Continuously running systems require kernel software updates applied to them without downtime. Facilitating fast reboots, or delaying an update may not be a suitable solution in many environments, especially in pay-per-use high-performance computing clusters and mission critical systems. Such systems will not reap the benefits of new kernel features, and will continue to operate with kernel security holes unpatched, at least until the next scheduled maintenance downtime. To address these problems we developed an on-the-fly kernel updating system that enables commodity operating systems to gain adaptive and mutative capabilities without kernel recompilation or reboot. Our system, DynAMOS, employs a novel and efficient dynamic code instrumentation technique termed adaptive function cloning. Execution flow can be switched adaptively among multiple editions of functions, possibly concurrently running. This approach becomes the foundation for dynamic replacement of non-quiescent kernel subsystems when the timeliness of an update depends on synchronization of multiple kernel paths. We illustrate our experience by dynamically updating core subsystems of the Linux kernel.

High-performance computing clusters running long-lived tasks currently cannot have kernel software updates applied to them without causing system downtime. These clusters miss opportunities for increased performance via specialized kernel support, cannot benefit from new kernel features, and continue to operate with kernel security holes unpatched, at least until the next scheduled maintenance date. We developed a system enabling dynamic kernel updates in parallel computing clusters to address these problems. Our system, DynAMOS, is founded on execution flow high-jacking through function cloning. It enables commodity operating systems popularly used in clusters gain adaptive and mutative capabilities. To demonstrate the efficacy of our system, we illustrate our experience in dynamically updating and extending a Linux cluster. We introduce adaptive memory paging for efficient gang-scheduling; extend the kernel's process scheduler to support unobtrusive fine-grain cycle stealing, apply public security fixes, and inject performance monitoring functionality to a selection of kernel functions. Our benchmarks show that the overhead imposed by DynAMOS is mostly in the range of 1-8% for common Linux kernel functions