The recent advancements in hardware prefetching, CGRA efficiency, and decentralized reconfiguration languages are pushing the boundaries of their respective fields. In hardware prefetching, there is a notable shift towards leveraging internal temporal correlations within spatial patterns to enhance prefetching performance, addressing the limitations of context-based predictions. This approach not only improves flexibility and practicality but also offers significant performance gains across various scenarios. In the realm of CGRAs, there is a focus on aligning compute and communication capabilities to optimize energy and area efficiency without compromising performance or generality. This is achieved through the identification and execution of recurring communication patterns within dataflow graphs. Lastly, decentralized reconfiguration languages are gaining traction, particularly in unstable network environments like edge computing and cyber-physical systems, where they provide robust coordination mechanisms and formal semantics to ensure executability and reliability. These developments collectively highlight innovative strategies that are advancing the efficiency, performance, and reliability of hardware and software systems.