RECN-IQ: A Cost-Effective Input-Queued Switch Architecture with Congestion Management

• Authors: Gaspar Mora;Pedro J. Garcia;Jose Flich;Jose Duato
• Venue: ICPP '07 Proceedings of the 2007 International Conference on Parallel Processing
• Year: 2007

As the number of computing and storage nodes keeps increasing, the interconnection network is becoming a key element of many computing and communication systems, where the overall performance directly depends on network performance. This performance may dramatically drop during congestion situations. Although congestion may be avoided by overdimensioning the network, the current trend is to reduce overall cost and power consumption by reducing the number of network components. Thus, the network will be prone to congestion, thereby becoming mandatory the use of congestion management techniques. In that sense, the technique known as Regional Explicit Congestion Notification (RECN) completely eliminates the Head-of-Line (HOL) blocking produced by congested packets, turning congestion harmless. However, RECN has been designed for switches with queues at input and output ports (CIOQ switches), thus it can not be directly applied to other types of switches. Additionally, the method RECN uses for detecting congestion requires several detection queues that increase the memory requirements and thus switch cost. Thus, we completely redefine the RECN mechanism in order to achieve different goals. First, we adapt RECN to a switch organization with queues only at input ports (IQ switches). These switches are simpler and cheaper to produce than CIOQ ones. Second, we propose a new method for detecting congestion that does not require several detection queues, thereby reducing RECN memory requirements. These improvements lead to achieve a cost-effective switch organization that derive maximum performance even in the presence of congestion. Also, we present in detail a realistic switch architecture supporting the new mechanism. Results demonstrate that the new RECN version in an IQ switch achieves maximum network performance in all the analyzed situations. These results have been obtained with a reduction factor of data memory requirements of 5 with respect to the previous RECN mechanism in CIOQ switches.