Download Keynote Address - Microsoft Research Cambridge2.32 Mb

Microsoft Research Cambridge
Cambridge in Numbers
Staff
Honours
111 researchers
1 Knighthood
148 total staff
1 Officer of the Order of the
British Empire (OBE)
100 interns per year
17 R&D staff from other
Microsoft R&D groups
11 Visiting Researchers per
year
Over 150 day visitors,
seminar speakers per year
Outputs
1 Turing Award winner
1 Kyoto prize winner
2 Marr prize winners
2 ACM Fellows
1 IEEE Fellow
3 Royal Society Fellows
1 Royal Society of Edinburgh
Fellow
4 Royal Academy of
Engineering Fellows
70+ top tier publications per
year
45+ patents filed per year
Mission
Advance state of the art in computer science
Transfer technology to Microsoft businesses
Lead Microsoft into the future
Culture
Integrated Systems Information Retrieval
Cloud Computing Computational Biology
Programming Security Machine Learning
Inference Supporting European Science
Sensors and Devices Constraint Reasoning
Distributed Systems Socio-digital Systems
Natural User Interfaces Operating Systems
Game Theory Networking Computational
Ecology Data Mining Environmental Science
Understanding Images Program Structure
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Listing ID
1570165
2213187
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Match
Type
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Exact Match
Broad Match
ML-1
Position
SB-1
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Transactional Memory
•
•
A high-level approach to building efficient, correct
shared-memory data structures
– The programmer marks sections of code that
should run atomically
– An implementation can introduce concurrency if
there is no interference
Simpler programming model than locks & condition
variables
Language design
Workloads
Implementation
techniques
void pushLeft(int item) {
atomic {
QElem e = new QElem(item);
e.right = this.leftSentinel.right;
e.left = this.leftSentinel;
this.leftSentinel.right.left = e;
this.leftSentinel.right = e;
}
}
Tech transfer contributing to
release of STM.NET in July ’09
SPIM: A Visual Programming Language for Biology
•
Scientists are building computer models of
biological systems to
– Design and simulate experiments,
saving time and resources
– Understand how biological systems
and diseases work
•
We developed a biological language using
advanced concurrency theory
– Exact algorithm for simulating
randomness inherent in biology
– biological models are decomposed
into components
•
We worked with leading Immunologists
– Built models that improved our
understanding of how viruses and
cancers are detected in cells.
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