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Integrating Stream Parallelism and Task Parallelism in a Dataflow Programming Model
RICE UNIVERSITY Integrating Stream Parallelism and Task Parallelism in a Dataflow Programming Model by Drago¸sDumitru Sb^ırlea A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree Master of Science Approved, Thesis Committee: Vivek Sarkar Professor of Computer Science E.D. Butcher Chair in Engineering Keith D. Cooper L. John and Ann H. Doerr Professor of Computational Engineering Lin Zhong Associate Professor of Electrical and Computer Engineering Jun Shirako Research Scientist Computer Science Department Houston, Texas September 3rd, 2011 ABSTRACT Integrating Stream Parallelism and Task Parallelism in a Dataflow Programming Model by Drago¸sDumitru Sb^ırlea As multicore computing becomes the norm, exploiting parallelism in applications becomes a requirement for all software. Many applications exhibit different kinds of parallelism, but most parallel programming languages are biased towards a specific paradigm, of which two common ones are task and streaming parallelism. This results in a dilemma for programmers who would prefer to use the same language to exploit different paradigms for different applications. Our thesis is an integration of stream- parallel and task-parallel paradigms can be achieved in a single language with high programmability and high resource efficiency, when a general dataflow programming model is used as the foundation. The dataflow model used in this thesis is Intel's Concurrent Collections (CnC). While CnC is general enough to express both task-parallel and stream-parallel paradigms, all current implementations of CnC use task-based runtime systems that do not de- liver the resource efficiency expected from stream-parallel programs. For streaming programs, this use of a task-based runtime system is wasteful of computing cycles and makes memory management more difficult than it needs to be. -
Dataflow Programming Model for Reconfigurable Computing Laurent Gantel, Amel Khiar, Benoît Miramond, Mohamed El Amine Benkhelifa, Fabrice Lemonnier, Lounis Kessal
Dataflow Programming Model For Reconfigurable Computing Laurent Gantel, Amel Khiar, Benoît Miramond, Mohamed El Amine Benkhelifa, Fabrice Lemonnier, Lounis Kessal To cite this version: Laurent Gantel, Amel Khiar, Benoît Miramond, Mohamed El Amine Benkhelifa, Fabrice Lemonnier, et al.. Dataflow Programming Model For Reconfigurable Computing. 6th International Workshop on Reconfigurable Communication-centric Systems-on-Chip (ReCoSoC), Jun 2011, Montpellier, France. pp.1-8, 10.1109/ReCoSoC.2011.5981505. hal-00623674 HAL Id: hal-00623674 https://hal.archives-ouvertes.fr/hal-00623674 Submitted on 14 Sep 2011 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Dataflow Programming Model For Reconfigurable Computing L. Gantel∗† and A. Khiar∗ and B. Miramond∗ and A. Benkhelifa∗ and F. Lemonnier† and L. Kessal∗ ∗ ETIS Laboratory – UMR CNRS 8051 † Embedded System Lab Universityof Cergy-Pontoise/ ENSEA Thales Research and Technology 6,avenueduPonceau 1,avenueAugustinFresnel 95014 Cergy-Pontoise, FRANCE 91767 Palaiseau, FRANCE Email {firstname.name}@ensea.fr Email {firstname.name}@thalesgroup.com Abstract—This paper addresses the problem of image process- system, such as sockets. ing algorithms implementation onto dynamically and reconfig- It reduces significantly the work of application programmers urable architectures. Today, these Systems-on-Chip (SoC), offer by relieving them of tedious and error-prone programming. -
Machine Learning with Multiscale Dataflow Computing for High Energy Physics
Machine Learning with Multiscale Dataflow Computing for High Energy Physics 10.7.2019 Outline • Dataflow Concept and Maxeler • Dataflow for ML and Use Cases • Dataflow Programming Introduction • Hands-on Example 2 Dataflow Concept and Maxeler 10.7.2019 Programmable Spectrum Control-flow processors Dataflow processor GK110 Single-Core CPU Multi-Core Several-Cores Many-Cores Dataflow Increasing Parallelism (#cores) Increasing Core Complexity ( Hardware Clock Frequency ) GPU (NVIDIA, AMD) Intel, AMD Tilera, XMOS etc... Maxeler Hybrid e.g. AMD Fusion, IBM Cell 4 Maxeler Dataflow Engines (DFEs) • Largest Reconfigurable DataflowLMEM Engine (DFE) (Large Memory) Chip 4-96GB MaxRing • O(1k) multipliers High bandwidth memory link Interconnect • O(100k) logic cells Reconfigurable compute fabric • O(10MB) of on-chip SRAM MaxRing Dataflow cores & * links FMEM (fast • O(10GB) of on-card DRAM memory) • DFE-to-DFE interconnect Link to main data network * approaching 128GB on a ¾, single slot PCIe card 5 5 Maxeler Dataflow Engines (DFEs) CPU DFE (Dataflow Engine) 6 Control Flow versus Data Flow • Control Flow: • It is all about how instructions “move” • Data may move along with instructions (secondary issue) • Order of computation is the key • Data Flow: • It is about how data moves through a set of “instructions” in 2D space • Data moves will trigger control • Data availability, transformations and operation latencies are the key 7 Area Utilisation of Modern Chips AMD Bulldozer CPU Nvidia Tesla V100 GPU 8 DFE Area Utilisation 9 Dataflow Computing • A custom chip for a specific application • No instructions ➝ no instruction decode logic • No branches ➝ no branch prediction • Explicit parallelism ➝ no out-of-order scheduling • Data streamed onto-chip ➝ no multi-level caches Memory (Lots (Lots of) Rest of the My Dataflow world Engine 10 Dataflow Computing • Single worker builds a single • Each component is added to bicycle from a group of parts the bicycle in a production line. -
NOVEMBER 18 • WEDNESDAY Build Stuff'15 Lithuania
Build Stuff'15 Lithuania NOVEMBER 18 • WEDNESDAY A Advanced B Beginner I Intermediate N NonTechnical 08:30 – 09:00 Registration 1. Alfa Speakers: Registration 09:00 – 09:15 Welcome talk 1. Alfa Speakers: Welcome talk 09:00 – 18:00 Open Space 6. Lobby Speakers: Open Space Sponsors: 4Finance, Devbridge, Storebrand, Visma Lietuva, WIX Lietuva 09:15 – 10:15 B Uncle Bob / Robert Martin @unclebobmartin The Last Programming Language 1. Alfa Speakers: Uncle Bob / Robert Martin For the last 50 years we’ve been exploring language after language. Now many of the “new” languages are actually quite old. The latest fad is “functional programming” which got it’s roots back in the 50s. Have we come full circle? Have we explored all the different kinds of languages? Is it time for us to finally decide on a single language for all software development? In this talk Uncle Bob walks through some of the history of programming languages, and then prognosticates on the future of languages. 10:15 – 10:35 Coffee/tea break 1. Alfa Speakers: Coffee/tea break 10:35 – 11:30 I Dmytro Mindra @dmytromindra Refactoring Legacy Code 5. Theta Speakers: Dmytro Mindra Every programmer has to face legacy code day after day. It might be ugly, it might look scary, it can make a grown man cry. Some will throw it away and try rewriting everything from scratch. Most of them will fail. Refactoring legacy code is a much better idea. It is not so scary when you take it in very small bites, introduce small changes, add unit tests. -
The Best of Both Worlds?
The Best of Both Worlds? Reimplementing an Object-Oriented System with Functional Programming on the .NET Platform and Comparing the Two Paradigms Erik Bugge Thesis submitted for the degree of Master in Informatics: Programming and Networks 60 credits Department of Informatics Faculty of mathematics and natural sciences UNIVERSITY OF OSLO Autumn 2019 The Best of Both Worlds? Reimplementing an Object-Oriented System with Functional Programming on the .NET Platform and Comparing the Two Paradigms Erik Bugge © 2019 Erik Bugge The Best of Both Worlds? http://www.duo.uio.no/ Printed: Reprosentralen, University of Oslo Abstract Programming paradigms are categories that classify languages based on their features. Each paradigm category contains rules about how the program is built. Comparing programming paradigms and languages is important, because it lets developers make more informed decisions when it comes to choosing the right technology for a system. Making meaningful comparisons between paradigms and languages is challenging, because the subjects of comparison are often so dissimilar that the process is not always straightforward, or does not always yield particularly valuable results. Therefore, multiple avenues of comparison must be explored in order to get meaningful information about the pros and cons of these technologies. This thesis looks at the difference between the object-oriented and functional programming paradigms on a higher level, before delving in detail into a development process that consisted of reimplementing parts of an object- oriented system into functional code. Using results from major comparative studies, exploring high-level differences between the two paradigms’ tools for modular programming and general program decompositions, and looking at the development process described in detail in this thesis in light of the aforementioned findings, a comparison on multiple levels was done. -
Graceful Language Extensions and Interfaces
Graceful Language Extensions and Interfaces by Michael Homer A thesis submitted to the Victoria University of Wellington in fulfilment of the requirements for the degree of Doctor of Philosophy Victoria University of Wellington 2014 Abstract Grace is a programming language under development aimed at ed- ucation. Grace is object-oriented, imperative, and block-structured, and intended for use in first- and second-year object-oriented programming courses. We present a number of language features we have designed for Grace and implemented in our self-hosted compiler. We describe the design of a pattern-matching system with object-oriented structure and minimal extension to the language. We give a design for an object-based module system, which we use to build dialects, a means of extending and restricting the language available to the programmer, and of implementing domain-specific languages. We show a visual programming interface that melds visual editing (à la Scratch) with textual editing, and that uses our dialect system, and we give the results of a user experiment we performed to evaluate the usability of our interface. ii ii Acknowledgments The author wishes to acknowledge: • James Noble and David Pearce, his supervisors; • Andrew P. Black and Kim B. Bruce, the other designers of Grace; • Timothy Jones, a coauthor on a paper forming part of this thesis and contributor to Minigrace; • Amy Ruskin, Richard Yannow, and Jameson McCowan, coauthors on other papers; • Daniel Gibbs, Jan Larres, Scott Weston, Bart Jacobs, Charlie Paucard, and Alex Sandilands, other contributors to Minigrace; • Gilad Bracha, Matthias Felleisen, and the other (anonymous) review- ers of papers forming part of this thesis; • the participants in his user study; • David Streader, John Grundy, and Laurence Tratt, examiners of the thesis; • and Alexandra Donnison, Amy Chard, Juanri Barnard, Roma Kla- paukh, and Timothy Jones, for providing feedback on drafts of this thesis. -
Graceful Language Extensions and Interfaces
Graceful Language Extensions and Interfaces by Michael Homer A thesis submitted to the Victoria University of Wellington in fulfilment of the requirements for the degree of Doctor of Philosophy Victoria University of Wellington 2014 Abstract Grace is a programming language under development aimed at ed- ucation. Grace is object-oriented, imperative, and block-structured, and intended for use in first- and second-year object-oriented programming courses. We present a number of language features we have designed for Grace and implemented in our self-hosted compiler. We describe the design of a pattern-matching system with object-oriented structure and minimal extension to the language. We give a design for an object-based module system, which we use to build dialects, a means of extending and restricting the language available to the programmer, and of implementing domain-specific languages. We show a visual programming interface that melds visual editing (à la Scratch) with textual editing, and that uses our dialect system, and we give the results of a user experiment we performed to evaluate the usability of our interface. ii ii Acknowledgments The author wishes to acknowledge: • James Noble and David Pearce, his supervisors; • Andrew P. Black and Kim B. Bruce, the other designers of Grace; • Timothy Jones, a coauthor on a paper forming part of this thesis and contributor to Minigrace; • Amy Ruskin, Richard Yannow, and Jameson McCowan, coauthors on other papers; • Daniel Gibbs, Jan Larres, Scott Weston, Bart Jacobs, Charlie Paucard, and Alex Sandilands, other contributors to Minigrace; • Gilad Bracha, Matthias Felleisen, and the other (anonymous) review- ers of papers forming part of this thesis; • the participants in his user study; • and Roma Klapaukh, Juanri Barnard, Alexandra Donnison, Amy Chard, and Timothy Jones for providing feedback on drafts of this thesis. -
Proceedings of the 8Th European Lisp Symposium Goldsmiths, University of London, April 20-21, 2015 Julian Padget (Ed.) Sponsors
Proceedings of the 8th European Lisp Symposium Goldsmiths, University of London, April 20-21, 2015 Julian Padget (ed.) Sponsors We gratefully acknowledge the support given to the 8th European Lisp Symposium by the following sponsors: WWWLISPWORKSCOM i Organization Programme Committee Julian Padget – University of Bath, UK (chair) Giuseppe Attardi — University of Pisa, Italy Sacha Chua — Toronto, Canada Stephen Eglen — University of Cambridge, UK Marc Feeley — University of Montreal, Canada Matthew Flatt — University of Utah, USA Rainer Joswig — Hamburg, Germany Nick Levine — RavenPack, Spain Henry Lieberman — MIT, USA Christian Queinnec — University Pierre et Marie Curie, Paris 6, France Robert Strandh — University of Bordeaux, France Edmund Weitz — University of Applied Sciences, Hamburg, Germany Local Organization Christophe Rhodes – Goldsmiths, University of London, UK (chair) Richard Lewis – Goldsmiths, University of London, UK Shivi Hotwani – Goldsmiths, University of London, UK Didier Verna – EPITA Research and Development Laboratory, France ii Contents Acknowledgments i Messages from the chairs v Invited contributions Quicklisp: On Beyond Beta 2 Zach Beane µKanren: Running the Little Things Backwards 3 Bodil Stokke Escaping the Heap 4 Ahmon Dancy Unwanted Memory Retention 5 Martin Cracauer Peer-reviewed papers Efficient Applicative Programming Environments for Computer Vision Applications 7 Benjamin Seppke and Leonie Dreschler-Fischer Keyboard? How quaint. Visual Dataflow Implemented in Lisp 15 Donald Fisk P2R: Implementation of -
On the Cognitive Prerequisites of Learning Computer Programming
On the Cognitive Prerequisites of Learning Computer Programming Roy D. Pea D. Midian Kurland Technical Report No. 18 ON THE COGNITIVE PREREQUISITES OF LEARNING COMPUTER PROGRAMMING* Roy D. Pea and D. Midian Kurland Introduction Training in computer literacy of some form, much of which will consist of training in computer programming, is likely to involve $3 billion of the $14 billion to be spent on personal computers by 1986 (Harmon, 1983). Who will do the training? "hardware and software manu- facturers, management consultants, -retailers, independent computer instruction centers, corporations' in-house training programs, public and private schools and universities, and a variety of consultants1' (ibid.,- p. 27). To date, very little is known about what one needs to know in order to learn to program, and the ways in which edu- cators might provide optimal learning conditions. The ultimate suc- cess of these vast training programs in programming--especially toward the goal of providing a basic computer programming compe- tency for all individuals--will depend to a great degree on an ade- quate understanding of the developmental psychology of programming skills, a field currently in its infancy. In the absence of such a theory, training will continue, guided--or to express it more aptly, misguided--by the tacit Volk theories1' of programming development that until now have served as the underpinnings of programming instruction. Our paper begins to explore the complex agenda of issues, promise, and problems that building a developmental science of programming entails. Microcomputer Use in Schools The National Center for Education Statistics has recently released figures revealing that the use of micros in schools tripled from Fall 1980 to Spring 1983. -
Handout 16: J Dictionary
J Dictionary Roger K.W. Hui Kenneth E. Iverson Copyright © 1991-2002 Jsoftware Inc. All Rights Reserved. Last updated: 2002-09-10 www.jsoftware.com . Table of Contents 1 Introduction 2 Mnemonics 3 Ambivalence 4 Verbs and Adverbs 5 Punctuation 6 Forks 7 Programs 8 Bond Conjunction 9 Atop Conjunction 10 Vocabulary 11 Housekeeping 12 Power and Inverse 13 Reading and Writing 14 Format 15 Partitions 16 Defined Adverbs 17 Word Formation 18 Names and Displays 19 Explicit Definition 20 Tacit Equivalents 21 Rank 22 Gerund and Agenda 23 Recursion 24 Iteration 25 Trains 26 Permutations 27 Linear Functions 28 Obverse and Under 29 Identity Functions and Neutrals 30 Secondaries 31 Sample Topics 32 Spelling 33 Alphabet and Numbers 34 Grammar 35 Function Tables 36 Bordering a Table 37 Tables (Letter Frequency) 38 Tables 39 Classification 40 Disjoint Classification (Graphs) 41 Classification I 42 Classification II 43 Sorting 44 Compositions I 45 Compositions II 46 Junctions 47 Partitions I 48 Partitions II 49 Geometry 50 Symbolic Functions 51 Directed Graphs 52 Closure 53 Distance 54 Polynomials 55 Polynomials (Continued) 56 Polynomials in Terms of Roots 57 Polynomial Roots I 58 Polynomial Roots II 59 Polynomials: Stopes 60 Dictionary 61 I. Alphabet and Words 62 II. Grammar 63 A. Nouns 64 B. Verbs 65 C. Adverbs and Conjunctions 66 D. Comparatives 67 E. Parsing and Execution 68 F. Trains 69 G. Extended and Rational Arithmeti 70 H. Frets and Scripts 71 I. Locatives 72 J. Errors and Suspensions 73 III. Definitions 74 Vocabulary 75 = Self-Classify - Equal 76 =. Is (Local) 77 < Box - Less Than 78 <. -
Visual Programming Language for Tacit Subset of J Programming Language
Visual Programming Language for Tacit Subset of J Programming Language Nouman Tariq Dissertation 2013 Erasmus Mundus MSc in Dependable Software Systems Department of Computer Science National University of Ireland, Maynooth Co. Kildare, Ireland A dissertation submitted in partial fulfilment of the requirements for the Erasmus Mundus MSc Dependable Software Systems Head of Department : Dr Adam Winstanley Supervisor : Professor Ronan Reilly June 30, 2013 Declaration I hereby certify that this material, which I now submit for assessment on the program of study leading to the award of Master of Science in Dependable Software Systems, is entirely my own work and has not been taken from the work of others save and to the extent that such work has been cited and acknowledged within the text of my work. Signed:___________________________ Date:___________________________ Abstract Visual programming is the idea of using graphical icons to create programs. I take a look at available solutions and challenges facing visual languages. Keeping these challenges in mind, I measure the suitability of Blockly and highlight the advantages of using Blockly for creating a visual programming environment for the J programming language. Blockly is an open source general purpose visual programming language designed by Google which provides a wide range of features and is meant to be customized to the user’s needs. I also discuss features of the J programming language that make it suitable for use in visual programming language. The result is a visual programming environment for the tacit subset of the J programming language. Table of Contents Introduction ............................................................................................................................................ 7 Problem Statement ............................................................................................................................. 7 Motivation.......................................................................................................................................... -
Visualocv: Refined Dataflow Programming Interface for Opencv
Southern Adventist University KnowledgeExchange@Southern MS in Computer Science Project Reports School of Computing Summer 8-17-2020 VisualOCV: Refined Dataflow ogrPr amming Interface for OpenCV John Boggess [email protected] Follow this and additional works at: https://knowledge.e.southern.edu/mscs_reports Part of the Graphics and Human Computer Interfaces Commons, and the Programming Languages and Compilers Commons Recommended Citation Boggess, John, "VisualOCV: Refined Dataflow ogrPr amming Interface for OpenCV" (2020). MS in Computer Science Project Reports. 5. https://knowledge.e.southern.edu/mscs_reports/5 This Article is brought to you for free and open access by the School of Computing at KnowledgeExchange@Southern. It has been accepted for inclusion in MS in Computer Science Project Reports by an authorized administrator of KnowledgeExchange@Southern. For more information, please contact [email protected]. VISUALOCV: REFINED DATAFLOW PROGRAMMING INTERFACE FOR OPENCV by John R. W. Boggess A PROJECT DEFENSE Presented to the Faculty of The School of Computing at the Southern Adventist University In Partial Fulfilment of Requirements For the Degree of Master of Science Major: Computer Science Under the Supervision of Professor Hall Collegedale, Tennessee August 4, 2020 VisualOVC: Refined Dataflow Programming Interface for OpenCV Approved by: Professor Tyson Hall, Adviser Professor Scot Anderson Professor Robert Ord´o˜nez Date Approved VISUALOCV: REFINED DATAFLOW PROGRAMMING INTERFACE FOR OPENCV John R. W. Boggess Southern Adventist University, 2020 Adviser: Tyson Hall, Ph.D. OpenCV is a popular tool for developing computer vision algorithms; however, prototyping OpenCV-based algorithms is a time consuming and iterative process. VisualOCV is an open source tool to help users better understand and create computer vision algorithms.