Learning from experimentation allows a system to acquire planning domain knowledge by correcting its knowledge when an action execution fails. Experiments are designed and planned...
Google's MapReduce programming model serves for processing large data sets in a massively parallel manner. We deliver the first rigorous description of the model including it...
Future systems will have to support multiple and concurrent dynamic compute-intensive applications, while respecting real-time and energy consumption constraints. To overcome these...
Nicolas Ventroux, Tanguy Sassolas, Raphael David, ...
Most shared memory systems maximize performance by unpredictably resolving memory races. Unpredictable memory races can lead to nondeterminism in parallel programs, which can suff...
Derek Hower, Polina Dudnik, Mark D. Hill, David A....
With advances in semiconductor technology, processors are becoming larger and more complex. Future processor designers will face an enormous design space, and must evaluate more a...