Pub Date : 2020-11-01DOI: 10.1109/EduHPC51895.2020.00012
H. Casanova, Rafael Ferreira da Silva, Arturo González-Escribano, William Koch, Yuri Torres, David P. Bunde
Peachy Parallel Assignments are high-quality assignments for teaching parallel and distributed computing. They are selected competitively for presentation at the Edu* workshops. All of the assignments have been successfully used in class and they are selected based on the their ease of adoption by other instructors and for being cool and inspirational to students. This paper presents a paper-and-pencil assignment asking students to analyze the performance of different system configurations and an assignment in which students parallelize a simulation of the evolution of simple living organisms.
{"title":"Peachy Parallel Assignments (EduHPC 2020)","authors":"H. Casanova, Rafael Ferreira da Silva, Arturo González-Escribano, William Koch, Yuri Torres, David P. Bunde","doi":"10.1109/EduHPC51895.2020.00012","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00012","url":null,"abstract":"Peachy Parallel Assignments are high-quality assignments for teaching parallel and distributed computing. They are selected competitively for presentation at the Edu* workshops. All of the assignments have been successfully used in class and they are selected based on the their ease of adoption by other instructors and for being cool and inspirational to students. This paper presents a paper-and-pencil assignment asking students to analyze the performance of different system configurations and an assignment in which students parallelize a simulation of the evolution of simple living organisms.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114823653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/EduHPC51895.2020.00007
Radu Velea, Valentin Ilie, I. Bica
Parallel technologies evolve at a fast rate, with new hardware and programming frameworks being introduced every few years. Keeping a Parallel and Distributed Computing (PDC) lecture up to date is a challenge in itself, let alone when one has to consider the synergies between other courses and the shifts in direction that are industry-driven and echo inside the student body. This paper details the process of aligning parallel and distributed curriculum at the Military Technical Academy of Bucharest (MTA) over the last five years, with government and industry demands as well as faculty and student expectations. The result has been an adaptation and an update of the previous lectures and assignments on PDC, and the creation of a new course that relies heavily on parallel technologies to provide a modern outlook on software security and the tools used to combat cyber threats. Concepts and assignments originally designed for a PDC course have molded perfectly into a new supporting paradigm focused on malicious code (malware) analysis.
{"title":"Applying Parallel and Distributed Computing Curriculum to Cyber Security Courses","authors":"Radu Velea, Valentin Ilie, I. Bica","doi":"10.1109/EduHPC51895.2020.00007","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00007","url":null,"abstract":"Parallel technologies evolve at a fast rate, with new hardware and programming frameworks being introduced every few years. Keeping a Parallel and Distributed Computing (PDC) lecture up to date is a challenge in itself, let alone when one has to consider the synergies between other courses and the shifts in direction that are industry-driven and echo inside the student body. This paper details the process of aligning parallel and distributed curriculum at the Military Technical Academy of Bucharest (MTA) over the last five years, with government and industry demands as well as faculty and student expectations. The result has been an adaptation and an update of the previous lectures and assignments on PDC, and the creation of a new course that relies heavily on parallel technologies to provide a modern outlook on software security and the tools used to combat cyber threats. Concepts and assignments originally designed for a PDC course have molded perfectly into a new supporting paradigm focused on malicious code (malware) analysis.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125597497","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/EduHPC51895.2020.00011
Justin Gosselin, Anjia Wang, P. Pirkelbauer, C. Liao, Yonghong Yan, D. Dechev
Compilers and compiler-based tools have become increasingly critical for optimizing high-performance computing workloads; however, compiler development remains difficult and time consuming due to the complex nature of compilers. FreeCompilerCamp.org is an online training framework for compiler development that allows users to complete hands-on tutorials with a Linux environment that is directly embedded in the web browser. It provides an effective and convenient training platform for both new and experienced compiler developers. In this paper, we present our enhancements to the framework to support self-evaluation and learning outcome feedback for trainees. We extend FreeCompilerCamp to support a fully contained self-learning environment with exercises and examinations providing immediate and automatic feedback via server-side grading. We achieve this through two forms of evaluation: openbook practicals and closed-book exams. To facilitate learning, we design several new tutorials and improve the framework to support both CPU and GPU servers and docker images, optimize resource utilization, and enhance usability. Our extended platform, FreeCompilerCamp v1.1, follows the same extensibility design goals as the original to allow for new practicals and exams, providing an effective method to reduce the barrier of entry to compiler development.
{"title":"Extending FreeCompilerCamp.org as an Online Self-Learning Platform for Compiler Development","authors":"Justin Gosselin, Anjia Wang, P. Pirkelbauer, C. Liao, Yonghong Yan, D. Dechev","doi":"10.1109/EduHPC51895.2020.00011","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00011","url":null,"abstract":"Compilers and compiler-based tools have become increasingly critical for optimizing high-performance computing workloads; however, compiler development remains difficult and time consuming due to the complex nature of compilers. FreeCompilerCamp.org is an online training framework for compiler development that allows users to complete hands-on tutorials with a Linux environment that is directly embedded in the web browser. It provides an effective and convenient training platform for both new and experienced compiler developers. In this paper, we present our enhancements to the framework to support self-evaluation and learning outcome feedback for trainees. We extend FreeCompilerCamp to support a fully contained self-learning environment with exercises and examinations providing immediate and automatic feedback via server-side grading. We achieve this through two forms of evaluation: openbook practicals and closed-book exams. To facilitate learning, we design several new tutorials and improve the framework to support both CPU and GPU servers and docker images, optimize resource utilization, and enhance usability. Our extended platform, FreeCompilerCamp v1.1, follows the same extensibility design goals as the original to allow for new practicals and exams, providing an effective method to reduce the barrier of entry to compiler development.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"50 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130012610","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/EduHPC51895.2020.00008
A. Dubey, Katherine M. Riley, D. Bernholdt
The Argonne Training Program in Extreme Scale Computing (ATPESC) was started by Argonne National Laboratory with the objective of expanding the ranks of better-prepared users of high-performance computing (HPC) machines. One of the unique aspects of the program was inclusion of a track on software engineering and community codes. The inclusion was motivated by the observation that the projects with good software processes were better able to meet their scientific goals. Over the years, with greater awareness of software sustainability issues in the community, the track has evolved into a software productivity and sustainability track. In this paper we present our experience in choosing and disseminating the content related to the topic of software engineering in high performance computing science from the beginning of the program until now. We discuss the motivations and the reception of the tracks. We also document the evolution of the track over the years based on student feedback and also the growth of awareness about software productivity in high performance computing.
{"title":"Teaching Software Sustainability for High Performance Computing at ATPESC","authors":"A. Dubey, Katherine M. Riley, D. Bernholdt","doi":"10.1109/EduHPC51895.2020.00008","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00008","url":null,"abstract":"The Argonne Training Program in Extreme Scale Computing (ATPESC) was started by Argonne National Laboratory with the objective of expanding the ranks of better-prepared users of high-performance computing (HPC) machines. One of the unique aspects of the program was inclusion of a track on software engineering and community codes. The inclusion was motivated by the observation that the projects with good software processes were better able to meet their scientific goals. Over the years, with greater awareness of software sustainability issues in the community, the track has evolved into a software productivity and sustainability track. In this paper we present our experience in choosing and disseminating the content related to the topic of software engineering in high performance computing science from the beginning of the program until now. We discuss the motivations and the reception of the tracks. We also document the evolution of the track over the years based on student feedback and also the growth of awareness about software productivity in high performance computing.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128455784","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/EduHPC51895.2020.00013
Joel C. Adams, Godmar Back, P. Bała, Michael K. Bane, K. Cameron, H. Casanova, Margaret Ellis, Rafael Ferreira da Silva, Gautam Jethwani, William Koch, T. Lee, Tongyu Zhu
Lightning talks of EduHPC are a venue where HPC educators discuss work in progress. This paper summarizes the EduHPC 2020 lightning talks, which cover four very different areas: (i) The simulation-based pedagogy of the EduWRENCH project, including motivations for using simulation to teach High Performance Computing, the design principles underlying EduWRENCH modules, a survey of the available modules, a look at a particular module, plus a conclusion including lesson learned thus far and future plans. (ii) The use of the software-tuning component from Student Cluster Competitions in the HPC master’s program at the University of Liverpool. (iii) Steps being taken by the Computer Systems Genome Project at Virginia Tech to foster a community atmosphere among the diverse students working to catalog the lineage of computer system performance over time. (iv) A 3-semester master’s degree program titled Computational Engineering, focused on HPC training, being offered at the University of Warsaw.
{"title":"Lightning Talks of EduHPC 2020","authors":"Joel C. Adams, Godmar Back, P. Bała, Michael K. Bane, K. Cameron, H. Casanova, Margaret Ellis, Rafael Ferreira da Silva, Gautam Jethwani, William Koch, T. Lee, Tongyu Zhu","doi":"10.1109/EduHPC51895.2020.00013","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00013","url":null,"abstract":"Lightning talks of EduHPC are a venue where HPC educators discuss work in progress. This paper summarizes the EduHPC 2020 lightning talks, which cover four very different areas: (i) The simulation-based pedagogy of the EduWRENCH project, including motivations for using simulation to teach High Performance Computing, the design principles underlying EduWRENCH modules, a survey of the available modules, a look at a particular module, plus a conclusion including lesson learned thus far and future plans. (ii) The use of the software-tuning component from Student Cluster Competitions in the HPC master’s program at the University of Liverpool. (iii) Steps being taken by the Computer Systems Genome Project at Virginia Tech to foster a community atmosphere among the diverse students working to catalog the lineage of computer system performance over time. (iv) A 3-semester master’s degree program titled Computational Engineering, focused on HPC training, being offered at the University of Warsaw.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"76 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121246147","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/EduHPC51895.2020.00010
Jan Ciesko, David Poliakoff, Daisy S. Hollman, Christian C. Trott, D. Lebrun-Grandié
Parallel patterns, views, and spaces are promising abstractions to capture the programmer's intent as well as the contextual information that can be used by an underlying runtime to efficiently map software to parallel hardware. These abstractions can be valuable in cases where an algorithm must accommodate requirements of code and performance portability across hardware architectures and vendor programming models. Kokkos is a parallel programming model for host- and accelerator architectures that relies on these abstractions and targets these requirements. It consists of a pure C++ interface, a specification, and a programming library. The programming library exposes patterns and types and maps them to an underlying abstract machine model. The abstract machine model offers a generic view of parallel hardware. While Kokkos is gaining popularity in large-scale HPC applications at some DOE laboratories, we believe that the implemented concepts are of interest to a broader audience including academia as they may contribute to a generic, vendor, and architecture-independent education of parallel programming. In this work, we give an insight into the design considerations of this programming model and list important abstractions. Further, we document best practices obtained from giving virtual classes on Kokkos and give pointers to resources that the reader may consider valuable for a lecture on generic parallel programming for students with preexisting knowledge on this matter.
{"title":"Towards Generic Parallel Programming in Computer Science Education with Kokkos","authors":"Jan Ciesko, David Poliakoff, Daisy S. Hollman, Christian C. Trott, D. Lebrun-Grandié","doi":"10.1109/EduHPC51895.2020.00010","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00010","url":null,"abstract":"Parallel patterns, views, and spaces are promising abstractions to capture the programmer's intent as well as the contextual information that can be used by an underlying runtime to efficiently map software to parallel hardware. These abstractions can be valuable in cases where an algorithm must accommodate requirements of code and performance portability across hardware architectures and vendor programming models. Kokkos is a parallel programming model for host- and accelerator architectures that relies on these abstractions and targets these requirements. It consists of a pure C++ interface, a specification, and a programming library. The programming library exposes patterns and types and maps them to an underlying abstract machine model. The abstract machine model offers a generic view of parallel hardware. While Kokkos is gaining popularity in large-scale HPC applications at some DOE laboratories, we believe that the implemented concepts are of interest to a broader audience including academia as they may contribute to a generic, vendor, and architecture-independent education of parallel programming. In this work, we give an insight into the design considerations of this programming model and list important abstractions. Further, we document best practices obtained from giving virtual classes on Kokkos and give pointers to resources that the reader may consider valuable for a lecture on generic parallel programming for students with preexisting knowledge on this matter.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116046257","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-01DOI: 10.1109/EduHPC51895.2020.00006
T. Newhall
We present the curricular design and learning goals of an upper-level undergraduate course that covers a wide breadth of topics in parallel and distributed computing (PDC), while also providing students with depth of experience and development of problem solving, programming, and analysis skills. We discuss lessons learned from our experiences teaching this course over the past 10 years, and discuss changes and improvements we have made in its offerings, as well as choices and trade-offs we made to achieve a balance, in a single course, between breadth and depth of topic across these two huge fields. Evaluations from students support that our approach works well meeting the goals of exposing students to a broad range of PDC topics, building important PDC thinking and programming skills, and meeting other pedagogical goals of an advance upper-level undergraduate CS course. Although our single course design was created due to constraints common to smaller schools that have fewer faculty resources, smaller curricula, and often fewer required courses for their majors, our experiences with this course lead us to conclude that it is a good approach for an advanced undergraduate course on PDC at any institution.
{"title":"Trying to do it all in a single course: a surprisingly good idea","authors":"T. Newhall","doi":"10.1109/EduHPC51895.2020.00006","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00006","url":null,"abstract":"We present the curricular design and learning goals of an upper-level undergraduate course that covers a wide breadth of topics in parallel and distributed computing (PDC), while also providing students with depth of experience and development of problem solving, programming, and analysis skills. We discuss lessons learned from our experiences teaching this course over the past 10 years, and discuss changes and improvements we have made in its offerings, as well as choices and trade-offs we made to achieve a balance, in a single course, between breadth and depth of topic across these two huge fields. Evaluations from students support that our approach works well meeting the goals of exposing students to a broad range of PDC topics, building important PDC thinking and programming skills, and meeting other pedagogical goals of an advance upper-level undergraduate CS course. Although our single course design was created due to constraints common to smaller schools that have fewer faculty resources, smaller curricula, and often fewer required courses for their majors, our experiences with this course lead us to conclude that it is a good approach for an advanced undergraduate course on PDC at any institution.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134000871","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-08-24DOI: 10.1109/EduHPC51895.2020.00009
V. Jadhao, J. Kadupitiya
We explore the idea of integrating machine learning (ML) with high performance computing (HPC)-driven simulations to address challenges in using simulations to teach computational science and engineering courses. We demonstrate that a ML surrogate, designed using artificial neural networks, yields predictions in excellent agreement with explicit simulation, but at far less time and computing costs. We develop a web application on nanoHUB that supports both HPC-driven simulation and the ML surrogate methods to produce simulation outputs. This tool is used for both in-classroom instruction and for solving homework problems associated with two courses covering topics in the broad areas of computational materials science, modeling and simulation, and engineering applications of HPC-enabled simulations. The evaluation of the tool via in-classroom student feedback and surveys shows that the ML-enhanced tool provides a dynamic and responsive simulation environment that enhances student learning. The improvement in the interactivity with the simulation framework in terms of real-time engagement and anytime access enables students to develop intuition for the physical system behavior through rapid visualization of variations in output quantities with changes in inputs.
{"title":"Integrating Machine Learning with HPC-driven Simulations for Enhanced Student Learning","authors":"V. Jadhao, J. Kadupitiya","doi":"10.1109/EduHPC51895.2020.00009","DOIUrl":"https://doi.org/10.1109/EduHPC51895.2020.00009","url":null,"abstract":"We explore the idea of integrating machine learning (ML) with high performance computing (HPC)-driven simulations to address challenges in using simulations to teach computational science and engineering courses. We demonstrate that a ML surrogate, designed using artificial neural networks, yields predictions in excellent agreement with explicit simulation, but at far less time and computing costs. We develop a web application on nanoHUB that supports both HPC-driven simulation and the ML surrogate methods to produce simulation outputs. This tool is used for both in-classroom instruction and for solving homework problems associated with two courses covering topics in the broad areas of computational materials science, modeling and simulation, and engineering applications of HPC-enabled simulations. The evaluation of the tool via in-classroom student feedback and surveys shows that the ML-enhanced tool provides a dynamic and responsive simulation environment that enhances student learning. The improvement in the interactivity with the simulation framework in terms of real-time engagement and anytime access enables students to develop intuition for the physical system behavior through rapid visualization of variations in output quantities with changes in inputs.","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2020-08-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129389621","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Message from the Workshop Chairs","authors":"G. Engels, Arbi Ghazarian, P. Ralph","doi":"10.1109/comhpc.2016.004","DOIUrl":"https://doi.org/10.1109/comhpc.2016.004","url":null,"abstract":"","PeriodicalId":269408,"journal":{"name":"2020 IEEE/ACM Workshop on Education for High-Performance Computing (EduHPC)","volume":"210 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-05-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116363806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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