Efficient Service Allocation in Hardware Using Credit-Controlled Static-Priority Arbitration

Resources in contemporary systems-on-chip (SoC) are shared between applications to reduce cost. Access to shared resources is provided by arbiters that require a small hardware implementation and must run at high speed. To manage heavily loaded resources, such as memory channels, it is also important that the arbiter minimizes over allocation. A Credit-Controlled Static-Priority (CCSP) arbiter comprised of a rate regulator and a static-priority scheduler has been proposed for scheduling access to SoC resources. The proposed rate regulator, however, is not straight-forward to implement in hardware, and assumes that service is allocated with infinite precision. In this paper, we introduce a fast and small hardware implementation of the CCSP rate regulator and formally prove its correctness. We also show an efficient way of representing the allocated service in hardware with finite precision. Based on this representation, we define and evaluate two allocation strategies, and derive tight bounds on their respective over allocations. We show that increasing the precision of the implementation results in an exponential reduction in maximum over allocation at the cost of a linear increase in area. We demonstrate that the allocation strategy has a large impact on the allocation success rate for use cases with high load. Finally, we compare CCSP to traditional frame-based approaches and conclude that having a fine allocation granularity that is decoupled from latency is essential to manage highly loaded resources in real-time systems.