Improving Non-minimal and Adaptive Routing Algorithms in Slim Fly Networks

Interconnection networks must meet the communication demands of current High-Performance Computing systems. In order to interconnect efficiently the end nodes of these systems with a good performance-to-cost ratio, new network topologies have been proposed in the last years that leverage high-radix switches, such as Slim Fly. Adversarial traffic patterns, however, may reduce severely the performance of Slim Fly networks when using only minimal-path routing. In order to mitigate the performance degradation in these scenarios, Slim Fly networks should configure an oblivious or adaptive non-minimal routing. The non-minimal routing algorithms proposed for Slim Fly usually rely on Valiant's algorithm to select the paths, at the cost of doubling the average path-length, as well as the number of Virtual Channels (VCs) required to prevent deadlocks. Moreover, Valiant may introduce additional inefficiencies when applied to Slim Fly networks, such as the "turn-around problem" that we analyze in this work. With the aim of overcoming these drawbacks, we propose in this paper two variants of the Valiant's algorithm that improve the non-minimal path selection in Slim Fly networks. They are designed to be combined with adaptive routing algorithms that rely on Valiant to select non-minimalpaths, such as UGAL or PAR, which we have adapted to the Slim Fly topology. Through the results from simulation experiments, we show that our proposals improve the network performance and/or reduce the number of required VCs to prevent deadlocks, even in scenarios with adversarial traffic.