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6th International Conference and Exhibition on Smart Grids and Smart Cities, ISUW 2020

作者： Hareesh, Reddi Senthil Kumar, R.K. Kalluri, Rajesh Bindhumadhava, B.S. Real Time Systems & Internet of Things Center for Development of Advanced Computing Bengaluru India

ISBN: (纸本)9789811690075

With ever growing cyber threats on critical infrastructures, need of deploying the security measures to protect these should be of utmost priority. However, without knowing about the assets in the network and what needs to be secured, all the threat modeling activities, strategies or mitigation/remediation activities will be incomplete or ineffective. Hence the critical infrastructure asset discovery and monitoring is a vital part for providing security. But unlike IT networks where asset discovery is automated, critical infrastructures often perform asset discovery and management manually which leads to incomplete and inefficient asset tracking and management over time and makes it ineffective in quick identification and response to potential threats. An automated approach for asset discovery and management is significant to secure critical infrastructures from cyber security incidents and other threats. This paper proposes an automation methodology for asset discovery, managing and monitoring. The solution is compliant to several NERC-CIP requirements and NCIIPC guidelines. It involves identification and real time monitoring of the critical assets connected to the network, baseline network behavior, maintain repository of asset details, compliance check adhering to policies and generates real time network map for visualization in the Purdue model for the better management of the assets. And it also generates incidents compatible with third party SOC/ SIEMs. The solution helps to reduce the risk of cyber security incidents in critical infrastructures. © 2022, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Critical infrastructures

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Vibration and displacement analysis of carbon nanotube based cantilever for NEMS applications 2

Vibration and displacement analysis of carbon nanotube based...

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2nd International Conference on Communication and Electronics Systems, ICCES 2017

作者： Verma, Manu Singh, Balwinder Chabbra, Varun Devi, Rekha Academic and Consultancy Services and Division Center of Development of Advanced Computing Mohali Punjab India

ISBN: (纸本)9781509050130

The cantilever is a wide-ranging structure used in nano electromechanical (NEMS) applications including sensors, actuators or in probes for the detection of displacement, mass, and charge. High sensitivity, selectivity, wide dynamic range and fast response time are required for applications in real time monitoring. Carbon nanotubes provide exceptional electrical and mechanical properties like high tensile strength, large surface area, high elasticity, flexibility, high electrical and thermal conductivity which give rise to new sensing concepts. This paper proposes the design and analysis of cantilever made up of carbon nanotube using finite element method to analyze the displacement of cantilever gets affected by varying load. The effect of thickness change on the resonant frequency of the cantilever for CNT material is also analyzed. It is found that that the simulation values of displacement for carbon nanotube are 1.11E-5 at 10 N/m2 and 5.56E-5 at 50 N/m2 The simulation values of resonant frequency for CNT material are 4.42E7 at the thickness of 1nm and 6.73E8 at 15nm. © 2017 IEEE.

关键词： Carbon nanotubes

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Parallelization of reverse time migration using MPI + OpenMP

Parallelization of reverse time migration using MPI + OpenMP

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2016 International Conference on advanced Communication Control and computing Technologies, ICACCCT 2016

作者： Akanksha, S. Kansara Kumar, Gardas Naresh Gujarat Technological University Gujarat India Center of Development for Advanced Computing Pune India

ISBN: (纸本)9781467395458

Increasing computational power ensures effective implementation of high-end HPC applications but does not guarantee performance. Seismic modelling is one such high computational demanding application. In oil and gas industries, reverse time migration is one of the important migration algorithms that guarantees accurate imaging results but its practical implementation gets hindered due to its high computational cost. In this paper we will discuss reverse time migration for solving 2D wave equations using finite difference method and its parallel implementation using Message Passing Interface(MPI) and OpenMP. © 2016 IEEE.

关键词： Message passing

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Seasonal ensemble forecasting application on dependable sumegha scientific cloud infrastructure

Seasonal ensemble forecasting application on dependable sume...

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2016 International Symposium on Grids and Clouds, ISGC 2016

作者： Laveti, Ramesh Naidu Prahladarao, B.B. Arackle, Vineeth Simon Arunachalam, B. Center for Development of Advanced Computing C-DAC Knowledge Park Byappanahalli Bangalore India

Despite several advances in understanding the behaviour of monsoon variability, innovations in the numerical modeling and the availability of higher computational capabilities, accurate prediction of Indian summer monsoon still remains a serious challenge. Seasonal Forecast Model (SFM), developed for seasonal forecast and climate research, is used for forecasting the Indian summer monsoon in advance of a season. Ensemble forecasting method helps us in finding and minimizing the uncertainty inherent in seasonal forecast. The inherent parallel nature and the bursty computational demands of the ensemble forecasting method allows it to effectively utilize the Infrastructure-as-a-Service (IaaS) model on the cloud platform. However, realizing huge scientific experiments is still a challenge to the cloud service providers as well as to the climate modeling community. To start with prototype experiments using SFM model were conducted at T-62 resolution (~ 200 km x 200 km grid). The experience gained from the prototype runs were used by the SuMegha operational team to fine tune the configuration of SuMegha Cloud resources to improve the quality of service. High resolution SFM at T-320 (~ 37 km x 37 km grid) was also configured and experiments were conducted to understand the scalability, computational performance of the application and the reliability of SuMegha Cloud. In this paper, we use SFM as a case study to present the key problems found by climate applications, and propose a framework to run the same on SuMegha Cloud infrastructure to allow a climate model to take advantage of these cloud resources in a seamless and reliable way. The framework uses classification and outlier detection techniques to classify the resources and also to identify the faulty resources. It addresses the challenges such as unexpected hardware failures, power outages, failed porting and software bugs. We share our experience in conducting the ensemble forecasting experiments on SuMegha Cloud u

关键词： Climate models

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PARALLEL computing AT CRS4

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INTERNATIONAL JOURNAL OF MODERN PHYSICS C-PHYSICS AND COMPUTERS 1993年第6期4卷 1315-1321页

作者： SCHEININE, AL Parallel Computing Group Center for Advanced Studies Research and Development in Sardinia via Nazario Sauro 10 I-09123 Cagliari Italy

An overview is given of parallel computing work being done at CRS4 (Centro di Ricerca, Sviluppo e Studi Superiori in Sardegna). Parallel computation projects include: parallelization of a simulation of the interaction of high energy particles with matter (GEANT), domain decomposition for numerical solution of partial differential equations, seismic migration for oil prospecting, finite-element structural analysis, parallel molecular dynamics, a C++ library for distributed processing of specific functions, and real-time visualization of a computer simulation that runs as distributed processes.

关键词： DOMAIN DECOMPOSITION GEANT SEISMIC MIGRATION PARALLEL MOLECULAR DYNAMICS

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Loop partitioning unimodular transformations for distributed memory multiprocessors 5

Loop partitioning unimodular transformations for distributed...

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5th International Parallel Processing Symposium, IPPS 1991

作者： Kulkarni, D. Kumar, K.G. Basu, A. Paulraj, A. Center for Development of Advanced Computing 2/1 Brunton Road Bangalore560 025 India

ISBN: (纸本)0818691670

We present a unimodular transformation called rotation to partition the iteration space of a perfectly nested loop. The transformation captures the individual transformations like loop interchange, reversal, and skewing in a uniform framework. Though the transformation is for any architecture, we have specifically addressed its application to distributed memory machines in this paper. We prove that the transformation is free from deadlocks. We finally describe the choice of an optimal rotation based on the parallelism factor, load imbalance and the volume of communication in the transformed space. © 1991 IEEE.

关键词： Memory architecture

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Deep Neural-Based Machine Translation Using RNN for Indian Languages 7th

Deep Neural-Based Machine Translation Using RNN for Indian L...

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7th International Conference on advanced computing and Intelligent Engineering, ICACIE 2022

作者： Singh, Shashi Pal Kumar, Ajai Pundir, Kanishka AAIG Center for Development of Advanced Computing Pune India Banasthali Vidyapith Rajasthan Banasthali India

ISBN: (纸本)9789819950140

This study describes how to develop a machine learning system for the translation of Indian languages (Hindi, Gujarati, and Punjabi) using a form of deep neural network (DNN). We are employing a form of RNN called long short-term memory (LSTM). The state-of-the-art algorithm for sequential data is recurrent neural networks (RNNs). This research work pertaining to RNN-based translation of Indian Languages involved experimenting with nmt models (unidirectional nmt and bidirectional) and their hyperparams to devise results important from real-world perspective. We employed the neural machine translation (NMT) model to get the best results. Unlike the standard phrase-based translation system, which consists of many small sub-components that are tweaked independently, this approach allows a single system to be trained directly on the source and target text and attempts at neural machine translation. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Long short-term memory

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Carving of bitmap files from digital evidences by contiguous file filtering

Carving of bitmap files from digital evidences by contiguous...

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International Conference on Security in Computer Networks and Distributed Systems, SNDS 2012

作者： Chelliah, Balan Vidyadharan, Divya S. Shabana, P. Thomas, K.L. Center for Development of Advanced Computing Trivandrum Ministry of Communications and Information Technology Government of India India

ISBN: (纸本)9783642341342

An evidence file is a bit-stream copy of any digital storage media or a hard disk partition. Retrieving files from these evidence files without the intervention of file system is quite challenging as the storage locations where file contents are stored are unknown or the contents of files are unavailable in contiguous storage locations. In addition to this, portion of some of the deleted files might have been overwritten by new files. In this paper, we propose a method to carve bitmap files from evidence files by making use of the presence of slack area in the evidence file. The contiguous file filtering technique proposed in this paper makes the carving of fragmented files easier. © 2012 Springer-Verlag.

关键词： Hard disk storage

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A multilayer deep learning framework for auto-content tagging 5th

A multilayer deep learning framework for auto-content taggin...

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5th International Conference on advanced Machine Learning Technologies and Applications, AMLTA 2020

作者： Jain, Shikha Jain, Ajit Kumar Singh, Shashi Pal Banasthali Vidyapith BanasthaliRajasthan India AAI Center for Development of Advanced Computing Pune India

ISBN: (纸本)9789811533822

With the rapid and recent development of Internet of things (IoT), Bigdata, the most fundamental challenge is to explore the large volume of data from heterogeneous data sources (logs, audio, video, reports, news, social media, etc.). The tools and techniques that are being used in successful transforming of structured data into business intelligence simply do not work when it comes to unstructured data. An estimated 80% of data held by firms today are unstructured. We have powerful computations tools such as graphics processor units (GPUs) for complex calculations and Hadoop, spark for Bigdata management still technology is lacking in complete utilization of available data. Deep learning is a powerful tool to resolve the issues related to data, such as automatic extraction of complex data and representation of large volume unsupervised and uncategorized raw data. But extracted data do not have any standard format. In the survey of Bigdata mining system and IoT systems, it has been found that a layer is needed in Bigdata mining framework that can work on structured, unstructured and semi-structured data and can integrate the complete raw data. The proposed framework is a multilayer deep learning model that performed the clustering of unstructured huge text data followed by classification layer, CNN, to extract features and classify the raw data clusters in parallel manner. Conversion of unstructured data in standard format by automates content tagging helps decision-making systems to easily identify the related data and increase the data utilization. © Springer Nature Singapore Pte Ltd 2021.

关键词： Multilayers

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Loop partitioning for distributed memory multiprocessors as unimodular transformations 91

Loop partitioning for distributed memory multiprocessors as ...

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5th ACM International Conference on Supercomputing

作者： Kulkarni, D. Kumar, K.G. Basu, A. Paularj, A. Center for Development of Advanced Computing 2/1 Brunton Road Bangalore 560 025 India

ISBN: (纸本)0897914341

In this paper, we present a unimodular loop transformation called rotation as a simple, systematic and uniform method for partitioning the iteration spaces of doubly nested loops for execution on distributed memory multiprocessors. We define three parameters which could be used to choose an optimal rotation. These parameters are the parallelism factor, the load imbalance and the volume of communication. We present algebraic expressions for these parameters and discuss their relative significance in choosing a combined metric. © 1991 ACM.

关键词： Iterative methods

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