GPU-based First Aid for System Faults

It is difficult to completely avoid system failures in recent large-scale and complex systems. Therefore, it is important to detect system faults rapidly and accurately and recover from them. Fault recovery is categorized into external one from remote hosts and internal one with processes or the operating system (OS) inside a target system. However, both methods are subject to system faults. If fault recovery fails, a hardware reset is required and can lead to losing system data and states. This paper proposes GPUfas for recovering from system faults by indirectly controlling OS behavior from a GPU, which is not easily affected by system faults. GPUfas attempts fault recovery by rewriting OS data in main memory and leveraging the capabilities of the OS itself. For example, it can mimic signal sending and process scheduling to force termination of the processes that consume excessive resources. It can also mimic unlocking to recover from some kind of deadlock. We have implemented GPUfas using the Linux kernel, CUDA, and LLVM to enable a GPU to rewrite OS data transparently. Then, we confirmed the effectiveness and efficiency of fault recovery by GPUfas.