Scope of the Spring School
Computer systems pervade all parts of human activity: transportation systems, weather and climate simulations, energy supply, medicine, the whole financial sector, and modern science. All these areas have become unthinkable without efficient hardware and software support. As these systems relentlessly acquire, process, exchange, and store data, we live in a Big Data world where information is accumulating at an exponential rate. Just think of the recent growth of online social networks, online shopping transactions, or genomic data in bioinformatics.
The urging problem has shifted from collecting enough data to dealing with its impetuous growth and abundance. Data volumes often grow faster than the hardware processing rate. On top of this, hardware improvements do not automatically lead to faster applications any more since single core performance has stalled and memory hierarchies become more and more complicated. This requires algorithms that are massively parallel and use memory access patterns with high locality. Moreover, an x-times machine performance improvement only translates into x-times larger manageable data volumes if the employed algorithms scale nearly linearly with the input size. Last but not least, the data often have hidden patterns. Uncovering these patterns allows us to predict future social network connections, to develop effective drugs, or to reduce risk to life in natural disasters.
All these aspects pose new challenges. Appropriate solution techniques require quick storage and access mechanisms with efficient data structures as well as large-scale data analytic methods that rely on appropriate concepts such as approximation.
- Feb 24:
| Photos are online.|
- Feb 17:
| Venue for the school is CS25, CSE Department, IIT Madras, Chennai.|
- Jan 27:
| Program is available.|
- Sep 25:
| Registrations closed on October 31, 2015.|
- Sep 25:
| Summer school receives funding by IIT Madras Alumni '89 batch.|
- Sep 7:
| Summer school receives funding by DFG.|
- Sep 4:
| Speakers announced.|
Motivation and Objectives
The Indo-German Spring School on Algorithms for Big Data wants to train young researchers, in particular PhD students and postdocs, in algorithmic solution techniques for big data problems. To this end, we bring leading researchers together that work on big data aspects in different scientific subfields - albeit under the common umbrella of efficient algorithms and data structures for large-scale problems. Besides the training, such a forum would allow the exchange of ideas for solving future challenges in the big data context. Moreover, and at least equally important, the lectures presented by international experts introduce students to unfamiliar areas related to each student’s own expertise. The newly acquired knowledge is likely to improve the students’ skills and take their scientific achievements to a higher level.
We will also invite selected industrial researchers from India as speakers. Furthermore, interested practitioners are welcome to attend and share their experience in discussion rounds. This opening to industry is meant to improve the exchange between theory and practice in both directions. Academic researchers learn about application requirements in practice and, in turn, top-notch academic results may enter industrial solutions sooner. This way the workshop would also serve as a platform for seeding new collaborations, both between academia and industry but also within academia across the two countries and beyond.