprecedentedly large nanostructures. Based on the Hamiltonian and overlap matrices generated by CP2K for a given system, OMEN solves the Schroedinger equation with open boundary conditions (OBCs) for all possible electron momenta and energies. To accelerate this core operation a robust algorithm called SplitSolve has been developed. It allows to simultaneously treat the OBCs on CPUs and the Schroedinger equation on GPUs, taking advantage of hybrid nodes. Our key achievements on the Cray-XK7 Titan are (i) a reduction in time-to-solution by more than one order of magnitude as compared to standard methods, enabling the simulation of structures with more than 50000 atoms, (ii) a parallel efficiency of 97% when scaling from 756 up to 18564 nodes, and (iii) a sustained performance of 15 DP-PFlop/s.