{"title":"HiPC 2019 WORKSHOP 1: 1st Workshop on Data Science for Future Energy Systems","authors":"S. Kuppannagari, Chayan Sarkar","doi":"10.1109/hipcw.2019.00007","DOIUrl":"https://doi.org/10.1109/hipcw.2019.00007","url":null,"abstract":"Workshop abstract","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"70 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127197914","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":"Improving Throughput of BigData Applications","authors":"Janardhana Reddy Naredula","doi":"10.1109/HiPCW.2019.00014","DOIUrl":"https://doi.org/10.1109/HiPCW.2019.00014","url":null,"abstract":"The paper describes various performance problems and solutions to improve throughput of BigData Application like Redis, Kafka, memcache, Cassandra, ElasticSearch,..etc. Most of the solution to the problems are achieved by some of the techniques like bypassing linux kernel, minimizing system calls, efficiently using the multi core machine using asynchronous programming, one thread per core, DPDK, .. etc. Modern machines are very different from those of just 10 years ago. They have many cores and deep memory hierarchies (from L1 caches to NUMA) which reward certain programming practices and penalizes others, Unscalable programming practices (such as taking locks) can devastate performance on many cores. Shared memory and lock-free synchronization primitives are used in solving some of the problems. The paper was concluded with the test prototype of Redis with efficient network path that resulted 37X perf improvement over the baseline.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125294115","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":"Invited Talk 1: The Future of Parallel Computing","authors":"H. Gabb","doi":"10.1109/hipcw.2019.00017","DOIUrl":"https://doi.org/10.1109/hipcw.2019.00017","url":null,"abstract":"Solving the biggest challenges in science, industry, and society requires dramatic increases in computing efficiency.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129186887","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":"Keynote Talk: Getting Ready for the Emerging Challenge of Massively Parallel Programming Paradigm","authors":"V. Bhatkar","doi":"10.1109/hipcw.2019.00016","DOIUrl":"https://doi.org/10.1109/hipcw.2019.00016","url":null,"abstract":"This talk will discuss the current state of HPC education and will suggest future directions for riding on the wave and leveraging on the tremendous computation power that will be required for the emerging applications.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126180834","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":"Theoretical and Practical Approaches for Teaching Parallel Code Correctness","authors":"Carlos Redondo, R. Arora, Trung Nguyen Ba","doi":"10.1109/HiPCW.2019.00021","DOIUrl":"https://doi.org/10.1109/HiPCW.2019.00021","url":null,"abstract":"The introductory-level courses on parallel programming, typically, do not cover the topic of code correctness. Often, students learn about the logical errors in parallel programs and troubleshoot them through trial and error, and spend a significant amount of time and effort in the process. A systematic pedagogical approach to teaching parallel code correctness is therefore needed to enhance the productivity of students and instructors. In this paper, we describe some theoretical and practical approaches that can be adopted for assessing and teaching parallel code correctness. The theoretical approaches include using formal methods (e.g., Petri nets and Hoare Logic). We apply these approaches on the test cases discussed in this paper. The practical approach involves teaching code correctness through demonstrations. For enabling this, we have not only curated a repository of parallel programs with commonly made logical errors but have also added a high-level interface on top of the repository for quickly comparing fixed and incorrect versions of the sample code in the repository, seeing the explanation text on the errors, and searching the repository on the basis of the causes and symptoms of logical errors. The work presented in this paper can potentially motivate the instructors in including the content on code correctness in their parallel programming courses and trainings.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"7 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127553967","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":"Variations in Residential Electricity Demand Across Income Categories in Urban Bangalore: Results from Primary Survey","authors":"Sashikiran Challa, Shoibal Chakravarty, K. Joshi","doi":"10.1109/HiPCW.2019.00009","DOIUrl":"https://doi.org/10.1109/HiPCW.2019.00009","url":null,"abstract":"Residential electricity demand arises from the need for households to meet various end uses. This demand from residences has seen consistent growth over the last decade. In developing nations like India, this demand is also a significant contributor to greenhouse emissions, given that we are starting from a lower base compared to other countries. Our understanding in this space though is still limited. One of the key reasons for this is lack of availability of open data sources on household's ownership, usage patterns of appliances and key socio-economic indicators which are critical in gaining insights into demand patterns of households. We outline the methodology for designing and executing a statistically representative survey to collect data to understand and analyze residential electricity demand, presenting the case study of a primary representative survey we conducted in urban Bangalore covering 403 households. We also present the methodology for development of a model to build residential load curves at hourly resolution. We analyze three primary questions; how do households in different income-representative brackets consume electricity, what is the variation in consumption between these brackets and what are key appliance groups that contribute to this variance. We also look at generation profiles from solar PV installations to see what times of the day demand can be met from these renewable sources. In the process, we also examine the rooftop policy in Karnataka and suggest any amendments that can be made to increase adoption of solar rooftop to meet some of this demand locally, based on the analysis of load curves.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130688923","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":"Experiences of Teaching Parallel Computing to Undergraduates and Post-Graduates","authors":"Preeti Malakar","doi":"10.1109/HiPCW.2019.00020","DOIUrl":"https://doi.org/10.1109/HiPCW.2019.00020","url":null,"abstract":"In this paper, we present teaching experiences of offering a course on large-scale parallel computing using message passing interface (MPI). This particular course was offered to under-graduates and graduates for the first time in the Department of Computer Science and Engineering, Indian Institute of Technology Kanpur in a very long time. We will present what topics were covered, how we decided the course content, the class demographics, what resources were made available for the students to run their MPI jobs and discuss the output of the course. We will also discuss what were the stumbling blocks encountered while offering a parallel computing systems course without much support from teaching assistants, and some lessons that we took forward to the next time we offered this course.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122561121","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":"Visually Introducing Freshmen to Low-Level Java Abstractions for Creating, Synchronizing and Coordinating Threads","authors":"P. Dewan","doi":"10.1109/HiPCW.2019.00022","DOIUrl":"https://doi.org/10.1109/HiPCW.2019.00022","url":null,"abstract":"We have developed and experimented with an approach to teach low-level Java concurrency abstractions in our first required course for CS majors, which assumes knowledge of procedural programming. The driving problems are visualized simulations of multiple physical objects in motion that may (a) be confined to a shared space and (b) coordinate with each other. Such simulations do not require any domain-specific knowledge such as sorting and image processing for driving problems and exercises, and their implementation demonstrates the benefits of object-based programming. They allow focus on both the performance and programmability benefits of concurrency, provide analogies for an abstraction-independent explanation of concurrency concepts, and can be used to incrementally motivate all low-level concurrency abstractions and visualize the effect of using and not using these abstractions. Layered simulation-based worked examples illustrating the abstractions were presented and easily understood in multiple offerings of a course that implemented this approach. Students implemented non-trivial assignments based on these abstractions, even when they were optional, did not face major obstacles because of visual error feedback, and were excited by concurrency as they felt it empowered them to implement arbitrary applications early.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123528553","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":"Keynote Talk 2: Technology Innovation for Social Good","authors":"Madhuri Duggirala","doi":"10.1109/hipcw.2019.00027","DOIUrl":"https://doi.org/10.1109/hipcw.2019.00027","url":null,"abstract":"This talk gives an overview of how technologies powered by software and hardware can be the key to building a thriving, resilient world to bring a sustainable and affordable transformation for societal needs in the areas of healthcare and sustainable environment.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122038661","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":"HPC Education for Domain Scientists: An Indian Experience and Perspective","authors":"V. V. Shenoi, Vaishali Shah, Sandeep K. Joshi","doi":"10.1109/HiPCW.2019.00023","DOIUrl":"https://doi.org/10.1109/HiPCW.2019.00023","url":null,"abstract":"We review the HPC training avenues for masters, Ph.D. students, postdocs and young faculty in Indian universities and research institutes. Their interest in HPC arises from their need to use it for research in their scientific domain having done some background courses in programming with Fortran/C/C++ and numerical methods. Very few Indian educational institutes offer a course/courses in parallel programming and the course is mostly offered in some of the high ranking engineering institutes. Even in the stream of Computer Science, the course if at all offered is an elective course. The non-Computer Science domain users that makeup as the majority of users of HPC in India do not possess sufficient background in Computer Science and gear up as HPC users mostly through self-study or short term training workshops that address their requirements. However, such training programmes are not a regular activity in India and cater to a broad audience with a varied level of aptitude in computing, programming, and simulation via mathematical modelling. In this paper, we discuss the current HPC education scenario and propose an education strategy to broaden the base of HPC users and to help researchers at all levels to effectively use HPC for their academic research and development work.","PeriodicalId":223719,"journal":{"name":"2019 26th International Conference on High Performance Computing, Data and Analytics Workshop (HiPCW)","volume":"111 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114984911","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}