81,031 research outputs found
Pervasive Parallel And Distributed Computing In A Liberal Arts College Curriculum
We present a model for incorporating parallel and distributed computing (PDC) throughout an undergraduate CS curriculum. Our curriculum is designed to introduce students early to parallel and distributed computing topics and to expose students to these topics repeatedly in the context of a wide variety of CS courses. The key to our approach is the development of a required intermediate-level course that serves as a introduction to computer systems and parallel computing. It serves as a requirement for every CS major and minor and is a prerequisite to upper-level courses that expand on parallel and distributed computing topics in different contexts. With the addition of this new course, we are able to easily make room in upper-level courses to add and expand parallel and distributed computing topics. The goal of our curricular design is to ensure that every graduating CS major has exposure to parallel and distributed computing, with both a breadth and depth of coverage. Our curriculum is particularly designed for the constraints of a small liberal arts college, however, much of its ideas and its design are applicable to any undergraduate CS curriculum
Teaching Parallel Programming Using Java
This paper presents an overview of the "Applied Parallel Computing" course
taught to final year Software Engineering undergraduate students in Spring 2014
at NUST, Pakistan. The main objective of the course was to introduce practical
parallel programming tools and techniques for shared and distributed memory
concurrent systems. A unique aspect of the course was that Java was used as the
principle programming language. The course was divided into three sections. The
first section covered parallel programming techniques for shared memory systems
that include multicore and Symmetric Multi-Processor (SMP) systems. In this
section, Java threads was taught as a viable programming API for such systems.
The second section was dedicated to parallel programming tools meant for
distributed memory systems including clusters and network of computers. We used
MPJ Express-a Java MPI library-for conducting programming assignments and lab
work for this section. The third and the final section covered advanced topics
including the MapReduce programming model using Hadoop and the General Purpose
Computing on Graphics Processing Units (GPGPU).Comment: 8 Pages, 6 figures, MPJ Express, MPI Java, Teaching Parallel
Programmin
Incorporating the NSF/TCPP Curriculum Recommendations in a Liberal Arts Setting
This paper examines the integration of the NSF/TCPP Core Curriculum Recommendations in a liberal arts undergraduate setting. We examine how parallel and distributed computing concepts can be incorporated across the breadth of the undergraduate curriculum. As a model of such an integration, changes are proposed to Data Structures and Design and Analysis of Algorithms. These changes were implemented in Design and Analysis of Algorithms and the results were compared to previous iterations of that course taught by the same instructor. The student feedback received shows that the introduction of these topics made the course more engaging and conveyed an adequate introduction to this material
Notes on Randomized Algorithms
Lecture notes for the Yale Computer Science course CPSC 469/569 Randomized
Algorithms. Suitable for use as a supplementary text for an introductory
graduate or advanced undergraduate course on randomized algorithms. Discusses
tools from probability theory, including random variables and expectations,
union bound arguments, concentration bounds, applications of martingales and
Markov chains, and the Lov\'asz Local Lemma. Algorithmic topics include
analysis of classic randomized algorithms such as Quicksort and Hoare's FIND,
randomized tree data structures, hashing, Markov chain Monte Carlo sampling,
randomized approximate counting, derandomization, quantum computing, and some
examples of randomized distributed algorithms
Developing High Performance Computing Resources for Teaching Cluster and Grid Computing courses
High-Performance Computing (HPC) and the ability to process large amounts of data are of
paramount importance for UK business and economy as outlined by Rt Hon David Willetts
MP at the HPC and Big Data conference in February 2014. However there is a shortage of
skills and available training in HPC to prepare and expand the workforce for the HPC and
Big Data research and development. Currently, HPC skills are acquired mainly by students
and staff taking part in HPC-related research projects, MSc courses, and at the dedicated
training centres such as Edinburgh University’s EPCC. There are few UK universities teaching
the HPC, Clusters and Grid Computing courses at the undergraduate level. To address the
issue of skills shortages in the HPC it is essential to provide teaching and training as part of
both postgraduate and undergraduate courses. The design and development of such courses is
challenging since the technologies and software in the fields of large scale distributed systems
such as Cluster, Cloud and Grid computing are undergoing continuous change. The students
completing the HPC courses should be proficient in these evolving technologies and equipped
with practical and theoretical skills for future jobs in this fast developing area.
In this paper we present our experience in developing the HPC, Cluster and Grid modules
including a review of existing HPC courses offered at the UK universities. The topics covered in
the modules are described, as well as the coursework projects based on practical laboratory work.
We conclude with an evaluation based on our experience over the last ten years in developing
and delivering the HPC modules on the undergraduate courses, with suggestions for future work
On the Prevalence and Nature of Computational Instruction in Undergraduate Physics Programs across the United States
A national survey of physics faculty was conducted to investigate the
prevalence and nature of computational instruction in physics courses across
the United States. 1246 faculty from 357 unique institutions responded to the
survey. The results suggest that more faculty have some form of computational
teaching experience than a decade ago, but it appears that this experience does
not necessarily translate to computational instruction in undergraduate
students' formal course work. Further, we find that formal programs in
computational physics are absent from most departments. A majority of faculty
do report using computation on homework and in projects, but few report using
computation with interactive engagement methods in the classroom or on exams.
Specific factors that underlie these results are the subject of future work,
but we do find that there is a variation on the reported experience with
computation and the highest degree that students can earn at the surveyed
institutions.Comment: 8 pages, 6 figure
TLAD 2010 Proceedings:8th international workshop on teaching, learning and assesment of databases (TLAD)
This is the eighth in the series of highly successful international workshops on the Teaching, Learning and Assessment of Databases (TLAD 2010), which once again is held as a workshop of BNCOD 2010 - the 27th International Information Systems Conference. TLAD 2010 is held on the 28th June at the beautiful Dudhope Castle at the Abertay University, just before BNCOD, and hopes to be just as successful as its predecessors.The teaching of databases is central to all Computing Science, Software Engineering, Information Systems and Information Technology courses, and this year, the workshop aims to continue the tradition of bringing together both database teachers and researchers, in order to share good learning, teaching and assessment practice and experience, and further the growing community amongst database academics. As well as attracting academics from the UK community, the workshop has also been successful in attracting academics from the wider international community, through serving on the programme committee, and attending and presenting papers.This year, the workshop includes an invited talk given by Richard Cooper (of the University of Glasgow) who will present a discussion and some results from the Database Disciplinary Commons which was held in the UK over the academic year. Due to the healthy number of high quality submissions this year, the workshop will also present seven peer reviewed papers, and six refereed poster papers. Of the seven presented papers, three will be presented as full papers and four as short papers. These papers and posters cover a number of themes, including: approaches to teaching databases, e.g. group centered and problem based learning; use of novel case studies, e.g. forensics and XML data; techniques and approaches for improving teaching and student learning processes; assessment techniques, e.g. peer review; methods for improving students abilities to develop database queries and develop E-R diagrams; and e-learning platforms for supporting teaching and learning
Latin American perspectives to internationalize undergraduate information technology education
The computing education community expects modern curricular guidelines for information technology (IT) undergraduate degree programs by 2017. The authors of this work focus on eliciting and analyzing Latin American academic and industry perspectives on IT undergraduate education. The objective is to ensure that the IT curricular framework in the IT2017 report articulates the relationship between academic preparation and the work environment of IT graduates in light of current technological and educational trends in Latin America and elsewhere. Activities focus on soliciting and analyzing survey data collected from institutions and consortia in IT education and IT professional and educational societies in Latin America; these activities also include garnering the expertise of the authors. Findings show that IT degree programs are making progress in bridging the academic-industry gap, but more work remains
Curriculum Guidelines for Undergraduate Programs in Data Science
The Park City Math Institute (PCMI) 2016 Summer Undergraduate Faculty Program
met for the purpose of composing guidelines for undergraduate programs in Data
Science. The group consisted of 25 undergraduate faculty from a variety of
institutions in the U.S., primarily from the disciplines of mathematics,
statistics and computer science. These guidelines are meant to provide some
structure for institutions planning for or revising a major in Data Science
Recommended from our members
The dynamics of computerization in a social science research team : a case study of infrastructure, strategies, and skills
This paper examines the dynamics of Computerization in a PC-oriented research group through a case study. The time and skill in integrating computing into the labor processes of research are often significant "hidden costs" of computerization. Computing infrastructure plays a key role in reducing these costs may be enhanced by careful organization. We illustrate computerization strategies that we have found to be productive and unproductive. Appropriate computerization strategies depend as much on the structuring of resources and interests in the larger social setting, as on a technical characterization of tasks
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