Channel Reservation Protocol for Over-Subscribed Channels and Destinations

Channels in system-wide networks tend to be over-subscribed due to the cost of bandwidth and increasing traffic demands. To make matters worse, workloads can overstress specific destinations, creating hotspots. Lossless networks offer attractive advantages compared to lossy networks but suffer from tree saturation. This led to the development of explicit congestion notification (ECN). However, ECN is very sensitive to its configuration parameters and acts only after congestion forms. We propose channel reservation protocol (CRP) to enable sources to reserve bandwidth in multiple resources in advance of packet transmission and with a single request, but without idling resources like circuit switching. CRP prevents congestion from ever occurring and thus reacts instantly to traffic changes, whereas ECN requires 300,000 cycles to stabilize in our experiments. Furthermore, ECN may not prevent congestion formed by short-lived flows generated by a large combination of source–destination pairs. General Terms Congestion control, congestion notification, large-scale networks, tree saturation, reservation protocol 1

MeSAP: a fast analytic power model for DRAM memories

\u3cp\u3eThe design of an energy-efficient memory subsystem is one of the key issues that system architects face today. To achieve this goal, architects usually rely on system simulators and trace-based DRAM power models. However, their long execution time makes the approach infeasible for the design-space exploration of next-generation exascale computing systems. Analytic models, in contrast, are orders of magnitude faster. In this paper, we propose a new analytic memory-scheduler-agnostic power model for DRAM, henceforth referred to as MeSAP. Similarly to state-of-the-art trace-based approaches, our analytic model achieves an average error of 20%, while being an order of magnitude faster. Furthermore, we integrate MeSAP into an analytic performance model of general-purpose processors and show its applicability to the design of a computing system targeting scientific image processing applications.\u3c/p\u3