Pub Date : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621405
Shwetabh Srivastava, Pranay Kumar Srivastava
RPC (Remote Procedure Call) is one of the ways for creating distributed client-server based applications. Sun RPC (ONC RPC) is old yet still popular implementation of RPC on UNIX based systems. However Sun RPC implementation suffers from poor performance despite having high speed hardware. In this paper we have given brief about Sun RPC, performance analysis of Sun RPC library and different possible optimization technique that can be applied for enhancing its performance.
{"title":"Performance analysis of Sun RPC","authors":"Shwetabh Srivastava, Pranay Kumar Srivastava","doi":"10.1109/PARCOMPTECH.2013.6621405","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621405","url":null,"abstract":"RPC (Remote Procedure Call) is one of the ways for creating distributed client-server based applications. Sun RPC (ONC RPC) is old yet still popular implementation of RPC on UNIX based systems. However Sun RPC implementation suffers from poor performance despite having high speed hardware. In this paper we have given brief about Sun RPC, performance analysis of Sun RPC library and different possible optimization technique that can be applied for enhancing its performance.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116351399","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621401
P. R. Redapangu, K. Sahu
Three-dimensional simulations of buoyancy-driven flow of two immiscible liquids are performed using lattice Boltzmann method (LBM) implemented on a graphics processing unit (GPU). Graphics processing unit is a new paradigm for computing fluid flows and has become more popular in the recent years. It is a powerful and convenient to use. LBM, which is an excellent alternative technique for fluid flow simulation, when implemented on GPUs gives a very high computational speed-up. Our present GPU based LBM solver gives a speed-up 25 times corresponding CPU based code.
{"title":"Three-dimensional LBM simulations of buoyancy-driven flow using graphics processing units","authors":"P. R. Redapangu, K. Sahu","doi":"10.1109/PARCOMPTECH.2013.6621401","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621401","url":null,"abstract":"Three-dimensional simulations of buoyancy-driven flow of two immiscible liquids are performed using lattice Boltzmann method (LBM) implemented on a graphics processing unit (GPU). Graphics processing unit is a new paradigm for computing fluid flows and has become more popular in the recent years. It is a powerful and convenient to use. LBM, which is an excellent alternative technique for fluid flow simulation, when implemented on GPUs gives a very high computational speed-up. Our present GPU based LBM solver gives a speed-up 25 times corresponding CPU based code.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126167532","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621407
A. Tomar, Jahnavi Bodhankar, Pavan Kurariya, Pramod Anarase, Priyanka Jain, Anuradha Lele, H. Darbari, V. Bhavsar
The main objective of this paper is to introduce a high performance natural language processing (NLP) service to fulfill the needs of researchers and users in the area of natural language computing. We consider various NLP components developed at Applied Artificial Group of C-DAC Pune, and carry out parallelization on the GARUDA grid. We demonstrate that almost linear speedup is achieved with good efficiencies. With 32 processors, we have achieved a speedup of more than 19. This allows us to offer high performance scalable NLP Web services. Further, the GARUDA grid offers high availability.
{"title":"High performance natural language processing services on the GARUDA grid","authors":"A. Tomar, Jahnavi Bodhankar, Pavan Kurariya, Pramod Anarase, Priyanka Jain, Anuradha Lele, H. Darbari, V. Bhavsar","doi":"10.1109/PARCOMPTECH.2013.6621407","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621407","url":null,"abstract":"The main objective of this paper is to introduce a high performance natural language processing (NLP) service to fulfill the needs of researchers and users in the area of natural language computing. We consider various NLP components developed at Applied Artificial Group of C-DAC Pune, and carry out parallelization on the GARUDA grid. We demonstrate that almost linear speedup is achieved with good efficiencies. With 32 processors, we have achieved a speedup of more than 19. This allows us to offer high performance scalable NLP Web services. Further, the GARUDA grid offers high availability.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125813612","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621398
S. R. Reddy, J. Sebastian, S. M. Miyyadad, R. Banerjee, N. Sivadasan
We present parallelization of single and two phase flow CFD solvers on a graphics processing unit (GPU) platform. Numerical simulations are done for some standard benchmark test cases for both single and two phase flow solvers. The formulation is based on finite volume method with SMAC algorithm on regular cartesian and collocated grid. Volume of fluid method in used for tracking the interface in multiphase flow solver. Pressure poisson equation is the most time consuming part of the solvers and hence this part is imported on to GPU. Pressure Poisson equation is solved by the conventional Gauss siedel method. Present day modern graphics hardware has several hundred cores which can be effectively used by CFD solvers to parallelize the computation. The results are validated against the reference solutions of the teat cases. A comparison is done between CPU and GPU simulations to estimate the computational acceleration and accuracy obtained.
{"title":"Single and two phase flow CFD solvers using GPU","authors":"S. R. Reddy, J. Sebastian, S. M. Miyyadad, R. Banerjee, N. Sivadasan","doi":"10.1109/PARCOMPTECH.2013.6621398","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621398","url":null,"abstract":"We present parallelization of single and two phase flow CFD solvers on a graphics processing unit (GPU) platform. Numerical simulations are done for some standard benchmark test cases for both single and two phase flow solvers. The formulation is based on finite volume method with SMAC algorithm on regular cartesian and collocated grid. Volume of fluid method in used for tracking the interface in multiphase flow solver. Pressure poisson equation is the most time consuming part of the solvers and hence this part is imported on to GPU. Pressure Poisson equation is solved by the conventional Gauss siedel method. Present day modern graphics hardware has several hundred cores which can be effectively used by CFD solvers to parallelize the computation. The results are validated against the reference solutions of the teat cases. A comparison is done between CPU and GPU simulations to estimate the computational acceleration and accuracy obtained.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"82 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116063436","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621392
Ranajoy Malakar, N. Vydyanathan
Hadoop is a map-reduce based distributed processing framework, frequently used in the industry today, in areas of big data analysis, particularly text analysis. Graphics processing units (GPUs), on the other hand, are massively parallel platforms with attractive performance to price and power ratios, used extensively in the recent years for acceleration of data parallel computations. CUDA or Compute Unified Device Architecture is a C-based programming model proposed by NVIDIA for leveraging the parallel computing capabilities of the GPU for general purpose computations. This paper attempts to integrate CUDA acceleration into the Hadoop distributed processing framework to create a heterogeneous high performance image processing system. As Hadoop primarily is used for text analysis, this involves facilitating efficient image processing in Hadoop. Our experimental evaluations using a Adaboost based face detection algorithm indicate that CUDA-enabling a Hadoop cluster, even with low-end GPUs, can result in a 25% improvement in data processing throughput, indicating that an integration of these two technologies can help build scalable, high throughput, power and cost-efficient computing platforms.
{"title":"A CUDA-enabled Hadoop cluster for fast distributed image processing","authors":"Ranajoy Malakar, N. Vydyanathan","doi":"10.1109/PARCOMPTECH.2013.6621392","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621392","url":null,"abstract":"Hadoop is a map-reduce based distributed processing framework, frequently used in the industry today, in areas of big data analysis, particularly text analysis. Graphics processing units (GPUs), on the other hand, are massively parallel platforms with attractive performance to price and power ratios, used extensively in the recent years for acceleration of data parallel computations. CUDA or Compute Unified Device Architecture is a C-based programming model proposed by NVIDIA for leveraging the parallel computing capabilities of the GPU for general purpose computations. This paper attempts to integrate CUDA acceleration into the Hadoop distributed processing framework to create a heterogeneous high performance image processing system. As Hadoop primarily is used for text analysis, this involves facilitating efficient image processing in Hadoop. Our experimental evaluations using a Adaboost based face detection algorithm indicate that CUDA-enabling a Hadoop cluster, even with low-end GPUs, can result in a 25% improvement in data processing throughput, indicating that an integration of these two technologies can help build scalable, high throughput, power and cost-efficient computing platforms.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"33 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126404248","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621395
B. Arunachalam, B. Kalasagar, Vineeth Simon Arackal, Prahlada Rao B.B.
Open Source Job Submission Portal (OSJSP) is for uniform access to Grid resources for the benefit of grid community. Users can submit jobs to Grid through the web-based Graphical User Interface. The ultimate aim of OSJSP is to provide portlet based portal for the researchers, students and academia to take care of their job and resource management issues in an efficient way. This portal adheres to basic grid system architecture by integrating gridsphere portal framework, Globus toolkit (Grid middleware), Gridway meta-scheduler and ingeniously developed portlets. These portlets are developed as per JSR 168 standard. OSJSP supports user authentication, authorization and job submission using x509 credentials. In this paper, we describe the importance of OSJSP, its implementation, features along with a related work.
{"title":"Open Source Job Submission Portal for Grid","authors":"B. Arunachalam, B. Kalasagar, Vineeth Simon Arackal, Prahlada Rao B.B.","doi":"10.1109/PARCOMPTECH.2013.6621395","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621395","url":null,"abstract":"Open Source Job Submission Portal (OSJSP) is for uniform access to Grid resources for the benefit of grid community. Users can submit jobs to Grid through the web-based Graphical User Interface. The ultimate aim of OSJSP is to provide portlet based portal for the researchers, students and academia to take care of their job and resource management issues in an efficient way. This portal adheres to basic grid system architecture by integrating gridsphere portal framework, Globus toolkit (Grid middleware), Gridway meta-scheduler and ingeniously developed portlets. These portlets are developed as per JSR 168 standard. OSJSP supports user authentication, authorization and job submission using x509 credentials. In this paper, we describe the importance of OSJSP, its implementation, features along with a related work.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"48 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131832135","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621399
A. Tripathy, J. Adinarayana, S. Merchant, U. Desai, S. Ninomiya, M. Hirafuji, T. Kiura
Recent technological developments allowed envisioning sensor devices with distributed ambient sensory network, which could be a potential technology for monitoring various natural phenomena (weather parameters, soil moisture, etc.) at micro level. As days more and more agricultural data are virtually being harvested along with the crops and are being collected/stored in databases, the same data can be used in productive decision making if appropriate data mining techniques are developed/applied. An experiment was conducted with four consecutive (Kharif and Rabi) agricultural seasons in a semi-arid region of India to understand the crop-weather-environment-pest/diseases relations using wireless sensory and field-level surveillance data on closely related and interdependent pest/disease dynamics of groundnut crop. Association rule mining and multivariate regression mining techniques/algorithms were designed/ developed/tailor-made to turn the data into useful information/ knowledge/relations/trends to know crop-weather-environment-pest/disease continuum. These findings have been used for development of prediction models (cumulative and non-cumulative) followed by a web based pest/disease decision support system, which will help the decision makers to take viable ameliorative measures.
{"title":"Data mining and wireless sensor network for groundnut pest/disease precision protection","authors":"A. Tripathy, J. Adinarayana, S. Merchant, U. Desai, S. Ninomiya, M. Hirafuji, T. Kiura","doi":"10.1109/PARCOMPTECH.2013.6621399","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621399","url":null,"abstract":"Recent technological developments allowed envisioning sensor devices with distributed ambient sensory network, which could be a potential technology for monitoring various natural phenomena (weather parameters, soil moisture, etc.) at micro level. As days more and more agricultural data are virtually being harvested along with the crops and are being collected/stored in databases, the same data can be used in productive decision making if appropriate data mining techniques are developed/applied. An experiment was conducted with four consecutive (Kharif and Rabi) agricultural seasons in a semi-arid region of India to understand the crop-weather-environment-pest/diseases relations using wireless sensory and field-level surveillance data on closely related and interdependent pest/disease dynamics of groundnut crop. Association rule mining and multivariate regression mining techniques/algorithms were designed/ developed/tailor-made to turn the data into useful information/ knowledge/relations/trends to know crop-weather-environment-pest/disease continuum. These findings have been used for development of prediction models (cumulative and non-cumulative) followed by a web based pest/disease decision support system, which will help the decision makers to take viable ameliorative measures.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131203877","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621406
S. Hore, S. Das, S. Banerjee, S. Mukherjee
A Monte Carlo (MC) simulation methodology using high performance computing (HPC) has been proposed to characterize grain growth kinetics and recrystallisation phenomena during hot rolling of C-Mn and TRIP steels. The simulation framework comprises of mesoscale modelling of evolution of grain growth and microstructure incorporating the system energetics of grain boundary energy and stored energy which are essentially the driving force for the evolution process. An in-house MC computer code has been developed and implemented in the GARUDA grid. This facilitated achieving faster convergence of the MC algorithm for a given lattice structure. The simulated grain growth and microstructure evolution have been successfully validated with the published data. It is inferred that the MC simulation in conjunction with HPC grid capability can be a powerful tool to simulate material behaviour at mesoscopic scale during thermo-mechanical processing of materials.
{"title":"Monte Carlo simulation of microstructure evolution during thermo-mechanical rolling of steel using grid computing technology","authors":"S. Hore, S. Das, S. Banerjee, S. Mukherjee","doi":"10.1109/PARCOMPTECH.2013.6621406","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621406","url":null,"abstract":"A Monte Carlo (MC) simulation methodology using high performance computing (HPC) has been proposed to characterize grain growth kinetics and recrystallisation phenomena during hot rolling of C-Mn and TRIP steels. The simulation framework comprises of mesoscale modelling of evolution of grain growth and microstructure incorporating the system energetics of grain boundary energy and stored energy which are essentially the driving force for the evolution process. An in-house MC computer code has been developed and implemented in the GARUDA grid. This facilitated achieving faster convergence of the MC algorithm for a given lattice structure. The simulated grain growth and microstructure evolution have been successfully validated with the published data. It is inferred that the MC simulation in conjunction with HPC grid capability can be a powerful tool to simulate material behaviour at mesoscopic scale during thermo-mechanical processing of materials.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"609 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123202720","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621391
A. Tomar, Jahnavi Bodhankar, Pavan Kurariya, Pramod Anarase, Priyanka Jain, Anuradha Lele, H. Darbari, V. Bhavsar
In this paper we consider a machine translation (MT) system based on the tree adjoining grammar (TAG) formalism. We have successfully carried out sentence level parallelization and its parallel implementations on a multicore machine with varying number of cores and a computing cluster with multicore nodes. Since our code is in Java, we use MPJ Express for parallel implementations. We have carried out experiments with these parallel implementations and their performance is analysed.
{"title":"Parallel implementation of machine translation using MPJ Express","authors":"A. Tomar, Jahnavi Bodhankar, Pavan Kurariya, Pramod Anarase, Priyanka Jain, Anuradha Lele, H. Darbari, V. Bhavsar","doi":"10.1109/PARCOMPTECH.2013.6621391","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621391","url":null,"abstract":"In this paper we consider a machine translation (MT) system based on the tree adjoining grammar (TAG) formalism. We have successfully carried out sentence level parallelization and its parallel implementations on a multicore machine with varying number of cores and a computing cluster with multicore nodes. Since our code is in Java, we use MPJ Express for parallel implementations. We have carried out experiments with these parallel implementations and their performance is analysed.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"155 8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128710362","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 : 2013-10-08DOI: 10.1109/PARCOMPTECH.2013.6621403
V. S. K. Nagireddi, Shakti Mishra
Cloud computing is an emerging technology which provides computing infrastructure, platform (Operating System, development/testing), software applications and storage as a service on a pay-per-use basis. Although there exists enormous number of services as well as Cloud Service Providers (CSP), identifying the appropriate service as per user requirement has not been addressed yet. The problem has been addressed in the proposed work in two modules. The first module describes about the construction of ontology based on relationship between cloud services and their characteristics. In the second module, a generic based search engine has been developed to search the cloud services for user's requirement. It uses cloud ontology to process the query and fetch the results. The cloud services are ranked on the basis of the cloud service characteristics. The proposed model has been implemented using protégé tool for constructing ontology and packages (owlapi, sparqldl, Jena) for constructing search engine.
{"title":"A naive approach for cloud service discovery mechanism using ontology","authors":"V. S. K. Nagireddi, Shakti Mishra","doi":"10.1109/PARCOMPTECH.2013.6621403","DOIUrl":"https://doi.org/10.1109/PARCOMPTECH.2013.6621403","url":null,"abstract":"Cloud computing is an emerging technology which provides computing infrastructure, platform (Operating System, development/testing), software applications and storage as a service on a pay-per-use basis. Although there exists enormous number of services as well as Cloud Service Providers (CSP), identifying the appropriate service as per user requirement has not been addressed yet. The problem has been addressed in the proposed work in two modules. The first module describes about the construction of ontology based on relationship between cloud services and their characteristics. In the second module, a generic based search engine has been developed to search the cloud services for user's requirement. It uses cloud ontology to process the query and fetch the results. The cloud services are ranked on the basis of the cloud service characteristics. The proposed model has been implemented using protégé tool for constructing ontology and packages (owlapi, sparqldl, Jena) for constructing search engine.","PeriodicalId":344858,"journal":{"name":"2013 National Conference on Parallel Computing Technologies (PARCOMPTECH)","volume":"173 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-10-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122872073","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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