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Andrew Herbert - Hot Topics From Microsoft Research


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Andrew Herbert - Hot Topics From Microsoft Research

  1. 1. Hot Topics From Microsoft ResearchAndrew HerbertChairman, Microsoft Research EMEA15 December 2010
  2. 2. Data, Cloud, Client
  3. 3. data
  4. 4. The mythical man-month If 1 accountant takes 8 hours to do my taxes, then 8 accountants can do 8 people’s taxes in 8 hours. But 8 accountants can’t do 1 tax return in 1 hour. The mythical cpu-secondIf it takes a 1-core machine 1 second to process 1 GB of data, how long does a 64-core machine take to process 64GB? Sometimes 1 second. Sometimes more.
  5. 5. Barrelfish A new OS architecture for scalable multicore systems Approach: structure the OS as a distributed system Design principles: • Make inter-core communication explicit • Make OS structure hardware-neutral • View state as replicated
  6. 6. A Multikernel vs Other Operating Systems Spectrum of sharing and locking disciplines Traditional OSes Multikernel Shared state, Finer-grained Clustered objects, Distributed state, one-big-lock locking partitioning replica maintenance Multikernel Windows and Unix variants are Research operating evolving from the far left operating system: towards the middle systems eg K42 Barrelfish
  7. 7. Barrelfish Structure App App App App OS node OS node OS node OS node State State State Async messages State replica replica replica replica x86 x64 ARM GPU Hardware interconnect
  8. 8. Natural User Interfaces
  9. 9. "This is a pivotal moment that will carrywith it a wave of change, the ripples ofwhich will reach far beyond video games“STEVEN SPIELBERG
  10. 10. Understanding Human MotionAndrew Blake, Kentaro Toyama,Probablisitic tracking in a metric space,Awarded the Marr Prize ,IEEE International conference on Computer Vision, 2001
  11. 11. Understanding Human MotionRamanan Navaratnam, Andrew Fitzgibbon, Roberto Cipolla,The Joint Manifold Model for Semi-supervised Multi-valued Regression,IEEE International conference on Computer Vision, 2007
  12. 12. Understanding ImagesJ. Shotton, J. Winn, C. Rother, A. Criminisi, TextonBoost: Joint Appearance, Shapeand Context Modeling for Multi-Class Object Recognition and Segmentation.European Conference on Computer Vision, 2006
  13. 13. Learning From Data
  14. 14. Large Scale Machine LearningBehind the scenes: AdPredictor
  15. 15. Problem: Ad Relevance
  16. 16. Click/Ad Information Probability 1341201 1570165Listing ID 2213187 9215433 +Match Exact MatchType Broad Match ML-1 p(Click|Query, Ad)Position SB-1 SB-2