Scientific Objectives

 

For the growing number of problems where experiments are impossible, dangerous, or inordinately costly, extreme-scale computing will enable the solution of vastly more accurate predictive models and the analysis of massive quantities of data, producing quantum advances in areas of science and technology. This lab will work with the following line of action:  

 

Transformation, not the evolution:

In traditional scientific computing, many computational problems are characterized by connection advances in computing capabilities and the benefits gained by such advances first. Such problems have the characteristic that computing a bit better gains results that are a bit better. But what if changing the model or internal design may leads toward better performance. So many systems require transformation, not the evolution.

Voracious Computing:

In some problem areas of computational sciences, there is no a priori reason to believe that increased computing capabilities will lead to increased knowledge, even in an incremental way. So increasing the performance is not always the task. In case of data analytics, increased knowledge may one of KPI of any system.  

Transformational Computing:  

There is certain class of problems where a smaller calculation does not solve the underlying problem, but a sufficiently large calculation can solve the problem completely. For this, the programmer has to set the relation between the size of the problem and the amount of the computation required. And exascale computing will enable such transformations in all disciplines.

 

The general objectives 

 

• Promotion of the theoretical and applied data sciences in academic and industry
• Contribution of knowledge w.r.t social and economic relevance in Pakistan’s perspective
• Related training at all levels for production of necessary Human Resource 
• Policy and Planning: Dialogues and consultation through conferences, seminars and workshop on emerging themes and the selected application domains of Data Analytics.
• Networking: Maximizing Pakistan’s participation within international communities working in the selected application domains   
• To enhance Pakistan’s footprint to the selected application domains  community internationally

The Specific objectives  

 

• There are several research groups at NEDUET and other Universities in Pakistan in different domain of data analytics and this lab will play its role in mentoring and providing the computational and software facilities to them.  
• A general entry point for access to data analysis and machine learning tool for both computing and non-computer background scientists. 
• Channels for sharing information and best practices in the selected domains 
• Development, testing and debugging of new data analytics software, libraries, tools and applications in selected domains  
• Introducing and Enhancing  open collaboration in cross disciplinary research domain
• This lab will also enable NEDUET and other universities to pursue data analytics in various real time applications from a theoretical to implementation point of view, thus opening up a new direction of research
• Repository of software and libraries for selected application domains community