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检索条件"主题词=Parallel and Distributed Computing"

共 270 条记录，以下是11-20 订阅

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Data-Intensive computing Modules for Teaching parallel and distributed computing

Data-Intensive Computing Modules for Teaching Parallel and D...

引用

35th IEEE International parallel and distributed Processing Symposium (IPDPS)

作者： Gowanlock, Michael Gallet, Benoit No Arizona Univ Sch Informat Comp & Cyber Syst Flagstaff AZ 86011 USA

ISBN: (纸本)9781665435772

parallel and distributed computing (PDC) has found a broad audience that exceeds the traditional fields of computer science. This is largely due to the increasing computational demands of many engineering and domain science research objectives. Thus, there is a demonstrated need to train students with and without computer science backgrounds in core PDC concepts. Given the rise of data science and other data-enabled computational fields, we propose several data-intensive pedagogic modules that are used to teach PDC using message-passing programming with the Message Passing Interface (MPI). These modules employ activities that are common in database systems and scientific workflows that are likely to be employed by domain scientists. Our hypothesis is that using application-driven pedagogic materials facilitates student learning by providing the context needed to fully appreciate the goals of the activities. We evaluated the efficacy of using the data-intensive pedagogic modules to teach core PDC concepts using a sample of graduate students enrolled in a high performance computing course at Northern Arizona University. In the sample, only 30% of students have a traditional computer science background. We found that the hands-on application-driven approach was generally successful at helping students learn core PDC concepts.

关键词： Computer Science Education Data-Intensive computing High Performance computing parallel and distributed computing

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I CAN HAS SUPERCOMPUTER? A Novel Approach to Teaching parallel and distributed computing Concepts Using a Meme-Based Programming Language 31

I CAN HAS SUPERCOMPUTER? A Novel Approach to Teaching Parall...

引用

31st IEEE International parallel and distributed Processing Symposium Workshops (IPDPS)

作者： Richie, David A. Ross, James A. Brown Deer Technol Forest Hill MD 21050 USA US Army Res Lab Aberdeen Proving Ground MD USA

ISBN: (纸本)9780769561493

A novel approach is presented to teach the parallel and distributed computing concepts of synchronization and remote memory access. The single program multiple data (SPMD) partitioned global address space (PGAS) model presented in this paper uses a procedural programming language appealing to undergraduate students. We propose that the amusing nature of the approach may engender creativity and interest using these concepts later in more sober environments. Specifically, we implement parallel extensions to LOLCODE within a source-to-source compiler sufficient for the development of parallel and distributed algorithms normally implemented using conventional high-performance computing languages and APIs.

关键词： component meme-based learning parallel and distributed computing

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NSF/IEEE-TCPP Curriculum Initiative on parallel and distributed computing - Status Report 18

NSF/IEEE-TCPP Curriculum Initiative on Parallel and Distribu...

引用

49th ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Prasad, Sushil K. Weems, Charles C. Dougherty, John P. Deb, Debzani Georgia State Univ 25 Pk PlSuite 717 Atlanta GA 30303 USA Univ Massachusetts Amherst MA 01003 USA Haverford Coll 370 Lancaster Ave Haverford PA 19041 USA Winston Salem State Univ 601 S Martin Luther King Jr Dr Winston Salem NC 27110 USA

No abstract available.

ISBN: (纸本)9781450351034

No abstract available.

关键词： parallel and distributed computing education curriculum guidelines status report

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NSF/IEEE-TCPP Curriculum on parallel and distributed computing for Undergraduates - Version II - Big Data, Energy, and distributed computing 2023

NSF/IEEE-TCPP Curriculum on Parallel and Distributed Computi...

引用

54th Annual ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE TS)

作者： Prasad, Sushil Weems, Charles Sussman, Alan Gupta, Anshul Estrada, Trilce Vaidyanathan, Ramachandran Ghafoor, Sheikh Kant, Krishna Stunkel, Craig Univ Texas San Antonio San Antonio TX 78249 USA Univ Massachusetts Amherst MA 01003 USA Univ Maryland College Pk MD 20742 USA IBM Res Yorktown Hts NY USA Univ New Mexico Albuquerque NM 87131 USA Louisiana State Univ Baton Rouge LA 70803 USA Tennessee Technol Univ Cookeville TN USA Temple Univ Philadelphia PA 19122 USA NVIDIA St Louis MO USA

ISBN: (纸本)9781450394338

This special session will report on the updated NSF/IEEE-TCPP Curriculum on parallel and distributed computing released in Nov 2020 by the Center for parallel and distributed computing Curriculum Development and Educational Resources (CDER). The purpose of the special session is to obtain SIGCSE community feedback on this curriculum in a highly interactive manner employing the hybrid modality and supported by a full-time CDER booth for the duration of SIGCSE. In this era of big data, cloud, and multi- and many-core systems, it is essential that the computer science (CS) and computer engineering (CE) graduates have basic skills in parallel and distributed computing (PDC). The topics are primarily organized into the areas of architecture, programming, and algorithms topics. A set of pervasive concepts that percolate across area boundaries are also identified. Version 1 of this curriculum was released in December 2012. That curriculum guideline has over 140 early adopter institutions worldwide and has been incorporated into the 2013 ACM/IEEE Computer Science curricula. This Version-II represents a major revision. The updates have focused on enhancing coverage related to the topical aspects of Big Data, Energy, and distributed computing. The session will also report on related CDER activities including a workshop series on a PDC institute conceptualization, developing a CE-oriented version of the curriculum, and identifying a minimal set of PDC topics aligned with ABET's exposure-level PDC requirements. The interested SIGCSE audience includes educators, authors, publishers, curriculum committee members, department chairs and administrators, professional societies, and the computing industry.

关键词： Education Undergraduate Curriculum parallel and distributed computing Bloom's Classification Learning Outcomes

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SCoPE@Scuola: (In)-formative Paths on Topics Related with High Performance, parallel and distributed computing 1

引用

23rd International Conference on parallel and distributed computing (Euro-Par)

作者： Barone, Giovanni Battista Boccia, Vania Bottalico, Davide Carracciuolo, Luisa Univ Naples Federico II Naples Italy Liceo Class & Sci R Cartesio Naples Italy Italian Natl Res Council Naples Italy

ISBN: (数字)9783319751788

ISBN: (纸本)9783319751788;9783319751771

The SCoPE@Scuola initiative was born with the aim to inspire curiosity in high school students about High Performance computing (HPC) and parallel and distributed computing (PDC). The HPC/PDC world could be an interesting matter for students because is a necessary tool to solve challenging problems in science and technology and it provides context where a plenty of knowledge acquired at school can find a real application. In fact, the themes related to HPC/PDC involve a large range of knowledge and skills: from mathematical modelling of problems to algorithm design, from software implementation to design and management of complex computer systems. The initiative, begun at the end of 2014, involved several schools in the Naples (Italy) district, and has also been used for work-based learning activities and projects aimed to avoid students "dropouts". The results collected during all the last years make us hopeful that such initiative could be useful both to increment students awareness about the utility in the real world of all the knowledge acquired at school and to help them in their future educational and/or working choices.

关键词： Education Scientific computing parallel and distributed computing

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A Model for Scientific Workflows with parallel and distributed computing

A Model for Scientific Workflows with Parallel and Distribut...

引用

作者： Luis Manuel da Costa Assuncao NOVA University of Lisbon

学位级别：博士

In the last decade we witnessed an immense evolution of the computing infrastructures in terms of processing, storage and communication. On one hand, developments in hard- ware architectures have made it possible to run multiple virtual machines on a single physical machine. On the other hand, the increase of the available network communica- tion bandwidth has enabled the widespread use of distributed computing infrastructures, for example based on clusters, grids and clouds. The above factors enabled diﬀerent scien- tific communities to aim for the development and implementation of complex scientific applications possibly involving large amounts of data. However, due to their structural complexity, these applications require decomposition models to allow multiple tasks running in parallel and distributed environments. The scientific workﬂow concept arises naturally as a way to model applications com- posed of multiple activities. In fact, in the past decades many initiatives have been undertaken to model application development using the workﬂow paradigm, both in the business and in scientific domains. However, despite such intensive eﬀorts, current scientific workﬂow systems and tools still have limitations, which pose difficulties to the development of emerging large-scale, distributed and dynamic applications. This dissertation proposes the AWARD model for scientific workﬂows with parallel and distributed computing. AWARD is an acronym for Autonomic Workﬂow Activities Reconfigurable and Dynamic. The AWARD model has the following main characteristics. It is based on a decentralized execution control model where multiple autonomic workﬂow activities interact by exchanging tokens through input and output ports. The activities can be executed separately in diverse computing environments, such as in a single computer or on multiple virtual machines running on distributed infrastructures, such as clusters and clouds. It provides basic workﬂow patterns for parallel and

关键词： Scientific workflows parallel and distributed computing Dynamic reconfig-uration

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Teaching parallel and distributed computing with MPI on Raspberry Pi Clusters 18

Teaching Parallel and Distributed Computing with MPI on Rasp...

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49th ACM SIGCSE Technical Symposium on Computer Science Education (SIGCSE)

作者： Brown, Richard Adams, Joel Matthews, Suzanne Shoop, Elizabeth St Olaf Coll Northfield MN 55057 USA Calvin Coll Grand Rapids MI 49506 USA USMA West Point NY USA Macalester Coll St Paul MN 55105 USA

ISBN: (纸本)9781450351034

CS2013 brings parallel and distributed computing (PDC) into the CS curricular mainstream. The Message Passing Interface (MPI) is a platform independent, industry-standard library for parallel and distributed computing. The MPI standard includes support for C, C++, and Fortran; third parties have created implementations for Python and Java. This hands-on workshop introduces MPI basics and applications in C/C++ using Raspberry Pi single-board computers, as an inexpensive and engaging hardware platform for studying PDC. The workshop includes: (i) personal experience with the Raspberry Pi (units provided) accessed via participant laptops (Windows, Mac, or Linux); (ii) assembly of Beowulf clusters of Raspberry Pis quickly in the classroom; (iii) self-paced hands-on experimentation with the working MPI programs; and (iv) a discussion of how such clusters can be used to engage students in and out of the classroom. Participants will experience how to teach distributed computing essentials with MPI by means of reusable, effective "parallel programming patterns," including single program multiple data (SPMD) execution, send-receive message passing, the master-worker, parallel loop, and other common patterns. Participants will then explore more in-depth "exemplar" applications, such as drug design and epidemiology. All materials including the Raspberry Pi software system setup from this workshop will be freely available from ***. No prior experience with MPI, PDC, or the Raspberry Pi is required. Windows, Mac, or Linux laptop required.

关键词： CSinparallel MPI distributed computing exemplars message passing parallel and distributed computing parallel design patterns

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OnRamp to parallel and distributed computing (Abstract Only) 16

OnRamp to Parallel and Distributed Computing (Abstract Only)

引用

Proceedings of the 47th ACM Technical Symposium on computing Science Education

作者： Samantha S. Foley Joshua Hursey Daniel Koepke Justin Ragatz Jason Regina University of Wisconsin-La Crosse La Crosse WI USA University of Wyoming Laramie WY USA

ISBN: (纸本)9781450336857

Computer science students must understand parallel and distributed computing (PDC) concepts to be effective computer scientists in the workforce, as reflected in the ACM Curriculum guidelines. Communities of CS educators are creating educational modules, and making parallel compute environments (PCEs) available to educators who are integrating PDC concepts into their existing curriculum. Even with these resources there is a barrier to entry for students to use PCEs, namely the unfamiliar and complex system software ecosystem of modern PCEs. The OnRamp project lowers that barrier to entry for exploring PDC concepts on a variety of PCEs while also providing a path for students to learn how to be productive on the native PCE. OnRamp is designed to be a general-purpose web portal for supporting the exploration of PDC concepts that harnesses the existing educational resources created by the CS education community. It coaches students through interactive modules that teach them about PDC concepts and PCEs while allowing them to launch parallel applications from day one. As students become more comfortable with running parallel applications on PCEs, OnRamp transforms into a reference guide as they graduate to using the native PCE. This poster describes the motivation, design, and some motivating use cases for the project. We hope that this poster inspires parallel and distributed computing educators to use OnRamp in their courses.

关键词： learning environment. web portal parallel and distributed computing

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Modernizing Early CS Courses with parallel and distributed computing 19

Modernizing Early CS Courses with Parallel and Distributed C...

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Proceedings of the 50th ACM Technical Symposium on Computer Science Education

作者： Sushil Prasad Sheikh Ghafoor Charles Weems Alan Sussman Georgia State University Atlanta GA USA Tennessee Technical University Cookeville TN USA University of Massachusetts Amherst Amherst MA USA University of Maryland College Park MD USA

ISBN: (纸本)9781450358903

parallel and distributed computing (PDC) is now a pervasive aspect of deployed systems, and thus it is essential that students include parallelism and distribution in the computational thinking that they apply to problem solving, from the very beginning. Our students all have multicore laptops. Most of their favorite applications use vast numbers of distributed processors. Why are we still teaching them to solve problems using only sequential thinking? Come to this workshop to see how easy it is to open their eyes to exploiting concurrency in problem solving, starting in their earliest courses. You'll hear about and experience some unplugged activities, learn how to help students recognize examples of concurrency in the world around them, see how event driven user interfaces can easily exemplify issues related to multithreading, and how freely available libraries can be used to naturally exploit parallelism in working with large data structures. We will also highlight the two summer training programs that we are organizing, for which we have funding to support attendance by instructors. Having a laptop that can run Java and C++ will allow you to follow along with some code examples, but isn't necessary.

关键词： unplugged activities introductory computer science data structures parallel and distributed computing

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NSF/IEEE-TCPP curriculum initiative on parallel and distributed computing: core topics for undergraduates (abstract only) 14

NSF/IEEE-TCPP curriculum initiative on parallel and distribu...

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Proceedings of the 45th ACM technical symposium on Computer science education

作者： Sushil K. Prasad Almadena Chtchelkanova Anshul Gupta Arnold Rosenberg Alan Sussman Georgia State University Atlanta USA National Science Foundation Arlington USA IBM T.J. Watson Research Yorktown USA Northeastern University Boston USA University of Maryland College Park USA

ISBN: (纸本)9781450326056

parallelism pervades all aspects of modern computing, from in-home devices such as cell phones to large-scale supercomputers. Recognizing this - and motivated by the premise that every undergraduate student in a computer-related field should be prepared to cope with parallel computing - a working group sponsored by NSF and IEEE/TCPP, and interacting with the ACM CS2013 initiative, has developed guidelines for assimilating parallel and distributed computing (PDC) into the core undergraduate curriculum. Over 100 Early-Adopter institutions worldwide are currently modifying their computer-related curricula in response to the guidelines. Additionally, the CDER Center for Curriculum Development and Educational Resources, which grew out of the working group, is currently assembling a book of contributed essays on how to teach PDC topics in lower-level CS/CE courses, to fill the serious lack of textual material for students and *** session is intended: (i) to report on the current state of this initiative; (ii) to bring together authors of book chapters and Early Adopters and other interested parties for discussions on ongoing activities and needs; (iii) to discuss the initiative and collect direct feedback from the community.

关键词： education parallel and distributed computing early adopters learning outcomes educational resources undergraduate curriculum bloom's classification

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