The Quickest Multicommodity Flow Problem
Proceedings of the 9th International IPCO Conference on Integer Programming and Combinatorial Optimization
The Nostrum Backbone - a Communication Protocol Stack for Networks on Chip
VLSID '04 Proceedings of the 17th International Conference on VLSI Design
TDM virtual-circuit configuration for network-on-chip
IEEE Transactions on Very Large Scale Integration (VLSI) Systems
The aethereal network on chip after ten years: goals, evolution, lessons, and future
Proceedings of the 47th Design Automation Conference
An improved algorithm for slot selection in the Æthereal network-on-chip
Proceedings of the Fifth International Workshop on Interconnection Network Architecture: On-Chip, Multi-Chip
A Statically Scheduled Time-Division-Multiplexed Network-on-Chip for Real-Time Systems
NOCS '12 Proceedings of the 2012 IEEE/ACM Sixth International Symposium on Networks-on-Chip
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With the rising number of cores on a single chip the question on how to organize the communication among those cores becomes more and more relevant. A common solution is to use a network-on-chip (NoC) that provides communication bandwidth, routing, and arbitration among the cores. The use of NoCs in real-time systems is problematic, since the shared network and all cores connected to it have to be analyzed to derive time bounds of real-time tasks. We propose to use a statically scheduled, time-division-multiplexed NoC design that allows a decoupled analysis of individual real-time tasks. Our network provides virtual circuits between all cores. These virtual circuits are implemented by delivering messages periodically on a static, fixed routing schedule. Since the routing does not change, it can be pre-computed offline. This work focuses on the computation of routing schedules for symmetric NoC topologies, e.g., torus and hyper-cube. Due to the symmetry, the all-to-all communication can be modeled via simplified communication patterns that are concurrently processed by all routers. The scheduling problem is solved by a heuristic that tries to maximize the overlap of active patterns. Our experiments show that, for larger networks, our heuristic yields schedule lengths that are only 15% to 20% longer than theoretical lower bounds.