Electronic structure of nanotubes by utilizing the helical symmetry properties: The code parallelization

Electronic structure of nanotubes by utilizing the helical symmetry properties: The code parallelization

Project reference: 1807

In calculations of nanotubes methods prevailing are based on a one-dimensional translational symmetry using a huge unit cell. A pseudo two-dimensional approach, when the inherent helical symmetry of general chirality nanotubes is exploited and has been limited to simple approximate model Hamiltonians. Currently, we are developing a new unique code for fully ab initio calculations of nanotubes that explicitly uses the helical symmetry properties. Implementation is based on a formulation in two-dimensional reciprocal space where one dimension is continuous whereas the second one is discrete. Independent particle quantum chemistry methods, such as Hartee-Fock and/or DFT or simple post Hartree-Fock perturbation techniques, such as Moller-Plesset 2nd order theory, are used to calculate the band structures.

The student is expected to cooperate on the further parallelization of this newly developed implementation and/or on performance testing for simple general nanotube model cases. Message Passing Interface (MPI) will be used as the primary tool to parallelize the code.

The aim of this work is to improve MPI parallelization to enable highly accurate calculations for the band structures of nanotubes on distributed nodes, with distributed memory. Furthermore, the second level parallelization in inner loops over the processors of individual nodes would certainly enhance the performance together with a combination with using threaded BLAS routines.

By improving the performance of our new software, we will open up new possibilities for tractable highly accurate calculations of energies and band structures for nanotubes with predictive power and with facilitated band topology whose interpretation is much more transparent than in the conventionally used one-dimensional approach. We believe that this methodology will soon become a standard tool for in-silico design and investigation in both the academic and commercial sectors.

General case nanotube with helical translational symmetry.

Project Mentor: Prof. Dr. Jozef Noga, DrSc.

Project Co-mentor: Mgr. Lukáš Demovič, PhD.

Site Co-ordinator: Mgr. Lukáš Demovič, PhD.

Learning Outcomes:
The student will familiarize themself with MPI programming and testing, as well as with ideas of efficient implementation of complex tensor-contraction based HPC applications. A basic understanding of treating the translationally periodic systems in physics will be gained along with the detailed knowledge of profiling tools and parallelization techniques.

Student Prerequisites (compulsory):
Basic knowledge of MPI and Fortran.

Student Prerequisites (desirable):
BLAS libraries and other HPC tools, knowledge of C/C++.

Training Materials:
Articles and test examples to be provided according to an actual students profile and skills.


  • Weeks 1-3: Training; profiling of the software and design simple MPI implementation, Deliver Plan at the end of week 3.
  • Weeks 4-7: Optimization and extensive testing/benchmarking of the code.
  • Week 8: Report completion and presentation preparation.

Final Product Description:
The resulting code will be capable of successfully and more efficiently completing the electronic structure calculations of nanotubes with a much simplified and transparent topology of the band structure.

Adapting the Project: Increasing the Difficulty
A more efficient implementation with the hybrid model using both MPI and Open Multi-Processing (OpenMP).

Adapting the Project: Decreasing the Difficulty
Profiling of the code to provide key information on the bottlenecks and a simple MPI parallelization of the main loops.

The student will need access to Fortran and a C++ compiler as well as MPI and OpenMP environment which can be provided by the host CC SAS.

Computing Centre of the Slovak Academy of Sciences

Tagged with: , , ,

Leave a Reply

Your email address will not be published. Required fields are marked *


This site uses Akismet to reduce spam. Learn how your comment data is processed.