Cache optimization for real-time embedded systems

Cache memory is used, in most single-core and multi-core processors, to improve performance by bridging the speed gap between the main memory and CPU. Even though cache increases performance, it poses some serious challenges for embedded systems running real-time applications. Cache introduces execution time unpredictability due to its adaptive and dynamic nature and cache consumes vast amount of power to be operated. Energy requirement and execution time predictability are crucial for the success of real-time embedded systems. Various cache optimization schemes have been proposed to address the performance, power consumption, and predictability issues. However, currently available solutions are not adequate for real-time embedded systems as they do not address the performance, power consumption, and execution time predictability issues at the same time. Moreover, existing solutions are not suitable for dealing with multi-core architecture issues.;In this dissertation, we develop a methodology through cache optimization for real-time embedded systems that can be used to analyze and improve execution time predictability and performance/power ratio at the same time. This methodology is effective for both single-core and multi-core systems. First, we develop a cache modeling and optimization technique for single-core systems to improve performance. Then, we develop a cache modeling and optimization technique for multi-core systems to improve performance/power ratio. We develop a cache locking scheme to improve execution time predictability for real-time systems. We introduce Miss Table (MT) based cache locking scheme with victim cache (VC) to improve predictability and performance/power ratio. MT holds information about memory blocks, which may cause more misses if not locked, to improve cache locking performance. VC temporarily stores the victim blocks from level-1 cache to improve cache hits. In addition, MT is used to improve cache replacement performance and VC is used to improve cache hits by supporting stream buffering. We also develop strategies to generate realistic workload by characterizing applications to simulate cache optimization and cache locking schemes. Popular MPEG4, H.264/AVC, FFT, MI, and DFT applications are used to run the simulation programs Simulation results show that newly introduced Miss Table based cache locking scheme with victim cache significantly improves the predictability and performance/power ratio. In this work, a reduction of 33% in mean delay per task and a reduction of 41% in total power consumption are achieved by using MT and VCs while locking 25% of level-2 cache size in an 4-core system. It is also observed that execution time predictability can be improved by avoiding more than 50% cache misses while locking one-fourth of the cache size.