Efficient Execution of Smart City’s Assets Through a Massive Parallel Computational Model

Urban areas are at the forefront for upcoming wave of emerging technologies in building smart sustainable cities. These real time fashion based smart cities will be combined with physical infrastructures and services to improve the lives of its citizens. Transformation to smart city, innovation in performance increasing, data processing, planning and management will be required for smart city’s assets. In order to achieve monolithic performance and data processing, an efficient parallel computational approach can bring us closer to the desired smartness in societies. In this study, we have proposed a massive parallel computational model to deal smart city’s assets and maintain real time connectivity among them. This model will be considered as initiative for emerging exascale computing system which will be used to deal the applications in intelligent smart cities.

[1]  Peter Cruickshank,et al.  Creating Smart-er Cities: An Overview , 2011 .

[2]  Yang Wei,et al.  Wearable and autonomous computing for future smart cities: Open challenges , 2017, 2017 25th International Conference on Software, Telecommunications and Computer Networks (SoftCOM).

[3]  James H. Laros,et al.  Evaluating the viability of process replication reliability for exascale systems , 2011, 2011 International Conference for High Performance Computing, Networking, Storage and Analysis (SC).

[4]  Jack Dongarra,et al.  Sunway TaihuLight supercomputer makes its appearance , 2016 .

[5]  Houssain Kettani.  Advances in high performance computing and their impact on smart cities , 2017, ICSDE.

[6]  Azadeh Farzan,et al.  Synthesis of divide and conquer parallelism for loops , 2017, PLDI.

[7]  Henri E. Bal,et al.  Programming Models for Multicore and Many-Core Computing Systems , 2017 .

[8]  Al Geist,et al.  A survey of high-performance computing scaling challenges , 2017, Int. J. High Perform. Comput. Appl..

[9]  Jinxing Hu,et al.  Managing Big City Information Based on WebVRGIS , 2016, IEEE Access.

[10]  Reinhard König,et al.  Managing Urban Resilience , 2017, Informatik-Spektrum.

[11]  Theresa A. Pardo,et al.  Conceptualizing smart city with dimensions of technology, people, and institutions , 2011, dg.o '11.

[12]  Toshio Obi,et al.  Promoting ICT innovations for the ageing population in Japan , 2013, Int. J. Medical Informatics.

[13]  Yang Hong,et al.  A heterogeneous computing accelerated SCE-UA global optimization method using OpenMP, OpenCL, CUDA, and OpenACC. , 2017, Water science and technology : a journal of the International Association on Water Pollution Research.

[14]  F. Cappello,et al.  Blocking vs. Non-Blocking Coordinated Checkpointing for Large-Scale Fault Tolerant MPI , 2006, ACM/IEEE SC 2006 Conference (SC'06).

[15]  Yasir Mehmood,et al.  Enabling Communication Technologies for Smart Cities , 2017, IEEE Communications Magazine.

[16]  Naveed Ahmed Khan,et al.  Software Engineering Challenges for Ubiquitous Computing in Various Applications , 2013, 2013 11th International Conference on Frontiers of Information Technology.

[17]  Tyng-Yeu Liang,et al.  An OpenMP Programming Toolkit for Hybrid CPU/GPU Clusters Based on Software Unified Memory , 2016, J. Inf. Sci. Eng..

[18]  Christian Terboven,et al.  OpenACC - First Experiences with Real-World Applications , 2012, Euro-Par.

[19]  Ashwin Pajankar.  Message Passing Interface , 2017 .

[20]  José Ramón Gil-García,et al.  Understanding Smart Cities: An Integrative Framework , 2012, HICSS.

[21]  Fathy Alboraei Eassa,et al.  Empirical Analysis of HPC Using Different Programming Models , 2016 .

[22]  Jeffrey S. Vetter,et al.  A Survey of CPU-GPU Heterogeneous Computing Techniques , 2015, ACM Comput. Surv..

[23]  Michael A. West,et al.  GPU-Accelerated Bayesian Learning and Forecasting in Simultaneous Graphical Dynamic Linear Models , 2016 .

[24]  John E. Stone,et al.  OpenCL: A Parallel Programming Standard for Heterogeneous Computing Systems , 2010, Computing in Science & Engineering.

[25]  Akhil Khare,et al.  Internet of Things for Smart Cities , 2014, IEEE Internet of Things Journal.

[26]  M. Weiser,et al.  Hot topics-ubiquitous computing , 1993 .

[27]  Jason Sanders,et al.  CUDA by example: an introduction to general purpose GPU programming , 2010 .

[28]  Dhabaleswar K. Panda,et al.  Designing efficient small message transfer mechanism for inter-node MPI communication on InfiniBand GPU clusters , 2014, 2014 21st International Conference on High Performance Computing (HiPC).