SFHG
From HP-SEE Wiki
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
Collaborations
Beneficiaries
Faculty of Science. Dept of Physics
Number of users
3
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: .
- PARADOX
- Applied for access on: 2010-09-01
- Access granted on: 2010-09-01
- Achieved scalability: 8
- Pecs SC
- Applied for access on: 2013-01-18
- Access granted on: 2013-01-21
- Achieved scalability: 48
- 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
Publications
Foreseen Activities
- Creating hybrid MPI+OpenMP code.
- Performing all types of walks at the same time.