On-the-fly kernel updates for high-performance computing clusters

Abstract

High-performance computing clusters running long-lived tasks currently cannot have kernel software updates applied to them without causing system down-time. 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. © 2006 IEEE.