As machine learning (ML) systems emerge in end-user applications, learning algorithms and classifiers will need to be robust to an increasingly unpredictable operating environment...
We describe a scheduling technique in which estimated job runtimes and estimated resource availability are used to efficiently distribute workloads across a homogeneous grid of res...
Sam Verboven, Peter Hellinckx, Jan Broeckhove, Fra...
While traditional approaches to code profiling help locate performance bottlenecks, they offer only limited support for removing these bottlenecks. The main reason is the lack of v...
The dynamic optimization problem concerns finding an optimum in a changing environment. In the field of evolutionary algorithms, this implies dealing with a timechanging fitness l...
Tuning compiler optimizations for rapidly evolving hardware makes porting and extending an optimizing compiler for each new platform extremely challenging. Iterative optimization i...
Grigori Fursin, Yuriy Kashnikov, Abdul Wahid Memon...