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SUMMARY:Practical Abstractions for Dynamic and Parallel Software - Umut Ac
 ar\, Max Planck Institute
DTSTART:20120112T100000Z
DTEND:20120112T110000Z
UID:TALK35412@talks.cam.ac.uk
CONTACT:Microsoft Research Cambridge Talks Admins
DESCRIPTION: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\nefficienc
 y and performance. I present practical and powerful abstractions for tamin
 g software complexity in two large domains: 1)dynamic software that intera
 cts 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 de
 signing and developing efficient\, reliable software by using high-level r
 easoning principles and programming techniques. As evidence of their effec
 tiveness\, 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 si
 de\, I show asymptotically significant improvements in efficiency and pres
 ent solutions to several major open problems. On the practical\nside\, I p
 resent programming languages\, compilers\, and related software systems th
 at deliver massive speedups with little or no programmer effort.\n
LOCATION:Large lecture theatre\, Microsoft Research Ltd\, 7 J J Thomson Av
 enue (Off Madingley Road)\, Cambridge
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