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National Power systems Conference (NPSC)

作者： Jainendra Jain Palem Benny Sudhakar Katta Jagan Mohan R Senthil Kumar S Bindhumadhava Bapu Real Time Systems Group Centre for Development of Advanced Computing Bengaluru India

With the advent of renewable energy, smart grids, and cutting-edge measurement technologies, modern power systems are becoming more complex. As a result, analyzing modern power systems requires more computational power. High Performance computing (HPC) is the most viable option for meeting this demand. In India’s power sector, the use of HPC is minimal. Hence, we are introducing HPC-based power flow analysis, which is the highly used application to analysis the system. The paper demonstrates the importance of HPC for power flow analysis. This paper also discusses a modified Gaussian Elimination method to utilize the sparse nature of Jacobian matrix to speedup the computation. Open-Multi Processing (OpenMP) is used to implement parallel computing. Parallel power flow analysis is simulated on the Central Processing Unit (CPU) and Graphics Processing Unit (GPU) nodes of the C-DAC’s PARAM Utkarsh supercomputer for various power system networks. The speedup obtained with HPC for the Polish 9241 bus network is 216.14 times the sequential computation.

关键词： Renewable energy sources Power measurement High performance computing Simulation Graphics processing units Supercomputers Power systems

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Analysis of communication channel attacks on control systems—SCADA in power sector 1

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3rd International Conference on India Smart Grid Week, ISGW 2017

作者： Kalluri, Rajesh Mahendra, Lagineni Senthil Kumar, R.K. Ganga Prasad, G.L. Bindhumadhava, B.S. Real Time Systems and Smart Grid Group Centre for Development of Advanced Computing Bengaluru India

ISBN: (数字)9789811082498

ISBN: (纸本)9789811082481

Usage of open standard protocols such as IEC 60870-5-101/104 in supervisory control and data acquisition (SCADA) systems which are not provided with security features leaves vulnerabilities for the attacker. Adopting these protocols in power SCADA draws more attention to attacker since a successful attack at one location may lead to catastrophic failure and may lead to a blackout. The critical communication channel in power SCADA is between remote terminal unit (RTU) and master terminal unit (MTU), and they communicate over IEC 60870-5-101/104 protocols. Any successful attack on this channel may lead to disastrous effect [1–3]. Simulation of attacks targeting this communication channel provides a better perception of impact for any successful attack. In this paper, attacks on communication channel have been discussed using an influence diagram. Experiments are also conducted to study the impact of communication channel attacks on power system which is simulated using real-time digital simulator (RTDS). This paper brings out the details of the experiment conducted and the results thus obtained. This paper also discusses countermeasures to protect systems from such kind of attacks. © Springer Nature Singapore Pte Ltd. 2018.

关键词： SCADA systems

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Power and Performance Modeling of Scientific Applications for Energy Optimization in High Performance computing 22

Power and Performance Modeling of Scientific Applications fo...

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22nd International Conference on advanced computing and Communication, ADCOM 2016

作者： Raghu, H.V. Ganga Prasad, G.L. Real Time Systems and Smart Grid Group Centre for Development of Advanced Computing C-DAC Knowledge Park Bangalore India

ISBN: (纸本)9781538623893

The increase in power consumption of High Performance computing (HPC) systems have became an important concern. Many decades of race for performance has increased the total power consumption of supercomputers. Very few studies provide deep insights into the power and energy consumption of scientific applications. A detailed performance, power and energy analysis is essential to identify the most compute intensive and costly parts of an application and to develop possible improvement strategies. In this paper, we focus on power and performance modeling of various HPC benchmarks and scientific applications in order to reduce energy consumption. We study the powerperformance efficiency and conserve energy using Dynamic Voltage and Frequency Scaling (DVFS) for scientific applications such as High Performance Linpack (HPL) benchmark, NAS Parallel Benchmarks (NPB), Multiple Em for Motif Elicitation (MEME), STREAM and Seasonal Forecasting Model (SFM). The HPC applications are executed in certain voltage and frequency (v/f) for CPU. The v/f used for execution of a job has a key impact on overall energy consumption. We evaluated HPC scientific applications by changing v/f during run-time for CPU and observed an average measured energy savings of 11.6% and a maximum of 14.8% with less than 5% performance degradation. The approach is to reduce energy at run-time by slowing down (applying voltage and frequency scaling) the processor during light workloads. The processor will deliver high performance whenever required, while significantly reducing power consumption during low workload periods. Our idea is to profiling and characterizing the application into multiple sections using time slicing to efficiently determine optimal frequency and voltage combinations over all the sections in the application using knowledge base. Selecting an optimal frequency and voltage by profile based technique requires several runs of the application with varying input data sizes. Another methodolo

关键词： Energy conservation

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Adaptive Power Management for HPC applications

Adaptive Power Management for HPC applications

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IEEE International Conference on Green High Performance computing (ICGHPC)

作者： Sumit Kumar Saurav Ganga Prasad G.L Manisha Chauhan Real Time Systems and Smart Grid Group Centre for Development of Advanced Computing Bengaluru India

Reduction of power and energy consumption is one of the major concerns and challenges for High Performance computing (HPC). However, as we move towards Exascale, it will be power limited in future. The advent of Running Average Power Limit (RAPL) abstraction after sandy bridge processors has paved the way to manage power adaptively. This gives the fine-grained power measurement and control mechanism with integrated voltage regulator at core level based on power budget. The purpose of Adaptive Power Management System (APM) for HPC systems is to decide when to place power manageable components into various power saving states based on the power consumption of an application within the power budget. In HPC, jobs are distributed across various computing nodes and power management is more complex with respect to the placement of the components in required operating states. The real time power monitoring and controlling through RAPL interface gives an opportunity for adaptive management. In this paper, we describe fine-grained profiling of HPC applications and control mechanism at component level using RAPL and APM system. The idea is to profile the HPC applications at fine granular level by measuring the power consumed by various power manageable components of a node such as processors and DRAM so that more accurate power related information can be obtained and then adaptively learn and devise the Optimal Power Budget (OPB) of an application. The OPB information is stored in Knowledge Base (KB). The devised OPB for HPC application with optimal number of processors is incorporated in the job scheduler to take power-aware scheduling decision.

关键词： Program processors Power demand Power measurement Voltage control Energy consumption High performance computing Energy efficiency

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Benders' decomposition applied to Energy Resource Management in smart distribution networks

Benders' decomposition applied to Energy Resource Management...

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Clemson University Power systems Conference (PSC)

作者： J. Soares Bruno Canizes Z. Vale G. K. Venayagamoorthy GECAD - Research Group on Intelligent Engineering and Computing for Advanced Innovation and Development Polytechnic of Porto Porto Portugal Real-Time Power and Intelligent Systems Lab. Clemson University Clemson SC USA

This paper proposes a Benders' decomposition approach for the large-scale Energy Resource Management (ERM). The problem considers large amount of Distributed Energy Resources (DER) including Electric Vehicles (EVs) with gridable capacity. The proposed model is designed for Virtual Power Players/Plants (VPPs) managing a smart distribution network with the aim to maximize profits considering the day-ahead time horizon. Previous literature has shown difficulties in solving similar problems using classical techniques in a centralized scheme, namely considering nonlinear network constrains. The proposed approach reduces computational burden of the original Mixed Integer Nonlinear Programming (MINLP) problem. The Benders' cuts are introduced for the ERM formulation in order to allow the communication between the slave and the master problem. Analysis of two large-scale instances have been carried out for smart distribution networks, namely a 33-bus and a real Portuguese 180-bus network assuming high penetration of DERs and EVs.

关键词： Energy resources Optimization Partial discharges Load flow Smart grids Processor scheduling Load management

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PAAS: Power aware algorithm for scheduling in high performance computing

PAAS: Power aware algorithm for scheduling in high performan...

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2013 IEEE/ACM 6th International Conference on Utility and Cloud computing, UCC 2013

作者： Raghu, H.V. Saurav, Sumit Kumar Bapu, Bindhumadhava S. Real Time Systems and Smart Grid Group Centre for Development of Advanced Computing C-DAC Knowledge Park Bangalore India

ISBN: (纸本)9780769551524

Energy consumption has become the major concern in High Performance computing (HPC) systems as far as operational cost, reliability of systems and environmental impacts are concerned. The optimization of energy consumption in HPC systems is challenging task. The frequency/voltage used for execution of a job has a key impact in overall energy consumption. In this paper, we have implemented Power Aware Algorithm for Scheduling (PAAS), which focuses on energy reduction and load balancing aspects of HPC systems. The PAAS guides the scheduler to take intelligent decisions based on the information available in knowledge base. The Scheduler provides an optimal energy aware schedule for each node to minimize the make span across nodes and to reduce energy consumption. The knowledge base gives the optimal frequency and voltage where energy consumption is minimal for a particular job. The Dynamic Voltage and Frequency Scaling (DVFS) knobs are tuned across the nodes based on predicted optimal frequency and voltage. We used hardware based power measurement device Watts up?.NET meter for individual computing nodes as well as Multi-Agent framework for monitoring and analyzing energy consumption. We evaluated the algorithm on the experimental test-bed with the set of scientific applications. Our technique showed an average measured energy savings of 12.64% and a maximum of 13.5%. © 2013 IEEE.

关键词： Energy utilization

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An intelligent energy optimization approach for MPI based applications in HPC systems

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CSI Transactions on ICT 2013年第2期1卷 175-181页

作者： Bhavyasree Unni Nazia Parveen Ankit Kumar B. S. Bindhumadhava Real Time Systems and Smart Grid Group Centre for Development of Advanced Computing Bangalore India

Energy-aware computing is gaining more and more attention in high performance computing (HPC) environment. As an outcome of this, various energy-aware techniques are existing and many are being proposed. But it is difficult to have a technique which saves energy without compromising the performance. This paper talks about a novel energy optimization approach for Message Passing Interface (MPI) applications running on HPC systems. Our approach relies on applying Dynamic Voltage Frequency Scaling (DVFS) at node level by an optimization agent. Whenever MPI processes are idle or busy with I/O operations, the corresponding CPU cores run at higher frequencies, which results in wastage of power. During this time, CPU cores frequencies can be reduced using DVFS so that the energy can be saved. Our approach is based on a Multi-agent based intelligent energy management framework, which uses an optimization agent for implementing energy optimization algorithm. The key advantage of the proposed approach is that the performance will not be compromised while achieving energy savings.

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SCADA communication protocols: vulnerabilities, attacks and possible mitigations

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CSI Transactions on ICT 2013年第2期1卷 135-141页

作者： Durga Samanth Pidikiti Rajesh Kalluri R. K. Senthil Kumar B. S. Bindhumadhava Real Time Systems and Smart Grid Group Centre for Development of Advanced Computing Bangalore India

Current hierarchical SCADA systems uses communication protocols which aren’t having the inbuilt security mechanism. This lack of security mechanism will help attackers to sabotage the SCADA system. However, to cripple down the SCADA systems completely coordinated communication channel attacks can be performed. IEC 60870-5-101 and IEC 60870-5-104 protocols are widely used in current SCADA systems in power utilities sector. These protocols are lacking in the application layer and the data link layer security. Application layer security is necessary to protect the SCADA systems from Spoofing and Non-Repudiation attacks. Data link layer security is necessary to protect the systems from the Sniffing, Data modification and Replay attacks. IEC 60870-5-101 & 104 communication protocol vulnerabilities and their exploitation by coordinated attacks are explained in this paper. Proposed experimental research model can be used to mitigate the attacks at application layer and data link layer by adopting the IEC 62351 standards.

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PAAS: Power Aware Algorithm for Scheduling in High Performance computing

PAAS: Power Aware Algorithm for Scheduling in High Performan...

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IEEE International Conference on Utility and Cloud computing (UCC)

作者： H.V. Raghu Sumit Kumar Saurav Bindhumadhava S. Bapu Real Time Systems and Smart Grid Group Centre for Development of Advanced Computing Bangalore INDIA Centre for Development of Advanced Computing Juhu Maharashtra IN

Energy consumption has become the major concern in High Performance computing (HPC) systems as far as operational cost, reliability of systems and environmental impacts are concerned. The optimization of energy consumption in HPC systems is challenging task. The frequency/voltage used for execution of a job has a key impact in overall energy consumption. In this paper, we have implemented Power Aware Algorithm for Scheduling (PAAS), which focuses on energy reduction and load balancing aspects of HPC systems. The PAAS guides the scheduler to take intelligent decisions based on the information available in knowledge base. The Scheduler provides an optimal energy aware schedule for each node to minimize the make span across nodes and to reduce energy consumption. The knowledge base gives the optimal frequency and voltage where energy consumption is minimal for a particular job. The Dynamic Voltage and Frequency Scaling (DVFS) knobs are tuned across the nodes based on predicted optimal frequency and voltage. We used hardware based power measurement device Watts up? .NET meter for individual computing nodes as well as Multi-Agent framework for monitoring and analyzing energy consumption. We evaluated the algorithm on the experimental test-bed with the set of scientific applications. Our technique showed an average measured energy savings of 12.64% and a maximum of 13.5%.

关键词： Energy consumption Scheduling Knowledge based systems Processor scheduling Power demand Optimization time-frequency analysis

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Big Data: Prospects and Challenges

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Vikalpa 2015年第1期40卷 74 - 96页

作者： Janakiraman Moorthy Rangin Lahiri Neelanjan Biswas Dipyaman Sanyal Jayanthi Ranjan Krishnadas Nanath Pulak Ghosh (Coordinator) Director and Professor of Marketing at the Institute of Management Technology Dubai. Earlier he was Professor of Marketing at the IIM Calcutta and IIM Lucknow. He received his PhD from IIM Ahmedabad. His recent research papers were published in the leading scholarly ournals such as Marketing Science British Food Journal Journal of Information Technology Case and Application Research Journal of Database Marketing & Customer Strategy Management. He has wide experience in the banking and investment industry. He was earlier the Global Research and Project Director of the Institute for Customer Relationship Management Atlanta USA. He was the Convener of the prestigious CAT Exam 2011. e-mail: Practice Director leading Atos India's CRM practice while supporting Strategic Business Development for North American Market. With an experience of more than 15 years Rangin has worked extensively as a Business Consultant in Information Technology (Sales Automation Marketing & Service Management area) Customer Data Management and CRM Analytics. e-mail: Business Consultant at Atos with extensive experience in Business Analysis Risk Management Analytics Business Development Presales Solution Ideation on Enterprise Data Management Enterprise Reference Data and Master Data Management area. e-mail: founder and CEO of dono consulting a boutique quantitative analytics and investment research firm. He has worked for leading financial firms in New York and India including Dow Jones Blackstone Sorin Capital (VP Quantitative Modeling) and Thomson Reuters (Head of Real Estate Analytics). A CFA charter holder and Commonwealth Scholar Deep has an MS (Applied Economics) from University of Texas Dallas and an MA (Economics) from Jadavpur University e-mail: Professor in the Information Systems Group of the Institute of Management Technology Ghaziabad. Her PhD is in the field of data mining from Jamia Millia Islamia Central University India. She has published five edited books. She is serving on the editorial b

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