Abstract

Graphical processing units (GPUs) are critical to high-quality visualization in many application domains. Running such applications in virtual machine monitor (VMM) environments is difficult for a number of reasons, all relating to the fact that the GPU hardware interface is proprietary rather than standardized. This paper describes the design, implementation, and evaluation of VMGL, a VMM-independent, GPU-independent, cross-platform solution to this problem. VMGL virtualizes at the OpenGL software interface, recognizing its widespread use in graphics-intensive applications. Our experiments confirm excellent rendering performance with VMGL, coming within 14 % or better of native hardware accelerated performance measured in frames per second. This is two orders of magnitude better than software rendering, which is the commonly available alternative today for graphics-intensive applications running in virtualized environments. Our results confirm VMGL’s portability across VMware Workstation and Xen (on VT and non-VT hardware), and across Linux (with and without paravirtualization), FreeBSD, and Solaris. Our results also show that the resource demands of VMGL align well with the emerging trend of multi-core processors. 1

VMM-independent graphics acceleration

This paper describes VMGL, a cross-platform OpenGL virtualization solution that is both virtual machine monitor (VMM) and graphics processing unit (GPU) independent. VMGL allows applications executing within virtual machines (VMs) to leverage hardware rendering acceleration, thus solving a problem that has limited virtualization of a growing class of graphics-intensive applications. VMGL also provides applications running within VMs with suspend and resume capabilities across GPUs from different vendors. Our experimental results from a number of graphics-intensive applications show that VMGL provides excellent rendering performance, coming within 14 % or better of native graphics hardware acceleration. Further, VMGL’s performance is two orders of magnitude better than that of software rendering, the commonly available alternative today for graphics-intensive applications running in virtualized environments. Our results confirm VMGL’s portability across VMware Workstation and Xen (on VT and non-VT hardware), and across Linux (with and without paravirtualization), FreeBSD, and Solaris. Finally, the resource demands of VMGL align well with the emerging trend of multi-core processors. Categories and Subject Descriptors I.3.4 [Computer Graphics]

Patagonix: Dynamically Neutralizing Malware with a Hypervisor

In most operating systems widely in use today, it is possible for malicious software (malware) that has gained administrator privileges on the system to arbitrarily modify the kernel. Recently, Windows-base

Self-service cloud computing

Modern cloud computing infrastructures use virtual machine monitors (VMMs) that often include a large and complex administrative domain with privileges to inspect client VM state. Attacks against or misuse of the administrative domain can compromise client security and privacy. Moreover, these VMMs provide clients inflexible control over their own VMs, as a result of which clients have to rely on the cloud provider to deploy useful services, such as VM introspection-based security tools. We introduce a new self-service cloud (SSC) computing model that addresses these two shortcomings. SSC splits administrative privileges between a system-wide domain and per-client administrative domains. Each client can manage and perform privileged system tasks on its own VMs, thereby providing flexibility. The system-wide administrative domain cannot inspect the code, data or computation of client VMs, thereby ensuring security and privacy. SSC also allows providers and clients to establish mutually trusted services that can check regulatory compliance while respecting client privacy. We have implemented SSC by modifying the Xen hypervisor. We demonstrate its utility by building user domains to perform privileged tasks such as memory introspection, storage intrusion detection, and anomaly detection

Adding the easy button to the cloud with SnowFlock and MPI

Cloud computing promises to provide researchers with the abil-ity to perform parallel computations using large pools of virtual machines (VMs), without facing the burden of owning or main-taining physical infrastructure. However, with ease of access to hundreds of VMs, comes also an increased management burden. Cloud users today must manually instantiate, configure and main-tain the virtual hosts in their cluster. They must learn new cloud APIs that are not germane to the problem of parallel process-ing. Those APIs usually take several minutes to perform their VM-management tasks, forcing users to keep VMs idling and pay for unused processing time, rather than shut VMs down and power them on as needed. Furthermore, users must still configure their cluster management framework to launch their parallel jobs. In this paper we show that all this management pain is unnec-essary. We show how to combine a cloud API – SnowFlock – and a parallel processing framework – MPI – to truly realize the potential of the cloud. SnowFlock allows users to fork VMs as if they were processes, occupying in sub-second time multiple physical hosts. We exploit the synergy between this paradigm and MPI’s job man-agement to completely hide all details of cloud management from the user. Maintaining a single VM and starting unmodified appli-cations with familiar MPI commands, a user can instantaneously leverage hundreds of processors to perform a parallel computa-tion. Besides making use of cloud resources trivial, we also elim-inate the cost of idling – VMs exist only for as long as they are involved in computation. 1

Low-Bandwidth VM Migration via Opportunistic Replay

Virtual machine (VM) migration has been proposed as a building block for mobile computing. An important challenge for VM migration is to optimize the transfer of large amounts of disk and memory state. We propose a solution based on the opportunistic replay of user interactions with applications at the GUI level. Whereas this approach results in very small replay logs that economize network utilization, replay of user interactions on a VM at the migration target site can result in divergent VM state. Cryptographic hashing techniques are used to identify and transmit only the differences. We discuss the implementation challenges of this approach, and present encouraging results from an early prototype that show savings of up to 80.5 % of bytes transferred

VMM-independent graphics acceleration

or Carnegie Mellon University. All unidentified trademarks mentioned in the paper are properties of their respectiv