Abel Gordon

ELI: bare-metal performance for I/O virtualization

Direct device assignment enhances the performance of guest virtual machines by allowing them to communicate with I/O devices without host involvement. But even with device assignment, guests are still unable to approach bare-metal performance, because the host intercepts all interrupts, including those interrupts generated by assigned devices to signal to guests the completion of their I/O requests. The host involvement induces multiple unwarranted guest/host context switches, which significantly hamper the performance of I/O intensive workloads. To solve this problem, we present ELI (ExitLess Interrupts), a software-only approach for handling interrupts within guest virtual machines directly and securely. By removing the host from the interrupt handling path, ELI manages to improve the throughput and latency of unmodified, untrusted guests by 1.3x-1.6x, allowing them to reach 97%-100% of bare-metal performance even for the most demanding I/O-intensive workloads.

Applications Know Best: Performance-Driven Memory Overcommit with Ginkgo

Memory over commitment enables cloud providers to host more virtual machines on a single physical server, exploiting spare CPU and I/O capacity when physical memory becomes the bottleneck for virtual machine deployment. However, over commiting memory can also cause noticeable application performance degradation. We present Ginkgo, a policy framework for over omitting memory in an informed and automated fashion. By directly correlating application-level performance to memory, Ginkgo automates the redistribution of scarce memory across all virtual machines, satisfying performance and capacity constraints. Ginkgo also achieves memory gains for traditionally fixed-size Java applications by coordinating the redistribution of available memory with the activities of the Java Virtual Machine heap. When compared to a non-over commited system, Ginkgo runs the Day Trader 2.0 and SPEC Web 2009 benchmarks with the same number of virtual machines while saving up to 73% (50% omitting free space) of a physical servers memory while keeping application performance degradation within 7%.

Towards exitless and efficient paravirtual I/O

Virtualization is a prominent technology used in data centers around the world. While many kinds of workloads can run at near-native performance even when virtualized, I/O intensive workloads still suffer from high overhead precluding the use of virtualization in many applications. In this paper we tackle the problem of improving the performance of paravirtual I/O. We propose an exitless paravirtual I/O model, under which guests and the hypervisor, running on distinct cores, exchange exitless notifications instead of costly exit-based notifications. Our initial proof of concept improved throughput by 45% and latency by 25μsec compared to a traditional network paravirtual I/O model. We show that a single hypervisor I/O core can become saturated when serving multiple I/O intensive guests, and further research is required to improve scalability in this scenario.

Bare-metal performance for virtual machines with exitless interrupts

Direct device assignment enhances the performance of guest virtual machines by allowing them to communicate with I/O devices without host involvement. But even with device assignment, guests are still unable to approach bare-metal performance, because the host intercepts all interrupts, including those generated by assigned devices to signal to guests the completion of their I/O requests. The host involvement induces multiple unwarranted guest/host context switches, which significantly hamper the performance of I/O intensive workloads. To solve this problem, we present ExitLess Interrupts (ELI), a software-only approach for handling interrupts within guest virtual machines directly and securely. By removing the host from the interrupt handling path, ELI improves the throughput and latency of unmodified, untrusted guests by 1.3×–1.6×, allowing them to reach 97–100% of bare-metal performance even for the most demanding I/O-intensive workloads.

IO Core Manager for Virtual Environments

Para-virtualization is the leading approach in IO device virtualization. It allows the hypervisor to interpose on and inspect a virtual machines I/O traffic at run-time. Examples of such interfaces are KVMs virtio [6] and VMWares VMXNET [7]. Current implementations of virtual I/O in the hypervisor have been shown to have performance and scalability limitations [2, 3, 5]. The overhead incurred during interposition arises from two main sources: VM exits and thread scheduling. VM exits are caused when the virtual machine requires some intervention of the hypervisor in order to continue execution. VM exits are required to perform I/O tasks since the VM does not have direct access to I/O hardware [1]. The second source of overhead is the hypervisors thread scheduler, which is not aware of the type of work being performed by a particular thread. When executing I/O threads have work (i.e. I/O traffic to process), the scheduler schedules the thread without regard to the latency or throughput requirements of the virtual device. In workloads with a small amount of latency-sensitive traffic, the thread context switches can become prohibitively costly. The limitations can be somewhat mitigated by using the side-core [4] approach, which divides the system cores into two distinct sets: one for running VM guests, and the other dedicated to virtual I/O processing. However, the number of cores that should be assigned to each set is dependent on the constantly changing workload. For optimum performance, the resources must be allocated according to measurements taken at runtime. We present IOcm which is able to tune the system automatically for using the side-core approach. IOcm provides a better foundation for building practical systems using the side-core approach by improving its usability. IOcm includes mechanisms that expose statistics and controls that allow for better management of the system. We show that IOcm is able to provide comparable performance to a side-core system tuned by an oracle.