SET

From HP-SEE Wiki

Revision as of 12:09, 15 June 2012

General Information

• Application's name: Simulation of Electron Transport
• Application's acronym: SET
• Virtual Research Community: Computational Physics
• Scientific contact: Todor Gurov, Aneta Karaivanova, (gurov, anet)[@]parallel.bas.bg
• Technical contact: Emanouil Atanassov, emanouil[@]parallel.bas.bg
• Developers: Assoc. Prof. Dr. E. Atanassov, Department Grid Technology and Applications. IICT-BAS, Bulgaria
• Web site: http://gta.grid.bas.bg

Short Description

SET uses Monte Carlo methods in order to solve integral equations describing electron transport. The methods use variance reduction for reducing the required CPU time. Billions of simulated trajectories are required for achieving accurate results. The application of these methods can benefit simulation of semiconductor devices at the nano-scale as well as other problems in computational electronics.

The advanced variance reduction techniques in this application require fast inter-process communication (using MPI or similar type of interface), while the total number of trajectories is in the number of billions. Thus a large scale computational resource with fast interconnection is required (a supercomputer or HPC cluster).

Problems Solved

The application deals with simulation of semiconductor devices at small scale and attempts to provide new insights into the physical phenomena that are occurring.

Scientific and Social Impact

Accurately predict or model new physical effects, occurring at the small scales (nanometer and femtosecond) scale. The reduced physical dimensions of contemporary electronic devices make quantum effects increasingly relevant for modeling the device operation.

The improved understanding of these physical effects can allow further improvement in the design of semiconductor devices. Bulgaria has a tradition in the electronic industry and nowadays there are efforts to revive these activities.

Collaborations

• IME-TU, Vienna, Austria
• RBI, Zagreb, Croatia

Beneficiaries

• Researchers in the field of semiconductor physics
• Manufacturers of small scale semiconductor devices

Number of users

11

Development Plan

• Concept: Done before the project started.
• Start of alpha stage: Done before the project started.
• Start of beta stage: M8
• Start of testing stage: M9
• Start of deployment stage: M15
• Start of production stage: M16

Resource Requirements

• Number of cores required for a single run: From 1 to up to 8000
• Minimum RAM/core required: 100 MB
• Storage space during a single run: 1 GB
• Long-term data storage: 10 GB
• Total core hours required: 3 000 000

Technical Features and HP-SEE Implementation

• Primary programming language: C
• Parallel programming paradigm: MPI/OpenMP
• Main parallel code: MPI
• Pre/post processing code: Own developer
• Application tools and libraries: SPRNG library, scrambling sequences

Usage Example

Infrastructure Usage

• Home system: HPCG/BG
  • Applied for access on: 09.2010
  • Access granted on: 09.2010
  • Achieved scalability: 512 cores
• Accessed production systems:

1. BG/BG
   • Applied for access on: 10.2010
   • Access granted on: 10.2010
   • Achieved scalability: 2048 cores

• Porting activities: The application has been successfully ported from the x86-64 Infiniband cluster system (HPCG) to the IBM BlueGene/P machine. Some of the code needed to be corrected, especially to take into account that the IBM system is 32bit and to comply with the IBM compiler rules.
• Scalability studies: Tests on 512, 1024 and 2048 cores on IBM Blue Gene /P.

Running on Several HP-SEE Centres

• Benchmarking activities and results: At the initial phase the application was benchmarked and optimized on the HPCG cluster at IICT-BAS. After successful deployment on 512 cores the second phase of the benchmarking was initiated and it was deployed on the Bulgarian Super Computer. It was tested there and showed good scalability results on 512, 1024 and 2048 cores. The test case uses 10 millions of trajectories to simulation 180 femtosecond evolution.
• Other issues: Code corrections, especially due to the IBM system being 32bit.

Achieved Results

The SET application was testing with new random number generators using permutations. Optimizations of transition density using genetic algorithm and acceptance-rejection methods were done. Initial scientific results for simulation of electron transport on quantum wires and are obtained.

Publications

• S. Ivanovska, A. Karaivanova, N. Manev, “Numerical Integration Using Sequences Generating Permutations”, 8th LSSC’11, June 6-10, 2011, Sozopol, Bulgaria, accepted to LNCS, 8 pages, 2011.
• T. Gurov, S. Ivanovska, A. Karaivanova, N. Manev, Monte Carlo Methods Using a New Class of Congruential Generators, ICT Innovations 2011, Sept. 14-16, 2011, Skopje, LNCS, Springer, ISSN: 1867-5662
• Т. Gurov, E. Atanassov, A. Karaivanova, “Monte Carlo methods for Electron Transport: Scalability Study”, Munich June 25-29, ISPDC2012 (submitted)
• E. Atanassov, T. Gurov, A. Karaivanova, Efficient Implementation of a Stochastic Electron Transport Simulation Algorithm Using GPGPU Computing, AMITANS 2012, June 2012, Varna, Bulgaria (submitted)

Foreseen Activities

• Message oriented frameworks overcome some deployment limitations like lack of common Grid middleware are installed. This problem is planned to be solved in next step, but it is not an immediate problem for production use.
• The availability of HPC resources enables new research to be performed where we will be investigating the impact of the applied electric field on the devices made from different semiconductor materials.