Uday Bondhugula and N. Viswanadham
Channel: Big Data Initiative at CSA (IISc)
Date: 30/08/2014

On July 3, 2014, we had Prof. Uday Bondhugula and Prof. N. Viswanadham speak about systems for big data. 

The first talk by Prof. Bondhugula focused on big data from the point of view of the programmer. In particular, how can techniques from high performance computing and parallel computing be leveraged? Prof. Bondhugula gave an overview of various approaches to automate optimizing code to work in big data settings.

Prof. N.V. gave a bird's eye tour of the role of big data in manufacturing supply chains. In a fascinating talk, he discussed how supply chains are evolving due to new technologies and how traditional manufacturing networks need to change.

------------------------------------------

Scalable Programming Technologies and Architectures for Big Data 

Abstract: This talk will present challenges associated with developing programs for big data along with some useful programming techniques and paradigms. Big data has a strong connection with high performance computing due to the need to extract parallelism when dealing with large amounts of data. We will highlight the problem of data movement and the need to exploit data locality and minimize data communication. We will also look at the relative strengths and weaknesses of various approaches: automatic compiler/runtime-based, domain-specific tools and code generators, tuned library-based, and completely manual. At a high level, we will also understand the merits and weaknesses of languages that provide a higher level of abstraction for expressive and productive programming at the expense of performance -- from C to R. 

------------------------------------------

Big Data Based Decision making in Manufacturing Supply Chains 

Abstract: Decision making in supply chains is based on optimization models and the data from past sales. Software tools such as ERP, CRP, TMS, and WMS have been developed and used in the Industry. The aim is to deliver quality products to the customers at the right cost. 

Currently, there are several new trends that are happening in the supply chain arena. Globalization has created dispersed supply chains which are vulnerable and dependent on entities and factors that are exogenous to the supply chain. Also, technologies such as Big data, Cloud computing, Blogs, Social Media, Internet of Things and Mobility have become sources of large volumes and several varieties of data. 

In this lecture, I would first present some recent big data start-ups that are revolutionizing or disrupting the traditional manufacturing networks. We then discuss how the new developments in tagging, sensing and embedding effects the four important supply chain processes: procurement, manufacturing, maintenance & repair and retail. Next, we present the big data ecosystem model: big data service chain, institutions (governments and social groups) and their influence on data availability, resources (natural, human, financial, and industry inputs) and delivery service infrastructure (communication and decision). This leads us to the question: what data should I collect, and what algorithms should I use to make decisions that would result in better business outcomes. 

Data based decision making, particularly with unorganized and non-numerical data is a relatively unexplored area of research with abundant opportunities. The takeaways from this lecture are opportunities for both research and start-ups in this evolving area.