University of Cambridge > Talks.cam > Microsoft Research Cambridge, public talks > Practical Abstractions for Dynamic and Parallel Software

Practical Abstractions for Dynamic and Parallel Software

Add to your list(s) Download to your calendar using vCal

If you have a question about this talk, please contact Microsoft Research Cambridge Talks Admins.

This event may be recorded and made available internally or externally via http://research.microsoft.com. Microsoft will own the copyright of any recordings made. If you do not wish to have your image/voice recorded please consider this before attending

Developing efficient and reliable software is a difficult task. Increasingly larger and dynamic data sets and parallel hardware further add to the complexity by making it more challenging to achieve efficiency and performance. I present practical and powerful abstractions for taming software complexity in two large domains: 1)dynamic software that interacts with dynamically changing data, and 2)parallel software that utilizes multiple processing units or cores. Together with the algorithmic models and programming-languages that embody them, these abstractions enable designing and developing efficient, reliable software by using high-level reasoning principles and programming techniques. As evidence of their effectiveness, I consider a broad range benchmarks involving lists, arrays, matrices, and trees, as well as sophisticated applications in geometry, machine-learning, and large-scale cloud computing. On the theoretical side, I show asymptotically significant improvements in efficiency and present solutions to several major open problems. On the practical side, I present programming languages, compilers, and related software systems that deliver massive speedups with little or no programmer effort.

This talk is part of the Microsoft Research Cambridge, public talks series.

Tell a friend about this talk:

This talk is included in these lists:

Note that ex-directory lists are not shown.

 

© 2006-2019 Talks.cam, University of Cambridge. Contact Us | Help and Documentation | Privacy and Publicity