NDLI: Shoot4U: Using VMM Assists to Optimize TLB Operations on Preempted vCPUs

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Virtualizing the Edge of the Cloud: the New Frontier

Building a KVM-based Hypervisor for a Heterogeneous System Architecture Compliant System

On Selecting the Right Optimizations for Virtual Machine Migration

Enabling Efficient Hypervisor-as-a-Service Clouds with Eemeral Virtualization

Next Generation Virtual Memory Management

Exploiting FIFO Scheduler to Improve Parallel Garbage Collection Performance

The nom Profit-Maximizing Operating System

Sweet Spots and Limits for Virtualization

Shoot4U: Using VMM Assists to Optimize TLB Operations on Preempted vCPUs

Urgent Virtual Machine Eviction with Enlightened Post-Copy

Abstractions for Practical Virtual Machine Replay

Performance Analysis and Optimization of Full Garbage Collection in Memory-hungry Environments

Enabling Hybrid Parallel Runtimes Through Kernel and Virtualization Support

Performance Implications of Extended Page Tables on Virtualized x86 Processors

SRVM: Hypervisor Support for Live Migration with Passthrough SR-IOV Network Devices

Leveraging Managed Runtime Systems to Build, Analyze, and Optimize Memory Graphs

Shoot4U: Using VMM Assists to Optimize TLB Operations on Preempted vCPUs

Content Provider	ACM Digital Library
Author	Ouyang, Jiannan Lange, John R. Zheng, Haoqiang
Abstract	Virtual Machine based approaches to workload consolidation, as seen in IaaS cloud as well as datacenter platforms, have long had to contend with performance degradation caused by synchronization primitives inside the guest environments. These primitives can be affected by virtual CPU preemptions by the host scheduler that can introduce delays that are orders of magnitude longer than those primitives were designed for. While a significant amount of work has focused on the behavior of spinlock primitives as a source of these performance issues, spinlocks do not represent the entirety of synchronization mechanisms that are susceptible to scheduling issues when running in a virtualized environment. In this paper we address the virtualized performance issues introduced by TLB shootdown operations. Our profiling study, based on the PARSEC benchmark suite, has shown that up to 64% of a VM's CPU time can be spent on TLB shootdown operations under certain workloads. In order to address this problem, we present a paravirtual TLB shootdown scheme named Shoot4U. Shoot4U completely eliminates TLB shootdown preemptions by invalidating guest TLB entries from the VMM and allowing guest TLB shootdown operations to complete without waiting for remote virtual CPUs to be scheduled. Our performance evaluation using the PARSEC benchmark suite demonstrates that Shoot4U can reduce benchmark runtime by up to 85% compared an unmodified Linux kernel, and up to 44% over a state-of-the-art paravirtual TLB shootdown scheme.
Starting Page	17
Ending Page	23
Page Count	7
File Format	PDF
ISBN	9781450339476
DOI	10.1145/2892242.2892245
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-03-25
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Preemption Tlb shootdown Virtualization
Content Type	Text
Resource Type	Article

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