Pub Date : 2015-07-20DOI: 10.1109/HPCSim.2015.7237022
Jens Lang, G. Rünger, P. Stocker
Autotuning is an established method for adapting the execution of an application to the underlying hardware for minimising the execution time. This article investigates whether autotuning is also suitable for minimising the energy consumption of an application. The investigation is done with the linear algebra library ATLAS. Adaptations for the ATLAS package which enable energy autotuning are proposed. Different tuning parameters are investigated for whether they show a different behaviour when ATLAS is tuned for energy consumption instead for execution time. The results suggest that some tuning parameters have to be set differently when ATLAS is supposed to work with a minimum energy consumption than with a minimum execution time. The results further indicate that tuning the complete ATLAS package for energy consumption leads to a more energy-efficient execution than tuning it for execution time.
{"title":"Towards energy-efficient linear algebra with an ATLAS library tuned for energy consumption","authors":"Jens Lang, G. Rünger, P. Stocker","doi":"10.1109/HPCSim.2015.7237022","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237022","url":null,"abstract":"Autotuning is an established method for adapting the execution of an application to the underlying hardware for minimising the execution time. This article investigates whether autotuning is also suitable for minimising the energy consumption of an application. The investigation is done with the linear algebra library ATLAS. Adaptations for the ATLAS package which enable energy autotuning are proposed. Different tuning parameters are investigated for whether they show a different behaviour when ATLAS is tuned for energy consumption instead for execution time. The results suggest that some tuning parameters have to be set differently when ATLAS is supposed to work with a minimum energy consumption than with a minimum execution time. The results further indicate that tuning the complete ATLAS package for energy consumption leads to a more energy-efficient execution than tuning it for execution time.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"9 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115931200","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237084
Elias Kouskoumvekakis, D. Soudris, E. Manolakos
Stochastic simulation of large-scale biochemical reaction networks is becoming essential for Systems Biology. It enables the in-silico investigation of complex biological system dynamics under different conditions and intervention strategies, while also taking into account the inherent “biological noise” especially present in the low species count regime. It is however a great computational challenge since in practice we need to execute many repetitions of a complex simulation model to assess the average and extreme cases behavior of the dynamical system it represents. The problem's work scales quickly, with the number of repetitions required and the number of reactions in the bio-model. The worst case scenario s when there is a need to run thousands of repetitions of a complex model with thousands of reactions. We have developed a stochastic simulation software framework for many- and multi-core CPUs. It is evaluated using Intel's experimental many-cores Single-chip Cloud Computer (SCC) CPU and the latest generation consumer grade Core i7 multi-core Intel CPU, when running Gillespie's First Reaction Method exact stochastic simulation algorithm. It is shown that emerging many-core NoC processors can provide scalable performance achieving linear speedup as simulation work scales in both dimensions.
{"title":"Many-core CPUs can deliver scalable performance to stochastic simulations of large-scale biochemical reaction networks","authors":"Elias Kouskoumvekakis, D. Soudris, E. Manolakos","doi":"10.1109/HPCSim.2015.7237084","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237084","url":null,"abstract":"Stochastic simulation of large-scale biochemical reaction networks is becoming essential for Systems Biology. It enables the in-silico investigation of complex biological system dynamics under different conditions and intervention strategies, while also taking into account the inherent “biological noise” especially present in the low species count regime. It is however a great computational challenge since in practice we need to execute many repetitions of a complex simulation model to assess the average and extreme cases behavior of the dynamical system it represents. The problem's work scales quickly, with the number of repetitions required and the number of reactions in the bio-model. The worst case scenario s when there is a need to run thousands of repetitions of a complex model with thousands of reactions. We have developed a stochastic simulation software framework for many- and multi-core CPUs. It is evaluated using Intel's experimental many-cores Single-chip Cloud Computer (SCC) CPU and the latest generation consumer grade Core i7 multi-core Intel CPU, when running Gillespie's First Reaction Method exact stochastic simulation algorithm. It is shown that emerging many-core NoC processors can provide scalable performance achieving linear speedup as simulation work scales in both dimensions.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134103691","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237053
P. Mayorga, D. Ibarra, V. Zeljkovic, C. Druzgalski
This paper presents integrated Hidden Markov and Gaussian Mixture Models (HMM-GMM) to classify lung sounds (LS) and heart sounds (HS) characteristics. In order to optimize the models' size, several methodologies encompassing dendrograms, silhouettes and the Bayesian Information Criterion (BIC) were applied. The experiments were carried out extracting features from the LS and HS with MFCC (Mel-Frequency Cepstral Coefficients) vectors and Quantile vectors, specifically Quartiles. The merged HMM-GMM architecture for the signals using Quartiles, overall offered consistent classification results. In both types of vectors, a high degree of classification efficiency was obtained reaching up to 96% for the studied sets of signals. For MFCC the classification results were not conclusive. An assessment of the number of clusters using dendrograms, silhouettes, and BIC linked with the models' size. Consequently this allows to enhance efficiency of merged HMM-GMM models in diagnostic classification of cardiopulmonary acoustic signals.
{"title":"Quartiles and Mel Frequency Cepstral Coefficients vectors in Hidden Markov-Gaussian Mixture Models classification of merged heart sounds and lung sounds signals","authors":"P. Mayorga, D. Ibarra, V. Zeljkovic, C. Druzgalski","doi":"10.1109/HPCSim.2015.7237053","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237053","url":null,"abstract":"This paper presents integrated Hidden Markov and Gaussian Mixture Models (HMM-GMM) to classify lung sounds (LS) and heart sounds (HS) characteristics. In order to optimize the models' size, several methodologies encompassing dendrograms, silhouettes and the Bayesian Information Criterion (BIC) were applied. The experiments were carried out extracting features from the LS and HS with MFCC (Mel-Frequency Cepstral Coefficients) vectors and Quantile vectors, specifically Quartiles. The merged HMM-GMM architecture for the signals using Quartiles, overall offered consistent classification results. In both types of vectors, a high degree of classification efficiency was obtained reaching up to 96% for the studied sets of signals. For MFCC the classification results were not conclusive. An assessment of the number of clusters using dendrograms, silhouettes, and BIC linked with the models' size. Consequently this allows to enhance efficiency of merged HMM-GMM models in diagnostic classification of cardiopulmonary acoustic signals.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131619531","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237040
Michael Darling, G. Heileman, Gilad Gressel, Aravind Ashok, P. Poornachandran
Given the continuous growth of malicious activities on the internet, there is a need for intelligent systems to identify malicious web pages. It has been shown that URL analysis is an effective tool for detecting phishing, malware, and other attacks. Previous studies have performed URL classification using a combination of lexical features, network traffic, hosting information, and other strategies. These approaches require time-intensive lookups which introduce significant delay in real-time systems. In this paper, we describe a lightweight approach for classifying malicious web pages using URL lexical analysis alone. Our goal is to explore the upper-bound of the classification accuracy of a purely lexical approach. We also aim to develop a scalable approach which could be used in a real-time system. We develop a classification system based on lexical analysis of URLs. It correctly classifies URLs of malicious web pages with 99.1% accuracy, a 0.4% false positive rate, an F1-Score of 98.7, and 0.62 milliseconds on average. Our method also outperforms similar approaches when classifying out-of-sample data.
{"title":"A lexical approach for classifying malicious URLs","authors":"Michael Darling, G. Heileman, Gilad Gressel, Aravind Ashok, P. Poornachandran","doi":"10.1109/HPCSim.2015.7237040","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237040","url":null,"abstract":"Given the continuous growth of malicious activities on the internet, there is a need for intelligent systems to identify malicious web pages. It has been shown that URL analysis is an effective tool for detecting phishing, malware, and other attacks. Previous studies have performed URL classification using a combination of lexical features, network traffic, hosting information, and other strategies. These approaches require time-intensive lookups which introduce significant delay in real-time systems. In this paper, we describe a lightweight approach for classifying malicious web pages using URL lexical analysis alone. Our goal is to explore the upper-bound of the classification accuracy of a purely lexical approach. We also aim to develop a scalable approach which could be used in a real-time system. We develop a classification system based on lexical analysis of URLs. It correctly classifies URLs of malicious web pages with 99.1% accuracy, a 0.4% false positive rate, an F1-Score of 98.7, and 0.62 milliseconds on average. Our method also outperforms similar approaches when classifying out-of-sample data.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115188501","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237114
Bas Stringer, Maurits J. J. Dijkstra, K. Feenstra, Sanne Abeln, J. Heringa
The design of solutions to current societal challenges in human health, healthcare and nutrition, and to the sustainable production of food, feed and energy, requires academic innovations and industrial activity based on life science R&D in its broadest sense. The diversity of on-going programs shows that public-private collaboration is increasing in each of these sectors. A few examples in The Netherlands alone include the Dutch Techcenter for Life Sciences (DTL), CTMM-TraIT (TransMart, Open Clinica), NFU Data 4 Lifesciences initiative, Onco-XL, Parelsnoer, Centre for Personalized Cancer Treatment (CPCT) and Philips' Health-Suite Digital Platform in the Life Science & Health sector; Breed4Food and TIFN in Agri&Food; Virtual Lab for Plant Breeding, Seed Valley and “Tuinbouw Digitaal” in Horticulture; and BeBasic in Biobased Economy.style the text.
设计解决当前人类健康、医疗保健和营养方面的社会挑战，以及食品、饲料和能源的可持续生产，需要基于最广泛意义上的生命科学研发的学术创新和工业活动。正在进行的项目的多样性表明，这些部门的公私合作正在增加。仅在荷兰就有几个例子，包括荷兰生命科学技术中心(DTL)、CTMM-TraIT (TransMart、Open Clinica)、NFU Data 4生命科学倡议、Onco-XL、Parelsnoer、个性化癌症治疗中心(CPCT)和飞利浦在生命科学与健康领域的Health- suite数字平台;食品育种与农业食品中的TIFN植物育种虚拟实验室、种子谷与园艺“双谷数字”以及生物经济领域的BeBasic。设置文本样式。
{"title":"Explaining disease using big data: How valid is your pathway?","authors":"Bas Stringer, Maurits J. J. Dijkstra, K. Feenstra, Sanne Abeln, J. Heringa","doi":"10.1109/HPCSim.2015.7237114","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237114","url":null,"abstract":"The design of solutions to current societal challenges in human health, healthcare and nutrition, and to the sustainable production of food, feed and energy, requires academic innovations and industrial activity based on life science R&D in its broadest sense. The diversity of on-going programs shows that public-private collaboration is increasing in each of these sectors. A few examples in The Netherlands alone include the Dutch Techcenter for Life Sciences (DTL), CTMM-TraIT (TransMart, Open Clinica), NFU Data 4 Lifesciences initiative, Onco-XL, Parelsnoer, Centre for Personalized Cancer Treatment (CPCT) and Philips' Health-Suite Digital Platform in the Life Science & Health sector; Breed4Food and TIFN in Agri&Food; Virtual Lab for Plant Breeding, Seed Valley and “Tuinbouw Digitaal” in Horticulture; and BeBasic in Biobased Economy.style the text.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"51 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115989057","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237037
P. Yébenes, P. García, F. Quiles, J. Escudero-Sahuquillo
HPC systems are growing in number of components which have to be interconnected in an efficient way. For that reason, network design has become a key issue in the development of these systems, especially when they are made of thousands of elements. In order to maximize the performance achieved by the network with an affordable cost, new network topologies have been proposed in the last years. Among them, one of the most popular is the dragonfly topology which benefits from high radix switches. As it is not affordable to test these topologies in large real systems, simulation is widely used. In that sense, simulation frameworks are used for avoiding problems and costs derived from developing a simulator from scratch, as well as easing the design of new models. In that sense, OMNeT++ is one of the most prominent simulation frameworks, deeply accepted in modeling large networks. This paper focuses on the modeling of fully-connected dragonfly topologies and its implementation in generic HPC-system simulators. First, we explain in detail the modeling of the dragonfly interconnection pattern. Next, we also describe the modeling of the minimal-path routing algorithm which fits the proposed pattern, as well as the mechanism required for avoiding deadlocks. Besides, we describe the basics of the implementation of the proposed model in an OMNeT++-based simulator. Finally, by means of a set of experiments carried out under several dragonfly configurations, we show performance results obtained from the simulator that implements our dragonfly model, and we compare them with results shown in other papers for validation purposes. Although this evaluation has been made using an OMNeT++-based simulator, the modeled interconnection pattern and routing algorithm can be adapted to any simulation tool.
{"title":"Straightforward modeling of fully-connected dragonfly topologies in HPC-system simulators","authors":"P. Yébenes, P. García, F. Quiles, J. Escudero-Sahuquillo","doi":"10.1109/HPCSim.2015.7237037","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237037","url":null,"abstract":"HPC systems are growing in number of components which have to be interconnected in an efficient way. For that reason, network design has become a key issue in the development of these systems, especially when they are made of thousands of elements. In order to maximize the performance achieved by the network with an affordable cost, new network topologies have been proposed in the last years. Among them, one of the most popular is the dragonfly topology which benefits from high radix switches. As it is not affordable to test these topologies in large real systems, simulation is widely used. In that sense, simulation frameworks are used for avoiding problems and costs derived from developing a simulator from scratch, as well as easing the design of new models. In that sense, OMNeT++ is one of the most prominent simulation frameworks, deeply accepted in modeling large networks. This paper focuses on the modeling of fully-connected dragonfly topologies and its implementation in generic HPC-system simulators. First, we explain in detail the modeling of the dragonfly interconnection pattern. Next, we also describe the modeling of the minimal-path routing algorithm which fits the proposed pattern, as well as the mechanism required for avoiding deadlocks. Besides, we describe the basics of the implementation of the proposed model in an OMNeT++-based simulator. Finally, by means of a set of experiments carried out under several dragonfly configurations, we show performance results obtained from the simulator that implements our dragonfly model, and we compare them with results shown in other papers for validation purposes. Although this evaluation has been made using an OMNeT++-based simulator, the modeled interconnection pattern and routing algorithm can be adapted to any simulation tool.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121964657","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237038
F. Candel, S. Petit, J. Sahuquillo, J. Duato
Nowadays, research on GPU processor architecture is extraordinarily active since these architectures offer much more performance per watt than CPU architectures. This is the main reason why massive deployment of GPU multiprocessors is considered one of the most feasible solutions to attain exascale computing capabilities. In this context, ongoing GPU architecture research is required to improve GPU programmability as well as to integrate CPU and GPU cores in the same die. One of the most important research topics in current GPUs, is the GPU memory hierarchy, since its design goals are very different from those of conventional CPU memory hierarchies. To explore novel designs to better support General Purpose computing in GPUs (GPGPU computing) as well as to improve the performance of GPU and CPU/GPU systems, researchers often require advanced microarchitectural simulators with detailed models of the memory subsystem. Nevertheless, due to fast speed at which current GPU architectures evolve, simulation accuracy of existing state-of-the-art simulators suffers. This paper focuses on accurately modeling the GPU memory subsystem. We identified three main aspects that should be modeled with more accuracy: i) miss status holding registers, ii) coalescing vector memory requests, and iii) non-blocking GPU stores. In this sense, we extend the Multi2Sim heterogeneous CPU/GPU processor simulator to model these aspects with enough accuracy. Experimental results show that if these aspects are not considered in the simulation framework, performance deviations can rise in some applications up to 70%, 75%, and 60%, respectively.
{"title":"Accurately modeling the GPU memory subsystem","authors":"F. Candel, S. Petit, J. Sahuquillo, J. Duato","doi":"10.1109/HPCSim.2015.7237038","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237038","url":null,"abstract":"Nowadays, research on GPU processor architecture is extraordinarily active since these architectures offer much more performance per watt than CPU architectures. This is the main reason why massive deployment of GPU multiprocessors is considered one of the most feasible solutions to attain exascale computing capabilities. In this context, ongoing GPU architecture research is required to improve GPU programmability as well as to integrate CPU and GPU cores in the same die. One of the most important research topics in current GPUs, is the GPU memory hierarchy, since its design goals are very different from those of conventional CPU memory hierarchies. To explore novel designs to better support General Purpose computing in GPUs (GPGPU computing) as well as to improve the performance of GPU and CPU/GPU systems, researchers often require advanced microarchitectural simulators with detailed models of the memory subsystem. Nevertheless, due to fast speed at which current GPU architectures evolve, simulation accuracy of existing state-of-the-art simulators suffers. This paper focuses on accurately modeling the GPU memory subsystem. We identified three main aspects that should be modeled with more accuracy: i) miss status holding registers, ii) coalescing vector memory requests, and iii) non-blocking GPU stores. In this sense, we extend the Multi2Sim heterogeneous CPU/GPU processor simulator to model these aspects with enough accuracy. Experimental results show that if these aspects are not considered in the simulation framework, performance deviations can rise in some applications up to 70%, 75%, and 60%, respectively.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"12 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124047728","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237025
Andrea Borghesi, C. Conficoni, M. Lombardi, Andrea Bartolini
Supercomputers machines, HPC systems in general, embed sophisticated and advanced cooling circuits to remove heat and ensuring the required peak performance. Unfortunately removing heat, by means of cold water or air, costs additional power which decreases the overall supercomputer energy efficiency. Free-cooling uses ambient air instead than chiller to cool down warm air or liquid temperature. The amount of heat which can be removed for-free depends on ambient conditions such as temperature and humidity. Power capping can be used to reduce the supercomputer power dissipation to maximize the cooling efficiency. In this paper we present a power capping approach based on Constraint Programming which enables to estimate at every scheduling interval the power consumption of a given job schedule and to select among all possible job schedules the one which maximizes the supercomputer efficiency.
{"title":"MS3: A Mediterranean-stile job scheduler for supercomputers - do less when it's too hot!","authors":"Andrea Borghesi, C. Conficoni, M. Lombardi, Andrea Bartolini","doi":"10.1109/HPCSim.2015.7237025","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237025","url":null,"abstract":"Supercomputers machines, HPC systems in general, embed sophisticated and advanced cooling circuits to remove heat and ensuring the required peak performance. Unfortunately removing heat, by means of cold water or air, costs additional power which decreases the overall supercomputer energy efficiency. Free-cooling uses ambient air instead than chiller to cool down warm air or liquid temperature. The amount of heat which can be removed for-free depends on ambient conditions such as temperature and humidity. Power capping can be used to reduce the supercomputer power dissipation to maximize the cooling efficiency. In this paper we present a power capping approach based on Constraint Programming which enables to estimate at every scheduling interval the power consumption of a given job schedule and to select among all possible job schedules the one which maximizes the supercomputer efficiency.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"127 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124775036","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237090
K. Bertels
Moore's law is pushing the technology to the scale where quantum phenonema, such as quantum tunneling, can no longer be ignored. Where in conventional CMOS one tries to avoid unwanted quantum behaviour, quantum computing actually embraces these phenomena for computational purposes. The famous physicist Richard Feyman was the first to describe the idea of using superposition and entanglement as a way to model and simulate quantum phenomena.
{"title":"Quantum computing: How far away is it?","authors":"K. Bertels","doi":"10.1109/HPCSim.2015.7237090","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237090","url":null,"abstract":"Moore's law is pushing the technology to the scale where quantum phenonema, such as quantum tunneling, can no longer be ignored. Where in conventional CMOS one tries to avoid unwanted quantum behaviour, quantum computing actually embraces these phenomena for computational purposes. The famous physicist Richard Feyman was the first to describe the idea of using superposition and entanglement as a way to model and simulate quantum phenomena.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"58 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128627642","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 : 2015-07-20DOI: 10.1109/HPCSim.2015.7237094
Viet Vu Duy, O. Sander, T. Sandmann, Jan Heidelberger, S. Bähr, J. Becker
Especially in complex system-of-systems scenarios, where multiple high-performance or real-time processing functions need to co-exist and interact, reconfigurable devices together with virtualization techniques show considerable promise to increase efficiency, ease integration and maintain functional and non-functional properties of the individual functions. In a previous work, we proposed a concept that leverages the advantages of FPGA's partial reconfiguration in heterogeneous mixed criticality multicore systems. The basic idea how to handle the partial reconfiguration transparently for noncritical tasks, while providing full control and a predictable behavior for safety relevant tasks was described. In this paper, we focus on the on-demand partial reconfiguration of coprocessors and its implementation details. Our prototype is implemented on an Intel multicore system and a Xilinx Virtex-7 FPGA connected via PCI Express, taking advantage of the Single-Root I/O Virtualization capabilities in modern PCI Express implementations. Experimental results show that compared to the reference software implementation, our concept achieves significantly shorter reconfiguration time with lower variance under various system load situations.
{"title":"On-demand reconfiguration for coprocessors in mixed criticality multicore systems","authors":"Viet Vu Duy, O. Sander, T. Sandmann, Jan Heidelberger, S. Bähr, J. Becker","doi":"10.1109/HPCSim.2015.7237094","DOIUrl":"https://doi.org/10.1109/HPCSim.2015.7237094","url":null,"abstract":"Especially in complex system-of-systems scenarios, where multiple high-performance or real-time processing functions need to co-exist and interact, reconfigurable devices together with virtualization techniques show considerable promise to increase efficiency, ease integration and maintain functional and non-functional properties of the individual functions. In a previous work, we proposed a concept that leverages the advantages of FPGA's partial reconfiguration in heterogeneous mixed criticality multicore systems. The basic idea how to handle the partial reconfiguration transparently for noncritical tasks, while providing full control and a predictable behavior for safety relevant tasks was described. In this paper, we focus on the on-demand partial reconfiguration of coprocessors and its implementation details. Our prototype is implemented on an Intel multicore system and a Xilinx Virtex-7 FPGA connected via PCI Express, taking advantage of the Single-Root I/O Virtualization capabilities in modern PCI Express implementations. Experimental results show that compared to the reference software implementation, our concept achieves significantly shorter reconfiguration time with lower variance under various system load situations.","PeriodicalId":134009,"journal":{"name":"2015 International Conference on High Performance Computing & Simulation (HPCS)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2015-07-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127422386","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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