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General Information

  • Application's name: Self Avoiding Hamiltonian Walk on Gaskets
  • Application's acronym: SFHG
  • Virtual Research Community: Computational Physics Applications
  • Scientific contact: Sreten Lekic, slekic@blic.net
  • Technical contact: Sreten Lekic, slekic@blic.net
  • Developers: Sreten Lekic, Faculty of Mech. Engineering, University of Banja Luka (UoBL), Bosnia - Herzegovina, Igor Sevo, Mihajlo Savic Faculty of Electrical Engineering, University of Banja Luka (UoBL), Bosnia - Herzegovina
  • Web site: http://wiki.hp-see.eu/index.php/SFHG

Short Description

Hamiltonian self avoiding walks on fractals (Sierpinsky gaskets) are one of perspective models for long polymers (DNA, RNA and other bio polymers) behavior description.

We have developed a program for counting self-avoiding Hamiltonian walks to run on multiple processors in a parallel mode. We study Hamiltonian walks (HWs) on the family of two-dimensional modified Sierpinski gasket fractals, as a simple model for compact polymers in nonhomogeneous media in two dimensions. We apply an exact recursive method which allows for explicit enumeration of extremely long Hamiltonian walks of different types: closed and open, with end-points anywhere in the lattice, or with one or both ends fixed at the corner sites. The leading term n is characterized by the value of the connectivity constant 1, which depends on fractal type, but not on the type of HW.

Problems Solved

New serial C++ code produced. Parallelization of serial C++ code done in OpenMP.

Scientific and Social Impact



Faculty of Science. Dept of Physics

Number of users


Development Plan

  • Concept: 2012-06-01
  • Start of alpha stage: 2012-10-01
  • Start of beta stage: 2013-01-01
  • Start of testing stage: 2013-01-15
  • Start of deployment stage: 2013-02-15
  • Start of production stage: 2013-03-01

Resource Requirements

  • Number of cores required for a single run: up to 64
  • Minimum RAM/core required: <1GB
  • Storage space during a single run: <1GB
  • Long-term data storage: <1GB
  • Total core hours required: <32000

Technical Features and HP-SEE Implementation

  • Primary programming language: C/C++
  • Parallel programming paradigm: OpenMP
  • Main parallel code: Nested OpenMP
  • Pre/post processing code: N/A
  • Application tools and libraries: libgomp, gcc, gprof

Usage Example

Infrastructure Usage

  • Home system: PARADOX
    • Applied for access on: 2010-09-01
    • Access granted on: 2010-09-01
    • Achieved scalability: 8
  • Accessed production systems: .
    • Applied for access on: 2010-09-01
    • Access granted on: 2010-09-01
    • Achieved scalability: 8
  2. Pecs SC
    • Applied for access on: 2013-01-18
    • Access granted on: 2013-01-21
    • Achieved scalability: 48
  3. Szeged SC
    • Applied for access on: 2013-01-18
    • Access granted on: 2013-01-21
    • Achieved scalability: 24
  • Porting activities: Emulated implementation of OpenMP functions not implemented in older versions of gcc/libgomp
  • Scalability studies: Scalability studies performed at PARADOX (up to 8 CPU cores), BA-01-ETFBL (up to 16 CPU cores) and Pecs SC (up to 48 CPU cores). Detailed results available in Deliverable D8.4.

Running on Several HP-SEE Centres

Application is currently running at PARADOX, Pecs SC and Szeged SC.

  • Benchmarking activities and results: Performed scalability study for D8.4. Achieved 207k Walks/s for level 8 and 132k Walks/s for level 9.
  • Other issues: Issues with incomplete or missing support for specific OpenMP features with Open64 and Portland Group compilers.

Achieved Results

  • We have calcualted exact number of walks for previously unavailable levels 8 and 9 for all needed types of walks.
  • We have created a novel approach to solution of the problem without resorting to brute-force walk counting.


Foreseen Activities

  • Optimization of parallelization approach to tasks - partially completed.
  • Creating MPI code.
  • Creating hybrid MPI+OpenMP code.
  • Performing all types of walks at the same time (most likely via MPI).
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