Accelerating distributed computing applications using a network offloading framework

During the last two decades, a considerable amount of academic research has been conducted in the field of distributed computing. Typically, distributed applications require frequent network communication, which becomes a dominate factor in the overall runtime overhead. The recent proliferation of programmable peripheral devices for computer systems may be utilized in order to improve the performance of such applications. Offloading application-specific network functions to peripheral devices can improve performance and reduce host CPU utilization. Due to the peculiarities of each particular device and the difficulty of programming an outboard CPU, the need for an abstracted offloading framework is apparent. This paper proposes a novel offloading framework, called HYDRA that enables utilization of such devices. The framework enables an application developer to design the offloading aspects of the application by specifying an "offloading layout", which is enforced by the runtime during application deployment. The performance of a variety of distributed algorithms can be significantly improved by utilizing such a framework. We demonstrate this claim by evaluating several offloaded applications: a distributed total message ordering algorithm and a packet generator.