Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045357
S. K. Mohapatra, K. P. Pradhan, Prasanna Kumar Sahu, D. Singh, Sashmita Panda
This paper investigates on the scaling capability of nanoscale ultra-thin (UT) silicon directly on insulator (SDOI) single gate (SG) and double-gate (DG) Metal Oxide Semiconductor Field-Effect Transistors (MOSFETs). An experiment is done by numerical modelling for both NMOS and PMOS by using device simulator TCAD Sentaurus. Based on the model, we conduct an investigation on Short Channel Effects (SCEs) like drain induced barrier lowering (DIBL), threshold voltage (Vth) shifting between two devices. Two types (Single and Double gate) enhancement type MOSFET has been studied for nanoscale CMOS digital application.
{"title":"Ultra-thin Si directly on insulator (SDOI) MOSFETs at 20 nm gate length","authors":"S. K. Mohapatra, K. P. Pradhan, Prasanna Kumar Sahu, D. Singh, Sashmita Panda","doi":"10.1109/ICHPCA.2014.7045357","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045357","url":null,"abstract":"This paper investigates on the scaling capability of nanoscale ultra-thin (UT) silicon directly on insulator (SDOI) single gate (SG) and double-gate (DG) Metal Oxide Semiconductor Field-Effect Transistors (MOSFETs). An experiment is done by numerical modelling for both NMOS and PMOS by using device simulator TCAD Sentaurus. Based on the model, we conduct an investigation on Short Channel Effects (SCEs) like drain induced barrier lowering (DIBL), threshold voltage (Vth) shifting between two devices. Two types (Single and Double gate) enhancement type MOSFET has been studied for nanoscale CMOS digital application.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114202533","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045322
J. Mathew, R. Vijayakumar
This paper mainly focuses in identifying the limitations of the k means algorithm and to propose the parallelization of the k-means using firefly based clustering method. The new parallel architecture can handle large number of clusters. Firefly algorithm to find initial optimal cluster centroid and then k-means algorithm with optimized centroid to refined them and improve clustering accuracy. The final convergence issue is also addressed and solved to a great extent. Finally modified algorithm is compared with parallel k means is demonstrated with experiments and it has been found that the performance of modified algorithm is better than the existing algorithm. Four typical benchmark data sets from the UCI machine learning repository are used to demonstrate the results of the techniques. To achieve this we can use fork/join method in java programming. It is the most effective design method for achieve good parallel performance.
{"title":"Scalable parallel clustering approach for large data using parallel K means and firefly algorithms","authors":"J. Mathew, R. Vijayakumar","doi":"10.1109/ICHPCA.2014.7045322","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045322","url":null,"abstract":"This paper mainly focuses in identifying the limitations of the k means algorithm and to propose the parallelization of the k-means using firefly based clustering method. The new parallel architecture can handle large number of clusters. Firefly algorithm to find initial optimal cluster centroid and then k-means algorithm with optimized centroid to refined them and improve clustering accuracy. The final convergence issue is also addressed and solved to a great extent. Finally modified algorithm is compared with parallel k means is demonstrated with experiments and it has been found that the performance of modified algorithm is better than the existing algorithm. Four typical benchmark data sets from the UCI machine learning repository are used to demonstrate the results of the techniques. To achieve this we can use fork/join method in java programming. It is the most effective design method for achieve good parallel performance.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122371708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045325
Rakesh Ranjan, R. Misra
The control and prevention of epidemics like influenza is a matter of high concern for the public health and decision support to the policy makers of public health. Epidemic disease propagation in a social contact network for the spread of contagion in a large real social contact having millions of individuals often becomes challenging for high performance computing. In this paper we present a novel MapReduce algorithm to detect the boundary of infectious nodes in social contact network. We used smart phone based personnel and community sensing for collecting the individual's connection, communication and interaction to others with respect to time. Using this extracted smart phone data; user's health status is predicted.
{"title":"Epidemic disease propagation detection algorithm using MapReduce for realistic social contact networks","authors":"Rakesh Ranjan, R. Misra","doi":"10.1109/ICHPCA.2014.7045325","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045325","url":null,"abstract":"The control and prevention of epidemics like influenza is a matter of high concern for the public health and decision support to the policy makers of public health. Epidemic disease propagation in a social contact network for the spread of contagion in a large real social contact having millions of individuals often becomes challenging for high performance computing. In this paper we present a novel MapReduce algorithm to detect the boundary of infectious nodes in social contact network. We used smart phone based personnel and community sensing for collecting the individual's connection, communication and interaction to others with respect to time. Using this extracted smart phone data; user's health status is predicted.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122022037","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045295
Xianhua Ding, Xiaomin Wang, Yuqing Du, Jianping Li, Guoying Liu
Dell Advanced Infrastructure Manager (AIM) is a software that separates the physical elements in the data center from how to control them. It is convenient to share a pool of backup servers that are ready to take over any other failed server's role. In this paper we integrate Matlab Distributed Computing Server (MDCS) with AIM to build a reliable, efficient platform for scientific computations. The motivation to use AIM as the resource management center for MDCS is to provide a fault-tolerant computation platform. We test the speedup rate of virtual worker cluster and compare with physical worker cluster using physical client and virtual client. Our experiment show that the performance of virtual worker cluster is about 82% of the physical worker cluster's performance.
{"title":"A reliable platform using matlab distributed computing server integrated with AIM","authors":"Xianhua Ding, Xiaomin Wang, Yuqing Du, Jianping Li, Guoying Liu","doi":"10.1109/ICHPCA.2014.7045295","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045295","url":null,"abstract":"Dell Advanced Infrastructure Manager (AIM) is a software that separates the physical elements in the data center from how to control them. It is convenient to share a pool of backup servers that are ready to take over any other failed server's role. In this paper we integrate Matlab Distributed Computing Server (MDCS) with AIM to build a reliable, efficient platform for scientific computations. The motivation to use AIM as the resource management center for MDCS is to provide a fault-tolerant computation platform. We test the speedup rate of virtual worker cluster and compare with physical worker cluster using physical client and virtual client. Our experiment show that the performance of virtual worker cluster is about 82% of the physical worker cluster's performance.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128169698","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045364
A. Agrawal, Sadhana Singh, Malay Tripathi, L. S. Maurya
As the complexity of software projects in today's environment is increasing, it's necessary to work more in teams. The team may be two member team or n- member team. The collaborative and co-operative effort from team produced a better result. Most recent software develop model “AGILE- a group of methods” also supports the team work in the form of pair programming. Pair programming is the method related to the efforts of two individuals, driver and navigator or we can say walker and the guide. Pair programming is used for getting more promising results, but sometimes due to the personality traits of individual team member it may become disastrous. This research paper focuses on this problem and tests whether personality test traits of any individual affect the final output or not.
{"title":"A study on role of personality traits for pair programming team","authors":"A. Agrawal, Sadhana Singh, Malay Tripathi, L. S. Maurya","doi":"10.1109/ICHPCA.2014.7045364","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045364","url":null,"abstract":"As the complexity of software projects in today's environment is increasing, it's necessary to work more in teams. The team may be two member team or n- member team. The collaborative and co-operative effort from team produced a better result. Most recent software develop model “AGILE- a group of methods” also supports the team work in the form of pair programming. Pair programming is the method related to the efforts of two individuals, driver and navigator or we can say walker and the guide. Pair programming is used for getting more promising results, but sometimes due to the personality traits of individual team member it may become disastrous. This research paper focuses on this problem and tests whether personality test traits of any individual affect the final output or not.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129241660","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045358
Soundar Thiagarajan, Kaliuday Balleda
Heart rate measurement plays a major role in diagnosis of heart diseases. There are many existing contact based methods which are in practice. These methods tend to be more expensive and unreachable in emergency scenarios. This paper introduces a novel non-contact method called HiBeat. HiBeat calculates heart rate using facial video of the subject. Proposed method does face recognition, traces the color channels and normalizes them. After normalization HiBeat detrends the color channels and then converts it into independent signals by applying independent component analysis. These signals will be converted into frequency domain and band limited to 1-4Hz. Peak value in band limited frequency among all three channels is considered as source for blood pulse per minute unit conversion. HiBeat is thoroughly tested for its accuracy in comparison with OMRON which is a contact based standard tool for heart rate measurement. It is observed that HiBeat results are accurate. HiBeat achieves 81percent accuracy in comparison with existing non-contact methods. HiBeat is parallelized for multicore architecture and it achieves 2x performance compared to its serial implementation.
{"title":"HiBeat: A novel highly accurate implementation of cardiac pulse measurement on a multicore architecture","authors":"Soundar Thiagarajan, Kaliuday Balleda","doi":"10.1109/ICHPCA.2014.7045358","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045358","url":null,"abstract":"Heart rate measurement plays a major role in diagnosis of heart diseases. There are many existing contact based methods which are in practice. These methods tend to be more expensive and unreachable in emergency scenarios. This paper introduces a novel non-contact method called HiBeat. HiBeat calculates heart rate using facial video of the subject. Proposed method does face recognition, traces the color channels and normalizes them. After normalization HiBeat detrends the color channels and then converts it into independent signals by applying independent component analysis. These signals will be converted into frequency domain and band limited to 1-4Hz. Peak value in band limited frequency among all three channels is considered as source for blood pulse per minute unit conversion. HiBeat is thoroughly tested for its accuracy in comparison with OMRON which is a contact based standard tool for heart rate measurement. It is observed that HiBeat results are accurate. HiBeat achieves 81percent accuracy in comparison with existing non-contact methods. HiBeat is parallelized for multicore architecture and it achieves 2x performance compared to its serial implementation.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"381 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132084079","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045304
Satvik Sachdev, Aparna Nayak, Tribikram Pradhan
Visual Cryptography (VC) is a cryptographic technique that allows visual information such as textual images, handwritten notes etc to be encrypted in such a way that the decryption can be performed using the human visual system i.e. eyes. Here we propose an algorithm for data hiding in halftone images. This algorithm uses a morphological operation and ordered dithering, and is a modified version of DHCOD[1].In this paper we focus on improving the security and robustness of shares in VC and generating more meaningful shares with respect to basic cryptographic scheme.
{"title":"Data hiding in halftone images using mathematical morphology and conjugate ordered dithering","authors":"Satvik Sachdev, Aparna Nayak, Tribikram Pradhan","doi":"10.1109/ICHPCA.2014.7045304","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045304","url":null,"abstract":"Visual Cryptography (VC) is a cryptographic technique that allows visual information such as textual images, handwritten notes etc to be encrypted in such a way that the decryption can be performed using the human visual system i.e. eyes. Here we propose an algorithm for data hiding in halftone images. This algorithm uses a morphological operation and ordered dithering, and is a modified version of DHCOD[1].In this paper we focus on improving the security and robustness of shares in VC and generating more meaningful shares with respect to basic cryptographic scheme.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"215 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132423857","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045320
Amit Datta, M. De, Sanjoy Das
The algorithm proposed in this paper is describing in place generation of Hadamard coefficients of N points on Multi Mesh (MM) architecture having N2 processors based on position of each processor in MM. The algorithm provides the Hadamard transformation of an input vector of length N in O (log (√N) addition and O (√N) data movement time.
{"title":"Parallel hadamard transform in Multi Mesh network","authors":"Amit Datta, M. De, Sanjoy Das","doi":"10.1109/ICHPCA.2014.7045320","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045320","url":null,"abstract":"The algorithm proposed in this paper is describing in place generation of Hadamard coefficients of N points on Multi Mesh (MM) architecture having N2 processors based on position of each processor in MM. The algorithm provides the Hadamard transformation of an input vector of length N in O (log (√N) addition and O (√N) data movement time.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121412291","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045343
Tanmay Sen, S. Saha, Asif Ekbal, A. Laha
In the current paper, Bi-objective portfolio optimization problem has been tackled using multiobjective optimization framework. Three popular multiobjective optimization algorithms are used for solving this problem. These are: Archive Multi-objective Simulated Annealing (AMOSA) algorithm, Non-dominated Sorting Genetic algorithm II (NSGA-II) and Multi-objective Particle Swarm Optimization using Crowding distance (MOPSOCD). For each algorithm we trace the Pareto optimal front and compare the results by using four comparisons metrics, Spread, Spacing, Set Coverage and Maximum Spread. Comparative results show that NSGA-II performs the best as compared to the other two algorithms.
本文采用多目标优化框架来解决双目标投资组合优化问题。三种常用的多目标优化算法用于解决该问题。这些算法包括:存档多目标模拟退火(AMOSA)算法、非支配排序遗传算法II (NSGA-II)和基于拥挤距离的多目标粒子群优化(MOPSOCD)。对于每种算法，我们都跟踪了Pareto最优前沿，并通过使用四个比较指标(Spread, Spacing, Set Coverage和Maximum Spread)来比较结果。对比结果表明，与其他两种算法相比，NSGA-II算法的性能最好。
{"title":"Bi-objective portfolio optimization using Archive Multi-objective Simulated Annealing","authors":"Tanmay Sen, S. Saha, Asif Ekbal, A. Laha","doi":"10.1109/ICHPCA.2014.7045343","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045343","url":null,"abstract":"In the current paper, Bi-objective portfolio optimization problem has been tackled using multiobjective optimization framework. Three popular multiobjective optimization algorithms are used for solving this problem. These are: Archive Multi-objective Simulated Annealing (AMOSA) algorithm, Non-dominated Sorting Genetic algorithm II (NSGA-II) and Multi-objective Particle Swarm Optimization using Crowding distance (MOPSOCD). For each algorithm we trace the Pareto optimal front and compare the results by using four comparisons metrics, Spread, Spacing, Set Coverage and Maximum Spread. Comparative results show that NSGA-II performs the best as compared to the other two algorithms.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"6 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126640013","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2014-12-01DOI: 10.1109/ICHPCA.2014.7045315
P. Remya, B. Neelgar, R. Shibu
This thesis is an attempt to investigate on methods to develop built in self test method for performance measurement of a wideband (20MHz) software defined radio with frequency coverage from 50MHz to 2.4GHz. The overall quality of transmission and reception is dictated by various RF system and baseband specifications in wireless systems. Error Vector Magnitude (EVM) is a measure of the digital modulation quality of the wireless system under test which is very sensitive to much impairment in the transceiver.
{"title":"GNU radio based BIST for SDR performance measurement","authors":"P. Remya, B. Neelgar, R. Shibu","doi":"10.1109/ICHPCA.2014.7045315","DOIUrl":"https://doi.org/10.1109/ICHPCA.2014.7045315","url":null,"abstract":"This thesis is an attempt to investigate on methods to develop built in self test method for performance measurement of a wideband (20MHz) software defined radio with frequency coverage from 50MHz to 2.4GHz. The overall quality of transmission and reception is dictated by various RF system and baseband specifications in wireless systems. Error Vector Magnitude (EVM) is a measure of the digital modulation quality of the wireless system under test which is very sensitive to much impairment in the transceiver.","PeriodicalId":197528,"journal":{"name":"2014 International Conference on High Performance Computing and Applications (ICHPCA)","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133252009","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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