2 research outputs found
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Shadow kernels: A general mechanism for kernel specialization in existing operating systems
Existing operating systems share a common kernel text section amongst all processes. It is not possible to perform kernel specialization or tuning such that different applications execute text optimized for their kernel use despite the benefits of kernel specialization for performance guided optimization, exokernels, kernel fastpaths, and cheaper hardware access. Current specialization primitives involve system wide changes to kernel text, which can have adverse effects on other processes sharing the kernel due to the global side-effects. We present shadow kernels: a primitive that allows multiple kernel text sections to coexist in a contemporary operating system. By remapping kernel virtual memory on a context-switch, or for individual system calls, we specialize the kernel on a fine-grained basis. Our implementation of shadow kernels uses the Xen hypervisor so can be applied to any operating system that runs on Xen.This work was principally supported by internal funds from the Computer Laboratory at the University of Cambridge; and also by the Engineering and Physical Sciences Research Council [grant number EP/K503009/1].This is the final version of the article. It first appeared from ACM via http://dx.doi.org/10.1145/2797022.279702
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Soroban: Attributing latency in virtualized environments
Applications running in the cloud have highly-variable response times due to the lack of perfect performance isolation from other services served by common infrastructure. In particular, response latency when executing on a loaded hypervisor or in a container is substantially higher than uncontested bare-metal performance. Whilst efforts to increase performance isolation continue, we present Soroban, a framework for attributing latency to either the cloud provider or their customer. Soroban allows cloud providers to instrument commonly used programs, such as a web server to determine, for each request, how much of the latency is due to the cloud provider, or the consumer. We apply Soroban to a HTTP server and show that it identifies when the cause of latency is due to a provider-induced activity, such as underprovisioning a host, or due to the software run by the customer.This is the author accepted manuscript. The final version is available from USENIX. via https://www.usenix.org/conference/hotcloud15/workshop-program/presentation/sne