  In many embedded systems, such as imaging sys- tems, the system has a single
designated purpose, and same threads are executed repeatedly. Profiling thread
behavior, allows the system to allocate each thread its resources in a way that
improves overall system performance. We study an online resource al-
locationproblem,wherearesourcemanagersimulta- neously allocates resources
(exploration), learns the impact on the different consumers (learning) and im-
proves allocation towards optimal performance (ex- ploitation). We build on the
rich framework of multi- armed bandits and present online and offline algo-
rithms. Through extensive experiments with both synthetic data and real-world
cache allocation to threads we show the merits and properties of our al-
gorithms
