A COMPLETE WEATHER FORECASTING SUITE ON PARAM

10000

Presented by- Sukanta pal Rgdn. No-0701106280 branch-IT

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Agenda Introduction. Need for Weather Forecasting. PARAM 10000. Design Approach. Numerical algorithm. The Weather Forecasting Capabilities. Accuracy Issue And Fault Tolerance Conclusion. References

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INTRODUCTION What is weather forecasting?

Prediction of atmospheric state for a given time and location

Why to forecast? Air traffic Agriculture Marine Private sector Forestry Military application

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Methods of weather forecast SynopticStatisticalNumerical

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Numerical Forecasting Computer simulation of atmospheric condition. It includes

i. Data collectionii.  Data assimilation and analysisiii.  Numerical weather predictioniv.  Model output post processing

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PARAM 10000

PARAM is a series of supercomputers developed by CDAC. It is India’s first Teraflop Supercomputer.  The major applications of PARAM 10000 includes

1. long-range weather forecasting

2. remote sensing

3. drug design and

4. molecular modelling.

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Design approach

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Based on cluster models of SMPs Has 1gb of RAM per node.

Message passing communication software like MPI and PVM.

Low latency, high bandwidth supported communication software

KSHIPRA.

Lightweight communication protocols on the PARAMNET

and MYRINET

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Numerical Algorithm Derived from conservation laws of mass, momentum, and energy. Two conditions .

If it is a linear quantity, then the representations are straight forward.

If it is a non-linear term, spectral transform methods have to be used.

The computations for spectral algorithms consists of following steps

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Weather Forecasting capabilities1. Parallelisation Strategy

Involves of Identification of code and subsequent compute intensive parts and their data dependencies

Latitude is taken as the most obvious and clear independent data for computation work in this algorithm.

Major computation is done through the use of Fourier and Legendre transform.

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A pair of latitudes is placed on one processor

Each processor computes Fourier coefficients using the inverse Legendre transform and the gaussian grid point values using the inverse Fourier transform

Partial sum of the Legendre transform is performed on each

processor for given latitudes.

Then these sums are circulated among all the processors to have global sum on each of the processor

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2 Implementation

CRAY assembly language was replaced by the Temperton's Fortran algorithm.

The important components of this code are the I. I/O, the forecast loop(GLOOPA), the radiation loop (GLOOPR) which is

called once in twelve hours.

II. Physics loop (GLOOPB), FFT and Legendre transform. GLOOPA and GLOOPB .

The data distribution of parallel T80 is along the latitudes distributed over the processors. This is a master-workers model

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Accuracy Issue Performance strongly linked to the architectural features like clock

speed, main memory bandwidth.

Message sending proportional to message length but independent of node location and network traffic.

Four cpus in a single node responsible for low latency of message passing between the processors.

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Fault Tolerance Independent Processing can be run independentently using an

interface.

Fault tolerance save re-running of the codes from system failures.

System failure recovered by restarting JCL.

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Conclusion Parallel Climate models T2l/T42 and Forecast models T80/T126

have been developed.

Achieve fault tolerance and accuracy.

Access to greater number of cpus thereby enhancing scalability.

Give better performances than before.

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Referenceshttp://www.iitr.ac.in/centers/CC/pages/

Resources+Param_1000.htmlhttp://www.cdac.in/html/press/3q09/

spot687.aspxhttp://pune.cdac.in/html/secg/cas.aspx http://pune.cdac.in/html/npsf/npsfidx.aspx http://pune.cdac.in/html/npsf/param10k/

benchmp.aspx http://www.buyya.com/papers/cdacrep.txt http://en.wikipedia.org/wiki/

Remote_direct_memory_access 20

THANK YOU

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