{"title":"基于项目的单箱计算机HPC课程","authors":"C. Bederián, N. Wolovick","doi":"10.1109/EDUHPC.2016.5","DOIUrl":null,"url":null,"abstract":"Throughout three iterations and six years we have developed a project-based course in HPC for single-box computers tailored to science students in general. The course is based on strong premises: showing that assembly is what actually runs on machines, dividing parallelism in three dimensions (ILP, DLP, TLP), and using them incrementally in a single numerical simulation throughout the course working in interdisciplinary pairs (CS, non-CS). The final goal is to explore how to use all the available transistors in a die. Assembly proved a great tool to show how bare-metal works, an alternative-semantics approach to programs, and a tool to demystify compiler technology. Parallelism is tackled gradually with a clear division into instruction, data, and thread parallelism. GPUs, through CUDA in particular, are used as a radically different approach to the three dimensions of parallelism. Each dimension is explored in a gradual manner, starting from a sequential toy-yet-interesting numerical simulation. After using each form of parallelism and submitting a short report, the experiences are put together in group discussion unveiling the strengths and weaknesses of each form of parallelism for each class of numerical simulation. Although there is a high variance in the students' background, CS and non-CS students pair well in project development, generating understanding and value of the disciplines. The experience proved successful, with former students producing parallel accelerated code of their own in their disciplines.","PeriodicalId":415151,"journal":{"name":"2016 Workshop on Education for High-Performance Computing (EduHPC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A Project-Based HPC Course for Single-Box Computers\",\"authors\":\"C. Bederián, N. Wolovick\",\"doi\":\"10.1109/EDUHPC.2016.5\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Throughout three iterations and six years we have developed a project-based course in HPC for single-box computers tailored to science students in general. The course is based on strong premises: showing that assembly is what actually runs on machines, dividing parallelism in three dimensions (ILP, DLP, TLP), and using them incrementally in a single numerical simulation throughout the course working in interdisciplinary pairs (CS, non-CS). The final goal is to explore how to use all the available transistors in a die. Assembly proved a great tool to show how bare-metal works, an alternative-semantics approach to programs, and a tool to demystify compiler technology. Parallelism is tackled gradually with a clear division into instruction, data, and thread parallelism. GPUs, through CUDA in particular, are used as a radically different approach to the three dimensions of parallelism. Each dimension is explored in a gradual manner, starting from a sequential toy-yet-interesting numerical simulation. After using each form of parallelism and submitting a short report, the experiences are put together in group discussion unveiling the strengths and weaknesses of each form of parallelism for each class of numerical simulation. Although there is a high variance in the students' background, CS and non-CS students pair well in project development, generating understanding and value of the disciplines. The experience proved successful, with former students producing parallel accelerated code of their own in their disciplines.\",\"PeriodicalId\":415151,\"journal\":{\"name\":\"2016 Workshop on Education for High-Performance Computing (EduHPC)\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-13\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 Workshop on Education for High-Performance Computing (EduHPC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/EDUHPC.2016.5\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 Workshop on Education for High-Performance Computing (EduHPC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EDUHPC.2016.5","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A Project-Based HPC Course for Single-Box Computers
Throughout three iterations and six years we have developed a project-based course in HPC for single-box computers tailored to science students in general. The course is based on strong premises: showing that assembly is what actually runs on machines, dividing parallelism in three dimensions (ILP, DLP, TLP), and using them incrementally in a single numerical simulation throughout the course working in interdisciplinary pairs (CS, non-CS). The final goal is to explore how to use all the available transistors in a die. Assembly proved a great tool to show how bare-metal works, an alternative-semantics approach to programs, and a tool to demystify compiler technology. Parallelism is tackled gradually with a clear division into instruction, data, and thread parallelism. GPUs, through CUDA in particular, are used as a radically different approach to the three dimensions of parallelism. Each dimension is explored in a gradual manner, starting from a sequential toy-yet-interesting numerical simulation. After using each form of parallelism and submitting a short report, the experiences are put together in group discussion unveiling the strengths and weaknesses of each form of parallelism for each class of numerical simulation. Although there is a high variance in the students' background, CS and non-CS students pair well in project development, generating understanding and value of the disciplines. The experience proved successful, with former students producing parallel accelerated code of their own in their disciplines.