Design and Implementation of a Stateful Network Packet Processing
610 IEEE/ACM TRANSACTIONS ON NETWORKING, VOL. 25, NO. 1, FEBRUARY 2017 Design and Implementation of a Stateful Network Packet Processing Framework for GPUs Giorgos Vasiliadis, Lazaros Koromilas, Michalis Polychronakis, and Sotiris Ioannidis Abstract— Graphics processing units (GPUs) are a powerful and TCAMs, have greatly reduced both the cost and time platform for building the high-speed network traffic process- to develop network traffic processing systems, and have ing applications using low-cost hardware. The existing systems been successfully used in routers [4], [7] and network tap the massively parallel architecture of GPUs to speed up certain computationally intensive tasks, such as cryptographic intrusion detection systems [27], [34]. These systems offer a operations and pattern matching. However, they still suffer from scalable method of processing network packets in high-speed significant overheads due to critical-path operations that are still environments. However, implementations based on special- being carried out on the CPU, and redundant inter-device data purpose hardware are very difficult to extend and program, transfers. In this paper, we present GASPP, a programmable net- and prohibit them from being widely adopted by the industry. work traffic processing framework tailored to modern graphics processors. GASPP integrates optimized GPU-based implemen- In contrast, the emergence of commodity many-core tations of a broad range of operations commonly used in the architectures, such as multicore CPUs and modern graph- network traffic processing applications, including the first purely ics processors (GPUs) has proven to be a good solution GPU-based implementation of network flow tracking and TCP for accelerating many network applications, and has led stream reassembly.
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