System-level performance optimization of the data queueing memory management in high-speed network processors

In high-speed network processors, data queueing has to allow real-time memory (de)allocation, buffering, retrieving, and forwarding of incoming data packets. Its implementation must be highly optimized to combine high speed, low power, large data storage, and high memory bandwidth. In this paper, such data queueing is used as case study to demonstrate the effectiveness of a new system-level exploration method for optimizing the memory performance in dynamic memory management. Assuming that a multi-bank memory architecture is used for data storage, the method trades off bank conflicts against memory accesses during real-time memory (de)allocation. It has been applied to the data queueing module of the PRO/sup 3/ system. Compared with the conventional memory management technique for embedded systems, our exploration method can save up to 90% of the bank conflicts, which allows to improve worst-case memory performance of data queueing operations by 50% too.