SC19 Proceedings

The International Conference for High Performance Computing, Networking, Storage, and Analysis

INCA: In-Network Compute Assistance

Authors: Whit Schonbein (Sandia National Laboratories), Ryan E. Grant (Sandia National Laboratories), Matthew G. F. Dosanjh (Sandia National Laboratories), Dorian Arnold (Emory University)

Abstract: Current proposals for in-network data processing operate on data as it streams through a network switch or endpoint. Since compute resources must be available when data arrives, these approaches provide deadline-based models of execution. This paper introduces a deadline-free general compute model for network endpoints called INCA: In-Network Compute Assistance. INCA builds upon contemporary NIC offload capabilities to provide on-NIC, deadline-free, general-purpose compute capacities that can be utilized when the network is inactive. We demonstrate INCA is Turing complete, and provide a detailed design for extending existing hardware to support this model. We evaluate runtimes for a selection of kernels, including several optimizations, and show INCA can provide up to a 11% speedup for applications with minimal code modifications and between 25% to 37% when applications are optimized for INCA.

Presentation: file

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