Emerging intelligent bump-in-the-wire network adapters, iNICs, are increasingly deployed for accelerating custom network functions in large-scale data center and cloud environments such as Microsoft Azure. However, their potential to speed up network-intensive server applications remains largely unexplored due to the lack of appropriate programming models and OS abstractions. GAON is a framework that facilitates accelerating network applications using iNICs. GAON introduces an *ikernel *abstraction that encapsulates the code and state of an iNIC-resident application task. The application dynamically invokes the ikernel by attaching it to a network socket, thereby rerouting the socket traffic to the ikernel. GAON can securely execute multiple ikernels of different applications, isolating ikernel state and network traffic, arbitrating access to network from ikernels and CPU applications, and providing protected access to the ikernel state from the owning CPU application. We prototype GAON on Mellanox Innova 40 Gbps iNICs and develop several accelerated versions of realistic server workloads. For example, the transparent key-value store cache ikernel serves 31Mtps (70% of the line rate) at 5 μs 99th percentile latency for 10 byte key/value pairs, seamlessly improving the host performance by up to 55× and 2.3× for 98% and 60% cache hit rate respectively, with almost no modification to the original memcached server running on the same machine.

Mark Silberstein is an Assistant Professor at the department of Electrical Engineering, Technion - Israel Institute of Technology. Mark is interested in accelerator-rich systems and OS abstractions and services for and *on* accelerators, with the ultimate goal to break out of the CPU-centric OS models (HotOS17). His works include GPUfs (ASPLOS13), GPUnet (OSDI14) and GPUrdma libraries for native file system, networking and RDMA support for GPU programs and application-managed virtual memory for GPUs (ISCA16) and SGX enclaves (EuroSYS17)