25,661 research outputs found
The Automated Instrumentation and Monitoring System (AIMS) reference manual
Whether a researcher is designing the 'next parallel programming paradigm,' another 'scalable multiprocessor' or investigating resource allocation algorithms for multiprocessors, a facility that enables parallel program execution to be captured and displayed is invaluable. Careful analysis of execution traces can help computer designers and software architects to uncover system behavior and to take advantage of specific application characteristics and hardware features. A software tool kit that facilitates performance evaluation of parallel applications on multiprocessors is described. The Automated Instrumentation and Monitoring System (AIMS) has four major software components: a source code instrumentor which automatically inserts active event recorders into the program's source code before compilation; a run time performance-monitoring library, which collects performance data; a trace file animation and analysis tool kit which reconstructs program execution from the trace file; and a trace post-processor which compensate for data collection overhead. Besides being used as prototype for developing new techniques for instrumenting, monitoring, and visualizing parallel program execution, AIMS is also being incorporated into the run-time environments of various hardware test beds to evaluate their impact on user productivity. Currently, AIMS instrumentors accept FORTRAN and C parallel programs written for Intel's NX operating system on the iPSC family of multi computers. A run-time performance-monitoring library for the iPSC/860 is included in this release. We plan to release monitors for other platforms (such as PVM and TMC's CM-5) in the near future. Performance data collected can be graphically displayed on workstations (e.g. Sun Sparc and SGI) supporting X-Windows (in particular, Xl IR5, Motif 1.1.3)
Distortion-Memory Tradeoffs in Cache-Aided Wireless Video Delivery
Mobile network operators are considering caching as one of the strategies to
keep up with the increasing demand for high-definition wireless video
streaming. By prefetching popular content into memory at wireless access points
or end user devices, requests can be served locally, relieving strain on
expensive backhaul. In addition, using network coding allows the simultaneous
serving of distinct cache misses via common coded multicast transmissions,
resulting in significantly larger load reductions compared to those achieved
with conventional delivery schemes. However, prior work does not exploit the
properties of video and simply treats content as fixed-size files that users
would like to fully download. Our work is motivated by the fact that video can
be coded in a scalable fashion and that the decoded video quality depends on
the number of layers a user is able to receive. Using a Gaussian source model,
caching and coded delivery methods are designed to minimize the squared error
distortion at end user devices. Our work is general enough to consider
heterogeneous cache sizes and video popularity distributions.Comment: To appear in Allerton 2015 Proceedings of the 53rd annual Allerton
conference on Communication, control, and computin
On Optimal and Fair Service Allocation in Mobile Cloud Computing
This paper studies the optimal and fair service allocation for a variety of
mobile applications (single or group and collaborative mobile applications) in
mobile cloud computing. We exploit the observation that using tiered clouds,
i.e. clouds at multiple levels (local and public) can increase the performance
and scalability of mobile applications. We proposed a novel framework to model
mobile applications as a location-time workflows (LTW) of tasks; here users
mobility patterns are translated to mobile service usage patterns. We show that
an optimal mapping of LTWs to tiered cloud resources considering multiple QoS
goals such application delay, device power consumption and user cost/price is
an NP-hard problem for both single and group-based applications. We propose an
efficient heuristic algorithm called MuSIC that is able to perform well (73% of
optimal, 30% better than simple strategies), and scale well to a large number
of users while ensuring high mobile application QoS. We evaluate MuSIC and the
2-tier mobile cloud approach via implementation (on real world clouds) and
extensive simulations using rich mobile applications like intensive signal
processing, video streaming and multimedia file sharing applications. Our
experimental and simulation results indicate that MuSIC supports scalable
operation (100+ concurrent users executing complex workflows) while improving
QoS. We observe about 25% lower delays and power (under fixed price
constraints) and about 35% decrease in price (considering fixed delay) in
comparison to only using the public cloud. Our studies also show that MuSIC
performs quite well under different mobility patterns, e.g. random waypoint and
Manhattan models
jsPhyloSVG: A Javascript Library for Visualizing Interactive and Vector-Based Phylogenetic Trees on the Web
BackgroundMany software packages have been developed to address the need for generating phylogenetic trees intended for print. With an increased use of the web to disseminate scientific literature, there is a need for phylogenetic trees to be viewable across many types of devices and feature some of the interactive elements that are integral to the browsing experience. We propose a novel approach for publishing interactive phylogenetic trees.
Methods/Principal Findings We present a javascript library, jsPhyloSVG, which facilitates constructing interactive phylogenetic trees from raw Newick or phyloXML formats directly within the browser in Scalable Vector Graphics (SVG) format. It is designed to work across all major browsers and renders an alternative format for those browsers that do not support SVG. The library provides tools for building rectangular and circular phylograms with integrated charting. Interactive features may be integrated and made to respond to events such as clicks on any element of the tree, including labels.
Conclusions/Significance jsPhyloSVG is an open-source solution for rendering dynamic phylogenetic trees. It is capable of generating complex and interactive phylogenetic trees across all major browsers without the need for plugins. It is novel in supporting the ability to interpret the tree inference formats directly, exposing the underlying markup to data-mining services. The library source code, extensive documentation and live examples are freely accessible at www.jsphylosvg.com
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