Physical Sciences and Mathematics Commons^™

Unoapi: Balancing Performance, Portability, And Productivity (P3) In Hpc Education, Konstantin Laufer, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

oneAPI is a major initiative by Intel aimed at making it easier to program heterogeneous architectures used in high-performance computing using a unified application programming interface (API). While raising the abstraction level via a unified API represents a promising step for the current generation of students and practitioners to embrace high- performance computing, we argue that a curriculum of well- developed software engineering methods and well-crafted exem- plars will be necessary to ensure interest by this audience and those who teach them. We aim to bridge the gap by developing a curriculum—codenamed UnoAPI—that takes a more holistic approach by looking …

Automated Discovery Of Network Cameras In Heterogeneous Web Pages, Ryan Dailey, Aniesh Chawla, Andrew Liu, Sripath Mishra, Ling Zhang, Josh Majors, Yung-Hisang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Reduction in the cost of Network Cameras along with a rise in connectivity enables entities all around the world to deploy vast arrays of camera networks. Network cameras offer real-time visual data that can be used for studying traffic patterns, emergency response, security, and other applications. Although many sources of Network Camera data are available, collecting the data remains difficult due to variations in programming interface and website structures. Previous solutions rely on manually parsing the target website, taking many hours to complete. We create a general and automated solution for aggregating Network Camera data spread across thousands of uniquely …

Modular Neural Networks For Low-Power Image Classification On Embedded Devices, Abhinav Goel, Sara Aghajanzadeh, Caleb Tung, Shuo-Han Chen, George K. Thiruvathukal, Yung-Hisang Lu

Computer Science: Faculty Publications and Other Works

Embedded devices are generally small, battery-powered computers with limited hardware resources. It is difficult to run deep neural networks (DNNs) on these devices, because DNNs perform millions of operations and consume significant amounts of energy. Prior research has shown that a considerable number of a DNN’s memory accesses and computation are redundant when performing tasks like image classification. To reduce this redundancy and thereby reduce the energy consumption of DNNs, we introduce the Modular Neural Network Tree architecture. Instead of using one large DNN for the classifier, this architecture uses multiple smaller DNNs (called modules) to progressively classify images …

Cloud Resource Optimization For Processing Multiple Streams Of Visual Data, Zohar Kapach, Andrew Ulmer, Daniel Merrick, Arshad Alikhan, Yung-Hsiang Lu, Anup Mohan, Ahmed S. Kaseb, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Hundreds of millions of network cameras have been installed throughout the world. Each is capable of providing a vast amount of real-time data. Analyzing the massive data generated by these cameras requires significant computational resources and the demands may vary over time. Cloud computing shows the most promise to provide the needed resources on demand. In this article, we investigate how to allocate cloud resources when analyzing real-time data streams from network cameras. A resource manager considers many factors that affect its decisions, including the types of analysis, the number of data streams, and the locations of the cameras. The …

Cross-Referencing Social Media And Public Surveillance Camera Data For Disaster Response, Chittayong Surakitbanharn,, Calvin Yau, Guizhen Wang, Aniesh Chawla, Yinuo Pan, Zhaoya Sun, Sam Yellin, David Ebert, Yung-Hsiang Lu, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Physical media (like surveillance cameras) and social media (like Instagram and Twitter) may both be useful in attaining on-the-ground information during an emergency or disaster situation. However, the intersection and reliability of both surveillance cameras and social media during a natural disaster are not fully understood. To address this gap, we tested whether social media is of utility when physical surveillance cameras went off-line during Hurricane Irma in 2017. Specifically, we collected and compared geo-tagged Instagram and Twitter posts in the state of Florida during times and in areas where public surveillance cameras went off-line. We report social media content …

Spring­11: Pdc In Cs1/2 And A Mobile/Cloud Intermediate Mobile/Cloud Intermediate Software Design Course, Joseph P. Kaylor, Konstantin Läufer, Chandra N. Sekharan, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

Recent changes in the environment of Loyola University Chicago’s Department of Computer Science include a better differentiation of our four undergraduate majors, growing interest in computing among science majors, and an increased demand for graduates with mobile and cloud skills. In our continued effort to incorporate parallel and distributed computing topics into the undergraduate curriculum, we are focusing on these three existing courses:

CS1: In response to a request from the physics department, we started to offer a CS1 section aimed at majors in physics and other hard sciences this spring semester. This section includes some material on numerical methods …

Network Technologies Used To Aggregate Environmental Data, Paul Stasiuk, Konstantin Läufer, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

The goal of the Loyola Weather Service (lws) project is to design and build a system of functioning environmental monitoring widgets that can intelligently and autonomously control the environment around them based on set thresholds and triggers. The widgets will also have the ability to aggregate their data and easily display this data in various ways: through a user interface in the room that the widget is placed, via a web application, and programmatically via a RESTful web service.

Building Capable, Energy-Efficient, Flexible Visualization And Sensing Clusters From Commodity Tablets, Thomas Delgado Dias, Xian Yan, Konstantin Läufer, George K. Thiruvathukal

Computer Science: Faculty Publications and Other Works

We explore the application of clusters of commodity tablet devices to problems spanning a “trilogy” of concerns: visualization, sensing, and computation. We conjecture that such clusters provide a low-cost, energy-efficient, flexible, and ultimately effective platform to tackle a wide range of problems within this trilogy. This is a work in progress, and we now elaborate our position and give a preliminary status report.

A wide range of Android tablet devices are available in terms of price and capabilities. “You get what you pay for” w.r.t. display resolution, sensors, and chipset---corresponding to the trilogy. $200 gets one a 1280x800-pixel touch display, …

Technologies For Ubiquitous Supercomputing: A Java Interface To The Nexus Communication System, Ian Foster, George K. Thiruvathukal, Steven Tuecke

Computer Science: Faculty Publications and Other Works

We use the term ubiquitous supercomputing to refer to systems that integrate low- and mid-range computing systems, advanced networks and remote high-end computers with the goal of enhancing the computational power accessible from local environments. Such systems promise to enable new applications in areas as diverse as smart instruments and collaborative environments. However, they also demand tools for transporting code between computers and for establishing flexible, dynamic communication structures. In this article, we propose that these requirements be satisfied by introducing Java classes that implement the global pointer and remote service request mechanisms defined by a communication library called Nexus. …

Randomized Routing On Fat-Trees, Ronald I. Greenberg

Computer Science: Faculty Publications and Other Works

Fat-trees are a class of routing networks for hardware-efficient parallel computation. This paper presents a randomized algorithm for routing messages on a fat-tree. The quality of the algorithm is measured in terms of the load factor of a set of messages to be routed, which is a lower bound on the time required to deliver the messages. We show that if a set of messages has load factor lambda on a fat-tree with n processors, the number of delivery cycles (routing attempts) that the algorithm requires is O(lambda+lgnlglgn) with probability 1-O(1/ …