APLX for Windows, Linux and Macos
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
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 .................. -
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. -
Design Automation for Integrated Optics
DESIGN AUTOMATION FOR INTEGRATED OPTICS by Christopher Condrat A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Electrical and Computer Engineering The University of Utah August 2014 Copyright © Christopher Condrat 2014 All Rights Reserved The University of Utah Graduate School STATEMENT OF DISSERTATION APPROVAL The dissertation of Christopher Condrat has been approved by the following supervisory committee members: Priyank Kalla , Chair 12 / 18 / 2013 Date Approved Steven Blair , Member 12 / 18 / 2013 Date Approved Chris Myers , Member 12 / 18 / 2013 Date Approved Kenneth Stevens , Member 12 / 18 / 2013 Date Approved Erik Brunvand , Member 12 / 18 / 2013 Date Approved and by Gianluca Lazzi , Chair/Dean of the Department/College/School of Electrical and Computer Engineering and by David B. Kieda, Dean of The Graduate School. ABSTRACT Recent breakthroughs in silicon photonics technology are enabling the integration of optical devices into silicon-based semiconductor processes. Photonics technology enables high-speed, high-bandwidth, and high-fidelity communications on the chip-scale—an important development in an increasingly communications-oriented semiconductor world. Significant developments in silicon photonic manufacturing and integration are also enabling investigations into applications beyond that of traditional telecom: sensing, filtering, signal processing, quantum technology—and even optical computing. In effect, we are now seeing a convergence of communications and computation, where the traditional roles of optics and microelectronics are becoming blurred. As the applications for opto-electronic integrated circuits (OEICs) are developed, and manufac- turing capabilities expand, design support is necessary to fully exploit the potential of this optics technology. -
The C Programming Language
The C programming Language The C programming Language By Brian W. Kernighan and Dennis M. Ritchie. Published by Prentice-Hall in 1988 ISBN 0-13-110362-8 (paperback) ISBN 0-13-110370-9 Contents ● Preface ● Preface to the first edition ● Introduction 1. Chapter 1: A Tutorial Introduction 1. Getting Started 2. Variables and Arithmetic Expressions 3. The for statement 4. Symbolic Constants 5. Character Input and Output 1. File Copying 2. Character Counting 3. Line Counting 4. Word Counting 6. Arrays 7. Functions 8. Arguments - Call by Value 9. Character Arrays 10. External Variables and Scope 2. Chapter 2: Types, Operators and Expressions 1. Variable Names 2. Data Types and Sizes 3. Constants 4. Declarations http://freebooks.by.ru/view/CProgrammingLanguage/kandr.html (1 of 5) [5/15/2002 10:12:59 PM] The C programming Language 5. Arithmetic Operators 6. Relational and Logical Operators 7. Type Conversions 8. Increment and Decrement Operators 9. Bitwise Operators 10. Assignment Operators and Expressions 11. Conditional Expressions 12. Precedence and Order of Evaluation 3. Chapter 3: Control Flow 1. Statements and Blocks 2. If-Else 3. Else-If 4. Switch 5. Loops - While and For 6. Loops - Do-While 7. Break and Continue 8. Goto and labels 4. Chapter 4: Functions and Program Structure 1. Basics of Functions 2. Functions Returning Non-integers 3. External Variables 4. Scope Rules 5. Header Files 6. Static Variables 7. Register Variables 8. Block Structure 9. Initialization 10. Recursion 11. The C Preprocessor 1. File Inclusion 2. Macro Substitution 3. Conditional Inclusion 5. Chapter 5: Pointers and Arrays 1. -
Reducing State Explosion for Software Model Checking with Relaxed Mcms 3 We Do Not Distinguish the Framework from Its Implementation and Refer to Both As Mc- SPIN
Reducing State Explosion for Software Model Checking with Relaxed Memory Consistency Models Tatsuya Abe1, Tomoharu Ugawa2, Toshiyuki Maeda1, and Kousuke Matsumoto2 1 {abet,tosh}@stair.center STAIR Lab, Chiba Institute of Technology 2 {ugawa,matsumoto}@plas.info.kochi-tech.ac.jp Kochi University of Technology Abstract. Software model checking suffers from the so-called state explosion problem, and relaxed memory consistency models even worsen this situation. What is worse, parameterizing model checking by memory consistency mod- els, that is, to make the model checker as flexible as we can supply definitions of memory consistency models as an input, intensifies state explosion. This pa- per explores specific reasons for state explosion in model checking with multi- ple memory consistency models, provides some optimizations intended to mit- igate the problem, and applies them to McSPIN, a model checker for memory consistency models that we are developing. The effects of the optimizations and the usefulness of McSPIN are demonstrated experimentally by verifying copying protocols of concurrent copying garbage collection algorithms. To the best of our knowledge, this is the first model checking of the concurrent copying protocols under relaxed memory consistency models. Keywords: software model checking; relaxed memory consistency models; state explosion; reordering of instructions; integration of states; concurrent copying garbage collection 1 Introduction Modern computing systems are based on concurrent/parallel processing designs for their performance advantages, and programs therefore must also be written to exploit these designs. However, writing such programs is quite difficult and error-prone, be- cause humans cannot exhaustively consider the behaviors of computers very well. One approach to this problem is to use software model checking, in which all possible states that can be reached during a program’sexecutionare explored.Many such model check- ers have been developed (e.g., [12,18,26,25,7,8]). -
Egyptian 1967
Southern Illinois University Carbondale OpenSIUC August 1967 Daily Egyptian 1967 8-11-1967 The aiD ly Egyptian, August 11, 1967 The aiD ly Egyptian Staff Follow this and additional works at: http://opensiuc.lib.siu.edu/de_August1967 Volume 48, Issue 198 Recommended Citation , . "The aiD ly Egyptian, August 11, 1967." (Aug 1967). This Article is brought to you for free and open access by the Daily Egyptian 1967 at OpenSIUC. It has been accepted for inclusion in August 1967 by an authorized administrator of OpenSIUC. For more information, please contact [email protected]. Student Response Computer System - ~ Installed in Lawson Students taking classes in could by used In a lecture when Lawson 121 tbis fall will find a test is not being given, a unique ~l of seven buttons Winsor said. at eacb seat-- all pan of a The system at SID, called sop histlcated computer tbe Student Responder System, response s ystem being com is one ot only a few In tbe pleted tbls week. country, Winsor said. Unlque The seven button panel will features of SID's system w!ll have three basic functions witb many variations, said Donald :e t~~o~;~~~~Ho~~:t~~~~~ 1- L. Winsor, assistant pro cbange answers. fessor in audio-visual ser vices and 'director of the pro Cost of tbe project was est ject. imated at between $30,000 and $40,000, Winsor said. The A student will be able to unit Is bUit by General El answer test questions by push ectric and Is be!t}g-thstalled ing one of tbe numbered buttons by Goldberg....K O'Brien· and change his answer by Electrical/ Co mpa n y of simply pushing a Sf correct" C bicago. -
Chapter 1 Basic Principles of Programming Languages
Chapter 1 Basic Principles of Programming Languages Although there exist many programming languages, the differences among them are insignificant compared to the differences among natural languages. In this chapter, we discuss the common aspects shared among different programming languages. These aspects include: programming paradigms that define how computation is expressed; the main features of programming languages and their impact on the performance of programs written in the languages; a brief review of the history and development of programming languages; the lexical, syntactic, and semantic structures of programming languages, data and data types, program processing and preprocessing, and the life cycles of program development. At the end of the chapter, you should have learned: what programming paradigms are; an overview of different programming languages and the background knowledge of these languages; the structures of programming languages and how programming languages are defined at the syntactic level; data types, strong versus weak checking; the relationship between language features and their performances; the processing and preprocessing of programming languages, compilation versus interpretation, and different execution models of macros, procedures, and inline procedures; the steps used for program development: requirement, specification, design, implementation, testing, and the correctness proof of programs. The chapter is organized as follows. Section 1.1 introduces the programming paradigms, performance, features, and the development of programming languages. Section 1.2 outlines the structures and design issues of programming languages. Section 1.3 discusses the typing systems, including types of variables, type equivalence, type conversion, and type checking during the compilation. Section 1.4 presents the preprocessing and processing of programming languages, including macro processing, interpretation, and compilation. -
A Modern Reversible Programming Language April 10, 2015
Arrow: A Modern Reversible Programming Language Author: Advisor: Eli Rose Bob Geitz Abstract Reversible programming languages are those whose programs can be run backwards as well as forwards. This condition impacts even the most basic constructs, such as =, if and while. I discuss Janus, the first im- perative reversible programming language, and its limitations. I then introduce Arrow, a reversible language with modern features, including functions. Example programs are provided. April 10, 2015 Introduction: Many processes in the world have the property of reversibility. To start washing your hands, you turn the knob to the right, and the water starts to flow; the process can be undone, and the water turned off, by turning the knob to the left. To turn your computer on, you press the power button; this too can be undone, by again pressing the power button. In each situation, we had a process (turning the knob, pressing the power button) and a rule that told us how to \undo" that process (turning the knob the other way, and pressing the power button again). Call the second two the inverses of the first two. By a reversible process, I mean a process that has an inverse. Consider two billiard balls, with certain positions and velocities such that they are about to collide. The collision is produced by moving the balls accord- ing to the laws of physics for a few seconds. Take that as our process. It turns out that we can find an inverse for this process { a set of rules to follow which will undo the collision and restore the balls to their original states1. -
APL-The Language Debugging Capabilities, Entirely in APL Terms (No Core Symbol Denotes an APL Function Named' 'Compress," Dumps Or Other Machine-Related Details)
DANIEL BROCKLEBANK APL - THE LANGUAGE Computer programming languages, once the specialized tools of a few technically trained peo p.le, are now fundamental to the education and activities of millions of people in many profes SIons, trades, and arts. The most widely known programming languages (Basic, Fortran, Pascal, etc.) have a strong commonality of concepts and symbols; as a collection, they determine our soci ety's general understanding of what programming languages are like. There are, however, several ~anguages of g~eat interest and quality that are strikingly different. One such language, which shares ItS acronym WIth the Applied Physics Laboratory, is APL (A Programming Language). A SHORT HISTORY OF APL it struggled through the 1970s. Its international con Over 20 years ago, Kenneth E. Iverson published tingent of enthusiasts was continuously hampered by a text with the rather unprepossessing title, A inefficient machine use, poor availability of suitable terminal hardware, and, as always, strong resistance Programming Language. I Dr. Iverson was of the opinion that neither conventional mathematical nota to a highly unconventional language. tions nor the emerging Fortran-like programming lan At the Applied Physics Laboratory, the APL lan guages were conducive to the fluent expression, guage and its practical use have been ongoing concerns publication, and discussion of algorithms-the many of the F. T. McClure Computing Center, whose staff alternative ideas and techniques for carrying out com has long been convinced of its value. Addressing the putation. His text presented a solution to this nota inefficiency problems, the Computing Center devel tion dilemma: a new formal language for writing clear, oped special APL systems software for the IBM concise computer programs. -
Subsistence-Based Socioeconomic Systems in Alaska: an Introduction
Special Publication No. SP1984-001 Subsistence-Based Socioeconomic Systems in Alaska: An Introduction by Robert J. Wolfe 1984 Alaska Department of Fish and Game Division of Subsistence Symbols and Abbreviations The following symbols and abbreviations, and others approved for the Système International d'Unités (SI), are used without definition in the reports by the Division of Subsistence. All others, including deviations from definitions listed below, are noted in the text at first mention, as well as in the titles or footnotes of tables, and in figure or figure captions. Weights and measures (metric) General Mathematics, statistics centimeter cm Alaska Administrative Code AAC all standard mathematical signs, symbols deciliter dL all commonly-accepted and abbreviations gram g abbreviations e.g., alternate hypothesis HA hectare ha Mr., Mrs., base of natural logarithm e kilogram kg AM, PM, etc. catch per unit effort CPUE kilometer km all commonly-accepted coefficient of variation CV liter L professional titles e.g., Dr., Ph.D., common test statistics (F, t, χ2, etc.) meter m R.N., etc. confidence interval CI milliliter mL at @ correlation coefficient (multiple) R millimeter mm compass directions: correlation coefficient (simple) r east E covariance cov Weights and measures (English) north N degree (angular ) ° cubic feet per second ft3/s south S degrees of freedom df foot ft west W expected value E gallon gal copyright greater than > inch in corporate suffixes: greater than or equal to ≥ mile mi Company Co. harvest per unit effort HPUE nautical mile nmi Corporation Corp. less than < ounce oz Incorporated Inc. less than or equal to ≤ pound lb Limited Ltd. -
Merrill Lynch Security Risk Evaluation 1-07
Security Risk Evaluation ALPHA January 2007 Price As of December 2006 Month End COPYRIGHT 1998 MERRILL LYNCH, PIERCE, FENNER & SMITH INCORPORATED (MLPF&S). APPROVED FOR PUBLICATION IN THE UNITED KINGDOM BY MERRILL LYNCH, PIERCE, FENNER & SMITH LIMITED, AN AFFILIATED COMPANY AND REGULATED BY THE SECURITIES AND FUTURES AUTHORITY LIMITED. THE INFORMATION HEREIN WAS OBTAINED FROM VARIOUS SOURCES; WE DO NOT GUARANTEE ITS ACCURACY. ADDITIONAL INFORMATION AVAILABLE. GLOBAL SECURITIES RESEARCH & ECONOMICS RESEARCH TECHNOLOGY ALPHA (1) 800 255-9107 CONTINENTAL UNITED STATES January 2007 (1) 212 449-1072 WORLD WIDE PRICE AS OF December 2006 MONTH END Merrill Lynch, Pierce, Fenner & Smith, Inc. Market Sensitivity Statistics 2006/ 12 Resid Number Ticker Close Std --Std Error-- Adjusted Of Symbol Security Name Price Beta Alpha R-Sqr Dev-n Beta Alpha Beta Observ DOWI DOW JONES & CO 30 INDUSTRIALS 12463.150 0.96 0.03 0.91 1.09 0.04 0.14 0.98 60 DJ 20 DOW JONES & CO 20 TRANS ACTUAL 4560.200 0.94 0.65 0.42 3.86 0.14 0.50 0.96 60 DJ 15 DOW JONES & CO 15 UTIL ACTUAL 456.770 0.57 0.60 0.19 4.12 0.15 0.54 0.72 60 DJ 65 DOW JONES & CO 65 STOCK COMPOSITE 4120.960 0.89 0.28 0.86 1.29 0.05 0.17 0.93 60 SPALNS S&P 500 500 STOCKS 1418.300 1.00 0.00 1.00 0.00 0.00 0.00 1.00 60 Based on S&P 500 Index Using Straight Regression Merrill Lynch, Pierce, Fenner & Smith, Inc.