Super-linear speed-up of a parallel multigrid Navier-Stokes solver on Flosolver

In parallel computing, scalability is an important issue and getting linear speed-ups is difficult for most codes. Super-linear speed up has been achieved on an eight-processor Flosolver system for a multigrid Navier-Stokes code. The physical problem solved, the parallelization method, the speed-ups obtained and possible explanations for this result are discussed here

Preliminary results on the simulation of the 1999 Orissa supercyclone using a GCM with a new boundary layer code

We present here preliminary results from the simulation of the Orissa supercyclone using a new AGCM code (named Varsha) written as part of a NMITLI project. The simulation is initialized at 00 UTC, 26 October 1999, using ECMWF T-106 initial conditions. The control run is made using the Varsha code at a T-80 resolution with a standard Monin-Obukhov boundary layer code incorporating a gustiness factor. With the horizontal resolution improved to 120 spectral modes with a 78 km grid spacing, and a new boundary layer parameterization at low winds, the code shows substantial improvements: the maximum error is reduced from 350 to 234 km at 36 h after initialization, 310 to 34 km at 48 h, and 410 to 55 km at 96 h. It is suggested that part of the explanation for this improvement lies in the improved estimation of surface forces and torque in the new boundary layer code. The role of torque is particularly interesting as the major contribution to it comes from the outer regions of the cyclone where the winds are relatively low but the area on which the surface force acts and its moment arm are both high. Intriguingly the higher surface forces arise also from the higher winds predicted by the new code. An interesting finding is that, on both track and minimum pressure, the improvement due to higher resolution is greater with the new boundary layer module. Further analysis is necessary to assess the effect of other eddy fluxes (sensible heat, moisture) on cyclone track prediction

Methodological Role of Mathematics to Estimate Human Blood Pressure Through Biosensors

This paper presents a non-invasive technique and cuff less method for blood pressure measurement with a hardware prototype implementation. The sophisticated feature called pulse transit time (PTT) is extracted and investigated with a development of a smart system which consists of ECG, PPG sensor to estimate the systolic and diastolic blood pressure with support of advanced signal processing methodologies. The proposed method experiments have been carried out in hospital environment and tested with real time patients to validate the proposed method. The maximum error percentage of the proposed system has been shown to be 5.3% of systolic blood pressure (mmHg) and 4.7% of diastolic blood pressure (mmHg). This system also allows the monitoring of patient hypertension and overcome the limitation of cuff-based hospitalized measurement system

Comprehensive software module for interactive graphics

The Comprehensive Software Module for Interactive Graphics(COSMIG) has been designed to operate using a data file. The portability of the data file and the graphics commands as a total database is an important feature of COSMIG. The data created using COSMIG can be edited either through direct modification of the graphic command parameters or through interactive cursor movement facilities on the screen. The package provides creation, positioning and dimensioning of graphic symbols. The information is stored in a tightly formatted data structure which can be used to redraw the figure with changes in dimension, position, scaling and rotation. These can be accomplished through an in-built editor. The data structure used is the array with appropriate pointers to form a linked list. The figures created using COSMIG can be plotted on a Calcomp13; type plotter with the help of specially designed plotroutines through calcomp plotrotine ca11s

Development of parallel processing at NAL: A retrospect 13; 13;

The present report describes the design and development of the Flosolver series of parallel computers at NAL. Built with the specific aim of providing the much-needed computing power for complex aerospace problems, the Flosolver series has evolved from Flosolver Mk1 with four processing elements based on the 16-bit Intel 8086/8087 CISC processor, to the the latest version, Flosolver Mk3 with 7 processing elements based on the 32-bit Intel i860 RISC processor. Starting with a discussion of the strategies adopted in the design of these machines, the paper also discusses the various phases in the development and fabrication of the system software, and the application codes currently operational on them

Preliminary report on the parallelisation of the panel code on Flosolver

A Panel Code from SOFFTS has been parallelised and the advantage of parallel computing in terms of computing speed has been clearly demonstrated13;

Artificial Intelligence-Based Energy Management and Real-Time Optimization in Electric and Hybrid Electric Vehicles

The depletion of fossil fuel and growing environmental pollution has led to the transformation of the transportation industry with the development of electric vehicles that run on clean and green energy. The rapid development in this field is driven towards replacing traditional power structures with smart power management models. This directs towards improving the efficiency of fuel cells and the system output performance in electric and hybrid electric vehicles. The fuel cell life is affected by the drive system and its control characteristics in a hybrid power system. The system operation is ensured by optimization of performance and strategical energy management in the hybrid system using power train model, dynamic programming (DP), and deep learning schemes. Tuning the equivalent factor (EF) dynamically can be done by equivalent consumption minimum strategy (ECMS) in plug-in hybrid electric vehicles (PHEVs) for achieving near-optimal fuel efficiency. Artificial intelligence is used for determining the EF in ECMS by analysis of available data. The State of Charge (SoC) values are varied to perform simulation under diverse conditions. When compared to the existing optimization techniques, the proposed model offers improved fuel economy. The energy management scheme is also time-conscious as the computational time for the entire trip duration is optimized. The training sample size and its impact on the performance of the AI module are also discussed

Status report on the parallelised version of NCMRWF forecast13; model on Flosolver

Detailed comparisons between the Cray output and the Flosolver output for 1-day' forecast using NCMRWF forecast model have been made. The calculations have been made both13; in single precision and double precision for a critical assessment of build up of rowld off error. The calculations show that there are no meteorologically significant differences between the outputs, the remaining difference may be ascribed to the differences in input, machine dependent features, library definition etc. and for practical purposes, single precision calculation is adequate13

Super-linear speed-up of a parallel multigrid navier-stokes solver on flosolver

In parallel computing, scalability is an important issue and getting linear speed-ups is difficult for most codes. Superlinear speed-up has been achieved on an eight-processor Flosolver system for a multigrid navier-stokes code. The physical problem solved, the parallelization method, the speed-ups obtained and possible explanations for this result are discussed here

NCMRWF Forecast Model: Implementing the recommendations of13; the review committee

Based on the recommendations of the Review Committee13; a double precision calculation for a one-day forecast using13; the parallelised version of .'JCMRWF Forecast Model has13; been made on Flosolver Mk3. The calculations show that13; there are no meteorologically significant differences between the Cray output Clnd the Flosolver output. The existing differences which are insignificant may be ascribed to the differ'ences in input, machine dependent features, library definitions etc