Exploiting Speculative and Asymmetric Execution on Multicore Architectures

The design of microprocessors is undergoing radical changes that affect the performance and reliability of hardware and will have a high impact on software development. Future systems will depend on a deep collaboration between software and hardware to cope with the current and predicted system design challenges. Instead of higher frequencies, the number of processor cores per chip is growing. Eventually, processors will be composed of cores that run at different speeds or support specialized features to accelerate critical portions of an application. Performance improvements of software will only result from increasing parallelism and introducing asymmetric processing. At the same time, substantial enhancements in the energy efficiency of hardware are required to make use of the increasing transistor density. Unfortunately, the downscaling of transistor size and power will degrade the reliability of the hardware, which must be compensated by software. In this thesis, we present new algorithms and tools that exploit speculative and asymmetric execution to address the performance and reliability challenges of multicore architectures. Our solutions facilitate both the assimilation of software to the changing hardware properties as well as the adjustment of hardware to the software it executes. We use speculation based on transactional memory to improve the synchronization of multi-threaded applications. We show that shared memory synchronization must not only be scalable to large numbers of cores but also robust such that it can guarantee progress in the presence of hardware faults. Therefore, we streamline transactional memory for a better throughput and add fault tolerance mechanisms with a reduced overhead by speculating optimistically on an error-free execution. If hardware faults are present, they can manifest either in a single event upset or crashes and misbehavior of threads. We address the former by applying transactions to checkpoint and replicate the state such that threads can correct and continue their execution. The latter is tackled by extending the synchronization such that it can tolerate crashes and misbehavior of other threads. We improve the efficiency of transactional memory by enabling a lightweight thread that always wins conflicts and significantly reduces the overheads. Further performance gains are possible by exploiting the asymmetric properties of applications. We introduce an asymmetric instrumentation of transactional code paths to enable applications to adapt to the underlying hardware. With explicit frequency control of individual cores, we show how applications can expose their possibly asymmetric computing demand and dynamically adjust the hardware to make a more efficient usage of the available resources