APL in the Nordic Countries
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A New Golden Age for Computer Architecture: Domain-Specific
A New Golden Age for Computer Architecture: Domain-Specific Hardware/Software Co-Design, Enhanced Security, Open Instruction Sets, and Agile Chip Development John Hennessy and David Patterson Stanford and UC Berkeley 13 June 2018 https://www.youtube.com/watch?v=3LVeEjsn8Ts 1 Outline Part I: History of Part II: Current Architecture - Architecture Challenges - Mainframes, Ending of Dennard Scaling Minicomputers, and Moore’s Law, Security Microprocessors, RISC vs CISC, VLIW Part III: Future Architecture Opportunities - Domain Specific Languages and Architecture, Open Architectures, Agile Hardware Development 2 IBM Compatibility Problem in Early 1960s By early 1960’s, IBM had 4 incompatible lines of computers! 701 ➡ 7094 650 ➡ 7074 702 ➡ 7080 1401 ➡ 7010 Each system had its own: ▪ Instruction set architecture (ISA) ▪ I/O system and Secondary Storage: magnetic tapes, drums and disks ▪ Assemblers, compilers, libraries,... ▪ Market niche: business, scientific, real time, ... IBM System/360 – one ISA to rule them all 3 Control versus Datapath ▪ Processor designs split between datapath, where numbers are stored and arithmetic operations computed, and control, which sequences operations on datapath ▪ Biggest challenge for computer designers was getting control correct Control Instruction Control Lines Condition?▪ Maurice Wilkes invented the idea of microprogramming to design the control unit of a PC processor* Datapath Registers Inst. Reg. ▪ Logic expensive vs. ROM or RAM ALU Busy? Address Data ▪ ROM cheaper than RAM Main Memory ▪ ROM much faster -
An Array-Oriented Language with Static Rank Polymorphism
An array-oriented language with static rank polymorphism Justin Slepak, Olin Shivers, and Panagiotis Manolios Northeastern University fjrslepak,shivers,[email protected] Abstract. The array-computational model pioneered by Iverson's lan- guages APL and J offers a simple and expressive solution to the \von Neumann bottleneck." It includes a form of rank, or dimensional, poly- morphism, which renders much of a program's control structure im- plicit by lifting base operators to higher-dimensional array structures. We present the first formal semantics for this model, along with the first static type system that captures the full power of the core language. The formal dynamic semantics of our core language, Remora, illuminates several of the murkier corners of the model. This allows us to resolve some of the model's ad hoc elements in more general, regular ways. Among these, we can generalise the model from SIMD to MIMD computations, by extending the semantics to permit functions to be lifted to higher- dimensional arrays in the same way as their arguments. Our static semantics, a dependent type system of carefully restricted power, is capable of describing array computations whose dimensions cannot be determined statically. The type-checking problem is decidable and the type system is accompanied by the usual soundness theorems. Our type system's principal contribution is that it serves to extract the implicit control structure that provides so much of the language's expres- sive power, making this structure explicitly apparent at compile time. 1 The Promise of Rank Polymorphism Behind every interesting programming language is an interesting model of com- putation. -
Compendium of Technical White Papers
COMPENDIUM OF TECHNICAL WHITE PAPERS Compendium of Technical White Papers from Kx Technical Whitepaper Contents Machine Learning 1. Machine Learning in kdb+: kNN classification and pattern recognition with q ................................ 2 2. An Introduction to Neural Networks with kdb+ .......................................................................... 16 Development Insight 3. Compression in kdb+ ................................................................................................................. 36 4. Kdb+ and Websockets ............................................................................................................... 52 5. C API for kdb+ ............................................................................................................................ 76 6. Efficient Use of Adverbs ........................................................................................................... 112 Optimization Techniques 7. Multi-threading in kdb+: Performance Optimizations and Use Cases ......................................... 134 8. Kdb+ tick Profiling for Throughput Optimization ....................................................................... 152 9. Columnar Database and Query Optimization ............................................................................ 166 Solutions 10. Multi-Partitioned kdb+ Databases: An Equity Options Case Study ............................................. 192 11. Surveillance Technologies to Effectively Monitor Algo and High Frequency Trading .................. -
Wake up with CPS 006 Program Design and Methodology I Computer Science and Programming What Is Computer Science? Computer Scienc
Computer Science and Programming z Computer Science is more than programming ¾ The discipline is called informatics in many countries ¾ Elements of both science and engineering • Scientists build to learn, engineers learn to build Wake up with CPS 006 – Fred Brooks Program Design and Methodology I ¾ Elements of mathematics, physics, cognitive science, music, art, and many other fields z Computer Science is a young discipline Jeff Forbes ¾ Fiftieth anniversary in 1997, but closer to forty years of research and development ¾ First graduate program at CMU (then Carnegie Tech) in http://www.cs.duke.edu/courses/cps006/current 1965 http://www.cs.duke.edu/csed/tapestry z To some programming is an art, to others a science, to others an engineering discipline A Computer Science Tapestry 1.1 A Computer Science Tapestry 1.2 What is Computer Science? Computer Science What is it that distinguishes it from the z Artificial Intelligence thinking machines separate subjects with which it is related? z Scientific Computing weather, cars, heart, modelling What is the linking thread which gathers these z Theoretical CS analyze algorithms, models disparate branches into a single discipline? My answer to these questions is simple --- it is z Computational Geometry theory of animation, 3-D models the art of programming a computer. It is the art z Architecture hardware-software interface of designing efficient and elegant methods of z Software Engineering engineering, science getting a computer to solve problems, z Operating Systems the soul of the machine theoretical or practical, small or large, simple z Graphics from Windows to Hollywood or complex. z Many other subdisciplines C.A.R. -
Reading List
EECS 101 Introduction to Computer Science Dinda, Spring, 2009 An Introduction to Computer Science For Everyone Reading List Note: You do not need to read or buy all of these. The syllabus and/or class web page describes the required readings and what books to buy. For readings that are not in the required books, I will either provide pointers to web documents or hand out copies in class. Books David Harel, Computers Ltd: What They Really Can’t Do, Oxford University Press, 2003. Fred Brooks, The Mythical Man-month: Essays on Software Engineering, 20th Anniversary Edition, Addison-Wesley, 1995. Joel Spolsky, Joel on Software: And on Diverse and Occasionally Related Matters That Will Prove of Interest to Software Developers, Designers, and Managers, and to Those Who, Whether by Good Fortune or Ill Luck, Work with Them in Some Capacity, APress, 2004. Most content is available for free from Spolsky’s Blog (see http://www.joelonsoftware.com) Paul Graham, Hackers and Painters, O’Reilly, 2004. See also Graham’s site: http://www.paulgraham.com/ Martin Davis, The Universal Computer: The Road from Leibniz to Turing, W.W. Norton and Company, 2000. Ted Nelson, Computer Lib/Dream Machines, 1974. This book is now very rare and very expensive, which is sad given how visionary it was. Simon Singh, The Code Book: The Science of Secrecy from Ancient Egypt to Quantum Cryptography, Anchor, 2000. Douglas Hofstadter, Goedel, Escher, Bach: The Eternal Golden Braid, 20th Anniversary Edition, Basic Books, 1999. Stuart Russell and Peter Norvig, Artificial Intelligence: A Modern Approach, 2nd Edition, Prentice Hall, 2003. -
ESD.33 -- Systems Engineering Session #1 Course Introduction
ESD.33 -- Systems Engineering Session #4 Axiomatic Design Decision-Based Design Summary of Frameworks Phase Dan Frey Follow-up on Session #3 • Mike Fedor - Your lectures and readings about Lean Thinking have motivated me to re-read "The Goal" by Eliyahu M. Goldratt • Don Clausing – Remember that although set-based design seems to explain part of Toyota’s system, it also includes a suite of other powerful tools (QFD, Robust Design) • Denny Mahoney – What assumptions are you making about Ops Mgmt? Plan for the Session • Why are we doing this session? • Axiomatic Design (Suh) • Decision-Based Design (Hazelrigg) • What is rationality? • Overview of frameworks • Discussion of Exam #1 / Next steps Claims Made by Nam Suh • “A general theory for system design is presented” • “The theory is applicable to … large systems, software systems, organizations…” • “The flow diagram … can be used for many different tasks: design, construction, operation, modification, … maintenance … diagnosis …, and for archival documentation.” • “Design axioms were found to improve all designs without exceptions or counter-examples… When counter-examples or exceptions are proposed, the author always found flaws in the arguments.” Claims Made by Hazelrigg • “We present here … axioms and … theorems that underlie the mathematics of design” • “substantially different from … conventional … eng design” • “imposes severe conditions on upon design methodologies” • “all other measures are wrong” • “apply to … all fields of engineering … all products, processes, and services, -
Application and Interpretation
Programming Languages: Application and Interpretation Shriram Krishnamurthi Brown University Copyright c 2003, Shriram Krishnamurthi This work is licensed under the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 United States License. If you create a derivative work, please include the version information below in your attribution. This book is available free-of-cost from the author’s Web site. This version was generated on 2007-04-26. ii Preface The book is the textbook for the programming languages course at Brown University, which is taken pri- marily by third and fourth year undergraduates and beginning graduate (both MS and PhD) students. It seems very accessible to smart second year students too, and indeed those are some of my most successful students. The book has been used at over a dozen other universities as a primary or secondary text. The book’s material is worth one undergraduate course worth of credit. This book is the fruit of a vision for teaching programming languages by integrating the “two cultures” that have evolved in its pedagogy. One culture is based on interpreters, while the other emphasizes a survey of languages. Each approach has significant advantages but also huge drawbacks. The interpreter method writes programs to learn concepts, and has its heart the fundamental belief that by teaching the computer to execute a concept we more thoroughly learn it ourselves. While this reasoning is internally consistent, it fails to recognize that understanding definitions does not imply we understand consequences of those definitions. For instance, the difference between strict and lazy evaluation, or between static and dynamic scope, is only a few lines of interpreter code, but the consequences of these choices is enormous. -
Compsci 6 Programming Design and Analysis
CompSci 6 Programming Design and Analysis Robert C. Duvall http://www.cs.duke.edu/courses/cps006/fall04 http://www.cs.duke.edu/~rcd CompSci 6 : Spring 2005 1.1 What is Computer Science? Computer science is no more about computers than astronomy is about telescopes. Edsger Dijkstra Computer science is not as old as physics; it lags by a couple of hundred years. However, this does not mean that there is significantly less on the computer scientist's plate than on the physicist's: younger it may be, but it has had a far more intense upbringing! Richard Feynman http://www.wordiq.com CompSci 6 : Spring 2005 1.2 Scientists and Engineers Scientists build to learn, engineers learn to build – Fred Brooks CompSci 6 : Spring 2005 1.3 Computer Science and Programming Computer Science is more than programming The discipline is called informatics in many countries Elements of both science and engineering Elements of mathematics, physics, cognitive science, music, art, and many other fields Computer Science is a young discipline Fiftieth anniversary in 1997, but closer to forty years of research and development First graduate program at CMU (then Carnegie Tech) in 1965 To some programming is an art, to others a science, to others an engineering discipline CompSci 6 : Spring 2005 1.4 What is Computer Science? What is it that distinguishes it from the separate subjects with which it is related? What is the linking thread which gathers these disparate branches into a single discipline? My answer to these questions is simple --- it is the art of programming a computer. -
The Computer Scientist As Toolsmith—Studies in Interactive Computer Graphics
Frederick P. Brooks, Jr. Fred Brooks is the first recipient of the ACM Allen Newell Award—an honor to be presented annually to an individual whose career contributions have bridged computer science and other disciplines. Brooks was honored for a breadth of career contributions within computer science and engineering and his interdisciplinary contributions to visualization methods for biochemistry. Here, we present his acceptance lecture delivered at SIGGRAPH 94. The Computer Scientist Toolsmithas II t is a special honor to receive an award computer science. Another view of computer science named for Allen Newell. Allen was one of sees it as a discipline focused on problem-solving sys- the fathers of computer science. He was tems, and in this view computer graphics is very near especially important as a visionary and a the center of the discipline. leader in developing artificial intelligence (AI) as a subdiscipline, and in enunciating A Discipline Misnamed a vision for it. When our discipline was newborn, there was the What a man is is more important than what he usual perplexity as to its proper name. We at Chapel Idoes professionally, however, and it is Allen’s hum- Hill, following, I believe, Allen Newell and Herb ble, honorable, and self-giving character that makes it Simon, settled on “computer science” as our depart- a double honor to be a Newell awardee. I am pro- ment’s name. Now, with the benefit of three decades’ foundly grateful to the awards committee. hindsight, I believe that to have been a mistake. If we Rather than talking about one particular research understand why, we will better understand our craft. -
Computer Science and Global Economic Development: Sounds Interesting, but Is It Computer Science?
Computer Science and Global Economic Development: Sounds Interesting, but is it Computer Science? Tapan S. Parikh UC Berkeley School of Information Berkeley, CA, USA [email protected] OVERVIEW interventions from the bottom up, usually applying experi- Computer scientists have a long history of developing tools mental methods [1]. This includes prominent use of ICTs, useful for advancing knowledge and practice in other disci- both as the focus of new interventions (mobile phones for plines. More than fifty years ago, Grace Hopper said the making markets more efficient [6], digital cameras to moni- role of computers was “freeing mathematicians to do math- tor teacher attendance [2]), and as tools for understanding ematics.” [5] Fred Brooks referred to a computer scientist as their impact (PDAs and smartphones to conduct extensive a toolsmith, , making “things that do not themselves satisfy in-field surveys [8]). It is a wonderfully timely moment for human needs, but which others use in making things that computer scientists to engage with the state-of-the-art in enrich human living.” [4]. Computational biologists have ap- development research and practice. plied algorithmic techniques to process and understand the deluge of data made possible by recent advances in molecu- lar biology. WHY ACADEMIA? WHY CS? The proper way to approach this kind of research has never been clear within Computer Science. The refrain“Sounds Why do this work in academia, and within the disci- interesting, but is it Computer Science?” is frequently heard. pline of Computer Science? There are several motivations. In this paper I argue that it is crucial take an expansive Academia allows us to be more free, and take greater risks, view of what Computer Science is. -
Dyalog User Conference Programme
Conference Programme Sunday 20th October – Thursday 24th October 2013 User Conference 2013 Welcome to the Dyalog User Conference 2013 at Deerfield Beach, Florida All of the presentation and workshop materials are available on the Dyalog 2013 Conference Attendee website at http:/conference.dyalog.com/. Details of the username and password for this site can be found in your conference registration pack. This website is available throughout the conference and will remain available for a short time afterwards – it will be updated as and when necessary. We will be recording the presentations with the intention of uploading the videos to the Internet. For this reason, please do not ask questions during the sessions until you have been passed the microphone. It would help the presenters if you can wait until the Q&A session that concludes each presentation to ask your questions. If your question can't wait, or if the presenter specifically states that questions are welcome throughout, then please raise your hand to indicate that you need the microphone. All of Dyalog's presenters are happy to answer specific questions relating to their topics at any time after their presentation. Scavenger Hunt Have fun and get to know the other delegates by participating in the scavenger hunt that is running throughout Dyalog '13. The hunt runs until 18:30 on Wednesday and prizes will be awarded at the Banquet. Team assignments, rules and the scavenger hunt list will be handed out at registration. Guests are welcome to join in as well as conference delegates. Good luck and happy hunting! For practical information, see the back cover If you have any questions not related to APL, please ask Karen. -
Technical Program Sessions | ACM Multimedia 2010
Technical Program Sessions | ACM Multimedia 2010 http://www.acmmm10.org/program/technical-program/technical-program-... Technical Program Sessions Tuesday, October 26 morning PLENARY PL1 Chairs: Alberto Del Bimbo, University of Firenze, I Shih-Fu Chang, Columbia University, USA Arnold Smeulders, University of Amsterdam, NL Using the Web to do Social Science Duncan Watts, Yahoo! Research Chair: Shih-Fu Chang, Columbia University, USA ORAL SESSION FULL F1 Content Automatic image tagging Chair: Yong Rui, Microsoft Research, USA Leveraging Loosely-Tagged Images and Inter-Object Correlations for Tag Recommendation Yi Shen, University of North Carolina at Charlotte Jianping Fan, University of North Carolina at Charlotte Multi-label Boosting for Image Annotation by Structural Grouping Sparsity Fei Wu, Zhejiang University Yahong Han, Zhejiang University Qi Tian, University of Texas at San Antonio Yueting Zhuang, Zhejiang University Unified Tag Analysis With Multi-Edge Graph Dong Liu, Harbin Institute of Technology Shuicheng Yan, National University of Singapore Yong Rui, Microsoft China R&D Group Hong-Jiang Zhang, Microsoft Advanced Technology Center Efficient Large-Scale Image Annotation by Probabilistic Collaborative Multi-Label Propagation Xiangyu Chen, National University of Singapore Yadong Mu, National University of Singapore Shuicheng Yan, National University of Singapore Tat-Seng Chua, National University of Singapore ORAL SESSION FULL F2 Applications / Human-centered multimedia User-adapted media access Chair: Ralf Steinmetz, University