Supercomputing for Artificial Intelligence and Big Data Applications
UCERD Gathering Intellectuals Fostering Innovations
Unal Center of Educaiton Research & Development
Unal Center of Educaiton Research & Development
UCERD Rawalpindi
Supercomputing Center
UCERD Murree
The evaluation of the information technology demands a processing system that can process big data and perform analysis, future prediction and give solutions in quick time. Machine and deep learning algorithms are now a key component of everything from media and entertainment industry to defense industry. The amount of data generated has skyrocketed, allow scientific problems to solve it by using artificial intelligence techniques. Artificial Intelligence is bringing a paradigm shift to power the increasing availability of data and rapid progress of analytic techniques. The next generation Artificial Intelligence demands dual performance a) predictive accuracy and b computation speed of the process. Therefore, a low-cost, low-power and high-performance supercomputer architecture is required in all fields of academia and research, which can execute supervised and unsupervised artificial intelligence applications.
The course will cover different Hardware Architectures, Software Development Frameworks, Applications of Artificial Intelligence and, future and market of supercomputers in Pakistan. The workshop presents different high performance supercomputing system architectures which are the CPU based Supercomputer, the CPU-GPU based Supercomputer and the Embedded Supercomputer system for executing big data applications using artificial intelligence approaches and parallel programming models. To handle the big data and to solve artificial intelligence problems the speaker will give hands on demo of deep learning classifiers and models using Barcelona Super-computing Center PowerCTE GPU. Moreover, the speaker will share his experience of his journey of supercomputers in Pakistan. Opportunities, and risks of HPC growing market in Pakistan will help participants to understand the local market trends and future investments in the region.
The course will cover different Hardware Architectures, Software Development Frameworks, Applications of Artificial Intelligence and, future and market of supercomputers in Pakistan. The workshop presents different high performance supercomputing system architectures which are the CPU based Supercomputer, the CPU-GPU based Supercomputer and the Embedded Supercomputer system for executing big data applications using artificial intelligence approaches and parallel programming models. To handle the big data and to solve artificial intelligence problems the speaker will give hands on demo of deep learning classifiers and models using Barcelona Super-computing Center PowerCTE GPU. Moreover, the speaker will share his experience of his journey of supercomputers in Pakistan. Opportunities, and risks of HPC growing market in Pakistan will help participants to understand the local market trends and future investments in the region.
• Supercomputing for Artificial Intelligence
• Using Supercomputers for Deep Learning Training
• A Gentle introduction to Deep Reinforcement Learning
• Scalable Deep Learning on Parallel and Distributed Infrastructures
• Train a Neural Network on multi-GPU with TensorFlow
• Distributed Deep Learning with Horovod
• Future and Market of Supercomputers in Pakistan
• Using Supercomputers for Deep Learning Training
• A Gentle introduction to Deep Reinforcement Learning
• Scalable Deep Learning on Parallel and Distributed Infrastructures
• Train a Neural Network on multi-GPU with TensorFlow
• Distributed Deep Learning with Horovod
• Future and Market of Supercomputers in Pakistan
Handbook of Research on Methodologies and Applications of Supercomputing
Multigrid methods: theory, applications, and supercomputing (Download link)
Supercomputing in engineering analysis (link)
The Student Supercomputer Challenge Guide (link)
Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
Deep Learning for Medical Image AnalysisVolume:
Author(s):S. Kevin Zhou, Hayit Greenspan and Dinggang Shen (Eds.)
Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization, 2nd Edition
Python Pandas for Beginners: Pandas Specialization for Data Scientist (Python for Beginners in Data Science and Data Analysis Book 2)
Multigrid methods: theory, applications, and supercomputing (Download link)
Supercomputing in engineering analysis (link)
The Student Supercomputer Challenge Guide (link)
Deep Learning for the Life Sciences: Applying Deep Learning to Genomics, Microscopy, Drug Discovery, and More
Deep Learning for Medical Image AnalysisVolume:
Author(s):S. Kevin Zhou, Hayit Greenspan and Dinggang Shen (Eds.)
Hands-On Data Analysis with Pandas: A Python data science handbook for data collection, wrangling, analysis, and visualization, 2nd Edition
Python Pandas for Beginners: Pandas Specialization for Data Scientist (Python for Beginners in Data Science and Data Analysis Book 2)
Prof. Tassadaq Hussain Cheema.
He did his Ph.D. from Barcelona-tech Spain, in collaboration with Barcelona Supercomputing Center and Microsoft Research Center.
More Details:
He is a member of HiPEAC: European Network on High Performance and Embedded Architecture and Compilation, Barcelona Supercomputing Center and Microsoft ResearchCentre Spain.
Until January 2018, he had more than 19 years of industrial experience including, Barcelona Supercomputing Centre Spain, Infineon technology France, Microsoft Research Cambridge, PLDA Italia, IBM Zurich Switzerland, and REPSOL Spain. He has published more than 80 international publications and filed 5 patents.
Tassadaq's main research lines are Machine Learning, Parallel Programming, Heterogeneous Multi-core Architectures, Single board Computers, Embedded Computer Vision, Runtime Resource Aware Architectures, Software Defined Radio and Supercomputing for Artificial Intelligence and Scientific Computing.
www.tassadaq.pakistansupercomputing.com
He did his Ph.D. from Barcelona-tech Spain, in collaboration with Barcelona Supercomputing Center and Microsoft Research Center.
More Details:
He is a member of HiPEAC: European Network on High Performance and Embedded Architecture and Compilation, Barcelona Supercomputing Center and Microsoft ResearchCentre Spain.
Until January 2018, he had more than 19 years of industrial experience including, Barcelona Supercomputing Centre Spain, Infineon technology France, Microsoft Research Cambridge, PLDA Italia, IBM Zurich Switzerland, and REPSOL Spain. He has published more than 80 international publications and filed 5 patents.
Tassadaq's main research lines are Machine Learning, Parallel Programming, Heterogeneous Multi-core Architectures, Single board Computers, Embedded Computer Vision, Runtime Resource Aware Architectures, Software Defined Radio and Supercomputing for Artificial Intelligence and Scientific Computing.
www.tassadaq.pakistansupercomputing.com
