Efficient and secure context switching and migrations for heterogeneous multiprocessors

Modern mobile processors are constrained by their limited energy resource and demanding applications that require fast execution. Single core designs use voltage/frequency throttling techniques that allow the system to switch between performant and efficient configurations to address this problem. Heterogeneous multicores also need to decide on which core to run rather than just adjust voltage and frequency. Consequently, they remain an open subject in terms of near optimal design and operation. This thesis investigates the performance and energy trade-off when migrating between heterogeneous cores and presents designs that enable low overhead transitions between cores through a series of contributions.The first contribution is based on a novel methodology, that can directly compare the execution of heterogeneous cores. With it, an in-depth investigation of the effects on the memory system when migrating between such cores is conducted. The analysis reveals that heterogeneous multiprocessor system slowdown is asymmetrical. In-Order core performance relies on the memory subsystem, while Out-of-Order execution depends on accurate speculation. A proposed design minimises migration overheads in In-Order cores without making the design prohibitively complex to implement. This is achieved by only sharing the larger caches and the translation state.The second contribution is a branch predictor design that transfers state when a migration occurs between heterogeneous cores. The design eliminates the warm up for Out-of-Order cores by transferring only minimal state. This improves post migration accuracy, potentially enabling better performance and energy efficiency.Finally, security has become a major concern for shared or transferable components in multicore systems, namely the branch predictor. The third contribution in this thesis investigates mitigation techniques of recently discovered side channel attacks. The proposed design flushes all but the most useful branch predictor state, ensuring isolation with minimal performance loss