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gRASPA

gRASPA (pronounced “gee raspa”) is a GPU-accelerated Monte Carlo simulation software built for molecular adsorption in nanoporous materials, such as zeolites and metal-organic frameworks (MOFs).

Installation

Installation in clusters

To install gRASPA on NERSC (DOE) and QUEST (Northwestern) clusters, check out Cluster-Setup

Installation on local machines

A detailed installation note for gRASPA on CentOS/Ubuntu 24.04 is documented in the manual here

Compatible GPUs

  • For NVIDIA GPUs, gRASPA code has been tested on the following NVIDIA GPUs:
    • A40, A100, RTX 3080 Ti, RTX 3090, RTX 4090.
    • 🤯: RTX 3090/4090 is faster than A40/A100 for gRASPA
  • gRASPA has a SYCL version (experimental) that supports other devices, available in Releases

Quick Start

gRASPA Manual

Reference

  • gRASPA paper is now online. Please kindly cite it if you find it useful.
  • Also, please give our repository a ⭐ if our code helps!

Table of Code Capabilities

Functionalities gRASPA gRASPA-fast gRASPA-HTC
Simulation Types
Canonical Monte Carlo
(NVT-MC)
✔️ ✔️ ✔️
Grand Canonical Monte Carlo
(GCMC)
✔️ ✔️ ✔️
Transition-Matrix Monte Carlo
in grand canonical ensemble
(GC-TMMC)
✔️ ✔️
Mixture Adsorption via GCMC ✔️
NVT-Gibbs MC ✔️ ✔️
Interactions
Lennard-Jones (12-6) ✔️ ✔️ ✔️
Short-Range Coulomb ✔️ ✔️ ✔️
Long-Range Coulomb: Ewald Summation ✔️ ✔️ ✔️
Analytical Tail Correction ✔️ ✔️
Machine-Learning Potential
(via LibTorch and cppFlow)
✔️
Moves
Translation/Rotation ✔️ ✔️ ✔️
Configurational-Bias Monte Carlo (CBMC) ✔️ ✔️
Widom test particle insertion ✔️ ✔️
Insertion/Deletion
(without CBMC)
✔️ ✔️ ✔️
Insertion/Deletion
(with CBMC)
✔️ ✔️
Identity Swap ✔️
NVT-Gibbs volume change move ✔️ ✔️
Gibbs particle transfer ✔️ ✔️
Configurational Bias/
Continuous Fractional Components
(CB/CFC) MC
✔️ ✔️
Extra Functionalities
Write: LAMMPS data file ✔️ ✔️ ✔️
Read: LAMMPS data file ✔️
Write: Restart files
(Compatible with RASPA-2)
✔️ ✔️
Read: Restart files ✔️ ✔️
Peng-Robinson Equation of State ✔️
Automatic Determination
of # unit cells
✔️

Authors

  • Zhao Li (Northwestern University, currently at Purdue University)
  • Kaihang Shi (Northwestern University, currently at University at Buffalo)
  • David Dubbeldam (University of Amsterdam)
  • Mark Dewing (Argonne National Laboratory)
  • Christopher Knight (Argonne National Laboratory)
  • Alvaro Vazquez Mayagoitia (Argonne National Laboratory)
  • Randall Q. Snurr (Northwestern University)