Group Communication in Amoeba and its Applications

Unlike many other operating systems, Amoeba is a distributed operating system that provides group communication (i.e., one-to-many communication). We wil

State of Utah v. Albert Ross : Brief of Appellant

Appeal from the Judgment of the Second District Court for Weber County, State of Utah, the Honorable Ronald O. Hude, Judge presiding

Platform Dependent Verification: On Engineering Verification Tools for 21st Century

The paper overviews recent developments in platform-dependent explicit-state LTL model checking.Comment: In Proceedings PDMC 2011, arXiv:1111.006

The distributed ASCI supercomputer project

The Distributed ASCI Supercomputer (DAS) is a homogeneous wide-area distributed system consisting of four cluster computers at different locations. DAS has been used for research on communication software, parallel languages and programming systems, schedulers, parallel applications, and distributed applications. The paper gives a preview of the most interesting research results obtained so far in the DAS project

Engineering at Cornell

Official publication of Cornell University V.72 1980/8

Scaling VM Deployment in an Open Source Cloud Stack

Interactive High Performance Computing (HPC) workloads take advantage of the elasticity of clouds to scale their com-putation based on user demand by dynamically provision-ing virtual machines during their runtime. As in this case users require the results of their computation in a short time, the time to start the provisioned virtual instances becomes crucial. In this paper we study the deployment scalability of OpenNebula, an open-source cloud stack, with respect to these workloads. We describe our efforts for tuning the infrastructure’s and OpenNebula’s configuration as well as solving scalability issues in its implementation. After tun-ing both infrastructure and cloud stack, the simultaneous deployment of 512 VMs improved by 5.9 × on average, from 615 to 104 seconds, and after optimizing the implementa-tion, the deployment time improved by 12 × on average, to 53.54 seconds. These results suggest two possible improve-ment opportunities that can be useful for both cloud devel-opers and scientific users deploying a cloud stack to avoid such scalability issues in the future. First, the tuning process of a cloud stack can be improved through automatic tools that adapt the configuration to the workload and infrastruc-ture characteristics. Second, the code scalability issues can be avoided through a testing infrastructure that supports large scale emulation

Efficient Large-Scale Model Checking

Model checking is a popular technique to systematically and automatically verify system properties. Unfortunately, the well-known state explosion problem often limits the extent to which it can be applied to realistic specifications, due to the huge resulting memory requirements. Distributed memory model checkers exist, but have thus far only been evaluated on small-scale clusters, with mixed results. We examine one well-known distributed model checker in detail, and show how a number of additional optimizations in its runtime system enable it to efficiently check very demanding problem instances on a large-scale, multi-core compute cluster. We analyze the impact of the distributed algorithms employed, the problem instance characteristics and network overhead. Finally, we show that the model checker can even obtain good performance in a high-bandwidth computational grid environment

Music Filled Flask : Real Time Distributed Transcoding

Color poster with text, images, and charts.It is becoming more common to stream videos to cell phones and other devices that rely on cellular data connections. One reason people stream videos to their cellular devices is to listen to music that is on YouTube. This uses an unnecessarily large amount of mobile bandwidth, as the user only wants the audio but receives the video as well. To minimize the cost of streaming videos to mobile devices for the purpose of listening to music, the purpose of this study was to develop a web service that converts a user-created playlist of YouTube videos into an audio stream.University of Wisconsin--Eau Claire Office of Research and Sponsored Programs