Abstract

The growing demand for high-performance and energy-efficient processing in edge-oriented Systems-on-Chip is driving the adoption of dedicated integrated circuits that accelerate computationally intensive workloads. To minimize area and performance overhead, low-power, general-purpose CPUs are often tightly coupled with domain-specific coprocessors implementing custom instructions, thereby delivering higher throughput and reduced memory traffic. However, commonly used in-order CPUs are not optimized for instruction-level parallelism, leading to stalls in the instruction stream while waiting for long-latency coprocessor operations and under-utilization of the coprocessor while executing other instructions. This work investigates the benefits of replacing simple in-order cores with a more complex out-of-order architecture to dynamically schedule instructions for the main core and coprocessor, optimizing resource utilization and reducing execution time. To ensure generality, an in-depth analysis was carried out by offloading instructions to a custom dummy coprocessor capable of emulating iterative and pipelined operations with arbitrary latency. Various workloads simulating real-world applications were executed on two variants of an open-source microcontroller equipped with a recent out-of-order core and the state-of-the-art CV32E40X in-order core, respectively. Results from Register Transfer Level simulations show that the former configuration executes up to 60% more instructions per cycle, with a modest 12% system area overhead on a 65 nm CMOS technology node.

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