SEE-GRID-2 The SEE-GRID-2 initiative is co-funded by the European Commission under the FP6 Research...

The SEE-GRID-2 initiative is co-funded by the European Commission under the FP6 Research Infrastructures contract no. 031775

SEE-GRID-2

Ultra-fast Semiconductor Carrier Transport Simulation on the Grid.

SALUTE: New results for the inhomogeneous case

Aneta Karaivanova, Emanouil Atanassov and Todor Gurov

Institute for Parallel ProcessingBulgarian Academy of Sciences

Sofia, BulgariaE-mails:{anet, emanouil,gurov}@parallel.bas.bg

3rd User Forum, 11-14 February 2008, Clermont-Ferrand2

Outline

1. Introduction 2. Monte Carlo Methods4. Algorithms in SALUTE5. SEE-GRID Infrastructure6. Grid Implementation7. Numerical results8. Conclusion and future work


Introduction

SALUTE (Stochastic ALgorithms for Ultra-fast Transport in sEmiconductors) is a grid application, which integrates a set of novel Monte Carlo and quasi-Monte Carlo algorithms for solving various computationally intensive problems which describe ultrafast carrier transport in semiconductors.

SALUTE studies memory and quantum effects during the relaxation process due to electron-phonon interaction in semiconductors.The quantum kinetic model: a femtosecond relaxation process of optically excited carriers in one-band semiconductors or quantum wires. The electron-phonon interaction is switched on after a laser pulse creates an initial electron distribution. Two cases are considered – with and without applied electric field.


SALUTE - Stochastic ALgorithms for Ultra-fast Transport in sEmiconductors

Application area: SALUTE is a grid application developed for solving various

computationally intensive problems which describe ultrafast carrier transport in semiconductors.

Expected results and their consequences SALUTE studies memory and quantum effects during the

relaxation process due to electron-phonon interaction in semiconductors; present version explores electron kinetics in GaAs nano-wires.

Social and scientific impact Studying the quantum effects that occur at nanometer and

femtosecond scale have important scientific (novel advanced methods, investigation of novel physical phenomena) and social impact (by improving the process of designing nano-devices)

Potential or existing user or beneficiary community Scientists and engineers working in the area of

nanotechnology from Bulgaria, Macedonia, Austria, UK …


Monte Carlo Methods

J is a quantity to be estimated via a MCM (in our application: different functionals of the solution of the integral equation)θ is a random variable with E[θ]=JθN is the estimator with N samplesσ(θ)N-1/2 is the statistical errorReducing the error: Variance reduction (antithetic variates, control variates,

stratification, importance sampling) Using more powerful random numbers (quasirandom

numbers instead of pseudorandom)


Quantum-kinetic equation (inhomogeneous case)

The integral form of the equation:

Kernels:


Estimated Quantities

Wigner function: Energy (or momentum) distribution: Density distribution:

Backward time evolution of the numerical trajectories


Algorithms in SALUTE

Homogeneous case: MC algorithm-1 (Zero electric field, Zero temp.); MC algorithm -2 (with electric field, Zero temp.); Quasi-MC algorithm (with el. field, different temp.) Importance Separation MC - 3 (zero el. field and

temp.) - new;

Inhomogeneous case (Carrier-phonon collisions are non-local in space): MC algorithm-4 (Zero electric field, Zero

temperature) Hybrid MC algorithm-5 (With electric field, zero

temp.) – new MC algorithm -6 ( with Field, with temperature) - new.

O(exp(ct2)/N(1/2))

O(exp(ct)/N(1/2))


Parallel Monte Carlo

Parallelism is an alternative way to accelerate the convergence of a Monte Carlo computation If n processors execute n independent copies of a MC computation, the accumulated result will have a variance n time smaller than that of a single copyA computational grid has attractively tremendous large amount of computational power Effectively exploring the power of distributed MC application requires

that the underlying random number streams in each subtask are independent in a statistical sense

Running quasi-MC in parallel is more challenging because division into subtasks is a non-trivial problem


SALUTE – Infrastructure usage and characteristics

Reasons for running the application on the grid Quantum problems are very computationally intensive. The inherent parallel nature of MC applications makes

efficient use of Grid resources.

Grid implementation scheme

AMGA – ARDA Metadata CatalogueWMS – Workload Management SystemCE – Computing ElementWN – Worker NodeFTS – File Transfer ServiceSE – Storage Element (dCache or other)GUI – Graphical User InterfaceOther Core Services – MyProxy, R-GMA, BDII, VOMS, LFC


SALUTE Demonstration

Monitoring of jobs and file transfers

Visualization of the Wigner function in 3D on the fly

Analysis of results


Application Results

Results in the inhomogeneous case Wigner function for

evolution time 175 fs Electron density

The results were obtained after 1000-1500 CPU hours The Wigner function

without an applied fieldThe Wigner function with an applied field

Electron density

Comparing Electron density with/without

applied field


Application Results

Results in the inhomogeneous case Wave vector Energy density

The results were obtained after running 1000-1500 CPU hours (500 jobs of 2-3 hours each)

Wave vector with/without applied electric field

Wave vector

Energy density


Grid implementation scheme for SALUTE

The SALUTE application requires accumulation of results from millions and even billions of trajectoriesThe Grid implementation scheme of SALUTE distributes the work between Grid sites and ultimately Grid WorkerNodes, and utilizes the various Grid Core services in order to manage the job execution and results accumulation. The data about every run is stored for later reuse and comparison, using Storage Elements and AMGA metadata catalogue.We make use of the new services, available in the gLite middleware, for more efficient and robust implementation of the SALUTE computational model, especially in its management of the generated data.

For example, the File Transfer Service is used in order to control the usage of networking resources and to avoid overloading of storage elements.


Average peak usage of SEE-GRID by SALUTE

•Number of jobs – 1000•Mean duration of job – 10 hours•Number of used CPU hours – 10000•Number of file transfers – 3000•Total storage used – 30GB•Time to finish – 24 hours•Sites used – 20


Usage of SEE-GRID by SALUTE

Progress in number of jobs completed after submission of 420 jobs to 21 SEE-GRID sites.


BG apps accounting vs some official EGEE appl

VOs Normalize CPU time

Fusion 208 372

Geant4 197 445

esr 125 805

magic 31 092

BG applications 12 applications 268 439 hours11 185 days, 30,6 years150000 hours (SALUTE)


Plans for Future

Special points allowing good progress SALUTE is supposed to work on any properly configured SEE-

GRID site. SALUTE can utilize the CPU power of the less resourceful SEE-

GRID sites. In order to be able to solve the new applied problems that we face we will need more CPU power

MPI support needs to be improved

Future work on SALUTE Continue to improve the algorithms performance Polish the User Interface Implement workaround for MPI on non-MPI enabled sites, that

would not require application recompilation

SEE-GRID-2 The SEE-GRID-2 initiative is co-funded by the European Commission under the FP6 Research...

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