In all-to-all personalized communication (AAPC), every node of a parallel system sends a potentially unique packet to every other node. AAPC is an important primitive operation for modern parallel compilers, since it is used to redistribute data structures during parallel computations. As an extremely dense communication pattern, AAPC causes congestion in many types of networks and therefore executes very poorly on general purpose, asynchronous message passing routers.We present and evaluate a network architecture that executes allto-all communication optimally on a two-dimensional torus. The router combines optimal partitions of the AAPC step with a selfsynchronizing switching mechanism integrated into a conventional wormhole router. Optimality is achieved by routing along shortest paths while fully utilizing all links. A simple hardware addition for synchronized message switching can guarantee optimal AAPC routing in many existing network architectures.The flexible communication agent of the iWarp VLSI component allowed us to implement an efficient prototype for the evaluation of the hardware complexity as well as possible software overheads. The measured performance on an 8 8 torus exceeded 2 GigaBytes/sec or 80% of the limit set by the raw speed of the interconnects. We make a quantitative comparison of the AAPC router with a conventional message passing system. The potential gain of such a router for larger parallel programs is illustrated with the example of a two-dimensional Fast Fourier Transform.

In a policy-based system, policy goals are described with respect to network entities (e.g., networks and users) instead of enforcement points (e.g., firewalls and routers). This global view has several advantages: usability, global rules are closer to the goals of the human administrator; scalability, the policy system ensures that the enforcement points are configured appropriately, whether there are 1 or 100 enforcement points; and security, the policy system ensures that the policy is enforced consistently. This paper describes techniques for accurately translating from global policy rules to actual per-device configurations, and it describes how these techniques were used in the implementation of Cisco Secure Policy Manager.

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