A Binary Data Stream Scripting Language
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processor handbook digital equipment corporation Copyright© 1972, by Digital Equipment Corporation DEC, PDP, UNIBUS are registered trademarks of Digital Equipment Corporation. ii TABLE OF CONTENTS CHAPTER 1 INTRODUCTION 1·1 1.1 GENERAL ............................................. 1·1 1.2 GENERAL CHARACTERISTICS . 1·2 1.2.1 The UNIBUS ..... 1·2 1.2.2 Central Processor 1·3 1.2.3 Memories ........... 1·5 1.2.4 Floating Point ... 1·5 1.2.5 Memory Management .............................. .. 1·5 1.3 PERIPHERALS/OPTIONS ......................................... 1·5 1.3.1 1/0 Devices .......... .................................. 1·6 1.3.2 Storage Devices ...................................... .. 1·6 1.3.3 Bus Options .............................................. 1·6 1.4 SOFTWARE ..... .... ........................................... ............. 1·6 1.4.1 Paper Tape Software .......................................... 1·7 1.4.2 Disk Operating System Software ........................ 1·7 1.4.3 Higher Level Languages ................................... .. 1·7 1.5 NUMBER SYSTEMS ..................................... 1-7 CHAPTER 2 SYSTEM ARCHITECTURE. 2-1 2.1 SYSTEM DEFINITION .............. 2·1 2.2 UNIBUS ......................................... 2-1 2.2.1 Bidirectional Lines ...... 2-1 2.2.2 Master-Slave Relation .. 2-2 2.2.3 Interlocked Communication 2-2 2.3 CENTRAL PROCESSOR .......... 2-2 2.3.1 General Registers ... 2-3 2.3.2 Processor Status Word ....... 2-4 2.3.3 Stack Limit Register 2-5 2.4 EXTENDED INSTRUCTION SET & FLOATING POINT .. 2-5 2.5 CORE MEMORY . .... 2-6 2.6 AUTOMATIC PRIORITY INTERRUPTS .... 2-7 2.6.1 Using the Interrupts . 2-9 2.6.2 Interrupt Procedure 2-9 2.6.3 Interrupt Servicing ............ .. 2-10 2.7 PROCESSOR TRAPS ............ 2-10 2.7.1 Power Failure .............. -
Generalized Linear Models (Glms)
San Jos´eState University Math 261A: Regression Theory & Methods Generalized Linear Models (GLMs) Dr. Guangliang Chen This lecture is based on the following textbook sections: • Chapter 13: 13.1 – 13.3 Outline of this presentation: • What is a GLM? • Logistic regression • Poisson regression Generalized Linear Models (GLMs) What is a GLM? In ordinary linear regression, we assume that the response is a linear function of the regressors plus Gaussian noise: 0 2 y = β0 + β1x1 + ··· + βkxk + ∼ N(x β, σ ) | {z } |{z} linear form x0β N(0,σ2) noise The model can be reformulate in terms of • distribution of the response: y | x ∼ N(µ, σ2), and • dependence of the mean on the predictors: µ = E(y | x) = x0β Dr. Guangliang Chen | Mathematics & Statistics, San Jos´e State University3/24 Generalized Linear Models (GLMs) beta=(1,2) 5 4 3 β0 + β1x b y 2 y 1 0 −1 0.0 0.2 0.4 0.6 0.8 1.0 x x Dr. Guangliang Chen | Mathematics & Statistics, San Jos´e State University4/24 Generalized Linear Models (GLMs) Generalized linear models (GLM) extend linear regression by allowing the response variable to have • a general distribution (with mean µ = E(y | x)) and • a mean that depends on the predictors through a link function g: That is, g(µ) = β0x or equivalently, µ = g−1(β0x) Dr. Guangliang Chen | Mathematics & Statistics, San Jos´e State University5/24 Generalized Linear Models (GLMs) In GLM, the response is typically assumed to have a distribution in the exponential family, which is a large class of probability distributions that have pdfs of the form f(x | θ) = a(x)b(θ) exp(c(θ) · T (x)), including • Normal - ordinary linear regression • Bernoulli - Logistic regression, modeling binary data • Binomial - Multinomial logistic regression, modeling general cate- gorical data • Poisson - Poisson regression, modeling count data • Exponential, Gamma - survival analysis Dr. -
CS 61A Streams Summer 2019 1 Streams
CS 61A Streams Summer 2019 Discussion 10: August 6, 2019 1 Streams In Python, we can use iterators to represent infinite sequences (for example, the generator for all natural numbers). However, Scheme does not support iterators. Let's see what happens when we try to use a Scheme list to represent an infinite sequence of natural numbers: scm> (define (naturals n) (cons n (naturals (+ n 1)))) naturals scm> (naturals 0) Error: maximum recursion depth exceeded Because cons is a regular procedure and both its operands must be evaluted before the pair is constructed, we cannot create an infinite sequence of integers using a Scheme list. Instead, our Scheme interpreter supports streams, which are lazy Scheme lists. The first element is represented explicitly, but the rest of the stream's elements are computed only when needed. Computing a value only when it's needed is also known as lazy evaluation. scm> (define (naturals n) (cons-stream n (naturals (+ n 1)))) naturals scm> (define nat (naturals 0)) nat scm> (car nat) 0 scm> (cdr nat) #[promise (not forced)] scm> (car (cdr-stream nat)) 1 scm> (car (cdr-stream (cdr-stream nat))) 2 We use the special form cons-stream to create a stream: (cons-stream <operand1> <operand2>) cons-stream is a special form because the second operand is not evaluated when evaluating the expression. To evaluate this expression, Scheme does the following: 1. Evaluate the first operand. 2. Construct a promise containing the second operand. 3. Return a pair containing the value of the first operand and the promise. 2 Streams To actually get the rest of the stream, we must call cdr-stream on it to force the promise to be evaluated. -
Chapter 2 Basics of Scanning And
Chapter 2 Basics of Scanning and Conventional Programming in Java In this chapter, we will introduce you to an initial set of Java features, the equivalent of which you should have seen in your CS-1 class; the separation of problem, representation, algorithm and program – four concepts you have probably seen in your CS-1 class; style rules with which you are probably familiar, and scanning - a general class of problems we see in both computer science and other fields. Each chapter is associated with an animating recorded PowerPoint presentation and a YouTube video created from the presentation. It is meant to be a transcript of the associated presentation that contains little graphics and thus can be read even on a small device. You should refer to the associated material if you feel the need for a different instruction medium. Also associated with each chapter is hyperlinked code examples presented here. References to previously presented code modules are links that can be traversed to remind you of the details. The resources for this chapter are: PowerPoint Presentation YouTube Video Code Examples Algorithms and Representation Four concepts we explicitly or implicitly encounter while programming are problems, representations, algorithms and programs. Programs, of course, are instructions executed by the computer. Problems are what we try to solve when we write programs. Usually we do not go directly from problems to programs. Two intermediate steps are creating algorithms and identifying representations. Algorithms are sequences of steps to solve problems. So are programs. Thus, all programs are algorithms but the reverse is not true. -
Lecture 04 Linear Structures Sort
Algorithmics (6EAP) MTAT.03.238 Linear structures, sorting, searching, etc Jaak Vilo 2018 Fall Jaak Vilo 1 Big-Oh notation classes Class Informal Intuition Analogy f(n) ∈ ο ( g(n) ) f is dominated by g Strictly below < f(n) ∈ O( g(n) ) Bounded from above Upper bound ≤ f(n) ∈ Θ( g(n) ) Bounded from “equal to” = above and below f(n) ∈ Ω( g(n) ) Bounded from below Lower bound ≥ f(n) ∈ ω( g(n) ) f dominates g Strictly above > Conclusions • Algorithm complexity deals with the behavior in the long-term – worst case -- typical – average case -- quite hard – best case -- bogus, cheating • In practice, long-term sometimes not necessary – E.g. for sorting 20 elements, you dont need fancy algorithms… Linear, sequential, ordered, list … Memory, disk, tape etc – is an ordered sequentially addressed media. Physical ordered list ~ array • Memory /address/ – Garbage collection • Files (character/byte list/lines in text file,…) • Disk – Disk fragmentation Linear data structures: Arrays • Array • Hashed array tree • Bidirectional map • Heightmap • Bit array • Lookup table • Bit field • Matrix • Bitboard • Parallel array • Bitmap • Sorted array • Circular buffer • Sparse array • Control table • Sparse matrix • Image • Iliffe vector • Dynamic array • Variable-length array • Gap buffer Linear data structures: Lists • Doubly linked list • Array list • Xor linked list • Linked list • Zipper • Self-organizing list • Doubly connected edge • Skip list list • Unrolled linked list • Difference list • VList Lists: Array 0 1 size MAX_SIZE-1 3 6 7 5 2 L = int[MAX_SIZE] -
The Hexadecimal Number System and Memory Addressing
C5537_App C_1107_03/16/2005 APPENDIX C The Hexadecimal Number System and Memory Addressing nderstanding the number system and the coding system that computers use to U store data and communicate with each other is fundamental to understanding how computers work. Early attempts to invent an electronic computing device met with disappointing results as long as inventors tried to use the decimal number sys- tem, with the digits 0–9. Then John Atanasoff proposed using a coding system that expressed everything in terms of different sequences of only two numerals: one repre- sented by the presence of a charge and one represented by the absence of a charge. The numbering system that can be supported by the expression of only two numerals is called base 2, or binary; it was invented by Ada Lovelace many years before, using the numerals 0 and 1. Under Atanasoff’s design, all numbers and other characters would be converted to this binary number system, and all storage, comparisons, and arithmetic would be done using it. Even today, this is one of the basic principles of computers. Every character or number entered into a computer is first converted into a series of 0s and 1s. Many coding schemes and techniques have been invented to manipulate these 0s and 1s, called bits for binary digits. The most widespread binary coding scheme for microcomputers, which is recog- nized as the microcomputer standard, is called ASCII (American Standard Code for Information Interchange). (Appendix B lists the binary code for the basic 127- character set.) In ASCII, each character is assigned an 8-bit code called a byte. -
File I/O Stream Byte Stream
File I/O In Java, we can read data from files and also write data in files. We do this using streams. Java has many input and output streams that are used to read and write data. Same as a continuous flow of water is called water stream, in the same way input and output flow of data is called stream. Stream Java provides many input and output stream classes which are used to read and write. Streams are of two types. Byte Stream Character Stream Let's look at the two streams one by one. Byte Stream It is used in the input and output of byte. We do this with the help of different Byte stream classes. Two most commonly used Byte stream classes are FileInputStream and FileOutputStream. Some of the Byte stream classes are listed below. Byte Stream Description BufferedInputStream handles buffered input stream BufferedOutputStrea handles buffered output stream m FileInputStream used to read from a file FileOutputStream used to write to a file InputStream Abstract class that describe input stream OutputStream Abstract class that describe output stream Byte Stream Classes are in divided in two groups - InputStream Classes - These classes are subclasses of an abstract class, InputStream and they are used to read bytes from a source(file, memory or console). OutputStream Classes - These classes are subclasses of an abstract class, OutputStream and they are used to write bytes to a destination(file, memory or console). InputStream InputStream class is a base class of all the classes that are used to read bytes from a file, memory or console. -
Specification of Bit Handling Routines AUTOSAR CP Release 4.3.1
Specification of Bit Handling Routines AUTOSAR CP Release 4.3.1 Document Title Specification of Bit Handling Routines Document Owner AUTOSAR Document Responsibility AUTOSAR Document Identification No 399 Document Status Final Part of AUTOSAR Standard Classic Platform Part of Standard Release 4.3.1 Document Change History Date Release Changed by Change Description 2017-12-08 4.3.1 AUTOSAR Addition on mnemonic for boolean Release as “u8”. Management Editorial changes 2016-11-30 4.3.0 AUTOSAR Removal of the requirement Release SWS_Bfx_00204 Management Updation of MISRA violation com- ment format Updation of unspecified value range for BitPn, BitStartPn, BitLn and ShiftCnt Clarifications 1 of 42 Document ID 399: AUTOSAR_SWS_BFXLibrary - AUTOSAR confidential - Specification of Bit Handling Routines AUTOSAR CP Release 4.3.1 Document Change History Date Release Changed by Change Description 2015-07-31 4.2.2 AUTOSAR Updated SWS_Bfx_00017 for the Release return type of Bfx_GetBit function Management from 1 and 0 to TRUE and FALSE Updated chapter 8.1 for the defini- tion of bit addressing and updated the examples of Bfx_SetBit, Bfx_ClrBit, Bfx_GetBit, Bfx_SetBits, Bfx_CopyBit, Bfx_PutBits, Bfx_PutBit Updated SWS_Bfx_00017 for the return type of Bfx_GetBit function from 1 and 0 to TRUE and FALSE without changing the formula Updated SWS_Bfx_00011 and SWS_Bfx_00022 for the review comments provided for the exam- ples In Table 2, replaced Boolean with boolean In SWS_Bfx_00029, in example re- placed BFX_GetBits_u16u8u8_u16 with Bfx_GetBits_u16u8u8_u16 2014-10-31 4.2.1 AUTOSAR Correct usage of const in function Release declarations Management Editoral changes 2014-03-31 4.1.3 AUTOSAR Editoral changes Release Management 2013-10-31 4.1.2 AUTOSAR Improve description of how to map Release functions to C-files Management Improve the definition of error classi- fication Editorial changes 2013-03-15 4.1.1 AUTOSAR Change return value of Test Bit API Administration to boolean. -
C++ Input/Output: Streams 4
C++ Input/Output: Streams 4. Input/Output 1 The basic data type for I/O in C++ is the stream. C++ incorporates a complex hierarchy of stream types. The most basic stream types are the standard input/output streams: istream cin built-in input stream variable; by default hooked to keyboard ostream cout built-in output stream variable; by default hooked to console header file: <iostream> C++ also supports all the input/output mechanisms that the C language included. However, C++ streams provide all the input/output capabilities of C, with substantial improvements. We will exclusively use streams for input and output of data. Computer Science Dept Va Tech August, 2001 Intro Programming in C++ ©1995-2001 Barnette ND & McQuain WD C++ Streams are Objects 4. Input/Output 2 The input and output streams, cin and cout are actually C++ objects. Briefly: class: a C++ construct that allows a collection of variables, constants, and functions to be grouped together logically under a single name object: a variable of a type that is a class (also often called an instance of the class) For example, istream is actually a type name for a class. cin is the name of a variable of type istream. So, we would say that cin is an instance or an object of the class istream. An instance of a class will usually have a number of associated functions (called member functions) that you can use to perform operations on that object or to obtain information about it. The following slides will present a few of the basic stream member functions, and show how to go about using member functions. -
Subtyping, Declaratively an Exercise in Mixed Induction and Coinduction
Subtyping, Declaratively An Exercise in Mixed Induction and Coinduction Nils Anders Danielsson and Thorsten Altenkirch University of Nottingham Abstract. It is natural to present subtyping for recursive types coin- ductively. However, Gapeyev, Levin and Pierce have noted that there is a problem with coinductive definitions of non-trivial transitive inference systems: they cannot be \declarative"|as opposed to \algorithmic" or syntax-directed|because coinductive inference systems with an explicit rule of transitivity are trivial. We propose a solution to this problem. By using mixed induction and coinduction we define an inference system for subtyping which combines the advantages of coinduction with the convenience of an explicit rule of transitivity. The definition uses coinduction for the structural rules, and induction for the rule of transitivity. We also discuss under what condi- tions this technique can be used when defining other inference systems. The developments presented in the paper have been mechanised using Agda, a dependently typed programming language and proof assistant. 1 Introduction Coinduction and corecursion are useful techniques for defining and reasoning about things which are potentially infinite, including streams and other (poten- tially) infinite data types (Coquand 1994; Gim´enez1996; Turner 2004), process congruences (Milner 1990), congruences for functional programs (Gordon 1999), closures (Milner and Tofte 1991), semantics for divergence of programs (Cousot and Cousot 1992; Hughes and Moran 1995; Leroy and Grall 2009; Nakata and Uustalu 2009), and subtyping relations for recursive types (Brandt and Henglein 1998; Gapeyev et al. 2002). However, the use of coinduction can lead to values which are \too infinite”. For instance, a non-trivial binary relation defined as a coinductive inference sys- tem cannot include the rule of transitivity, because a coinductive reading of transitivity would imply that every element is related to every other (to see this, build an infinite derivation consisting solely of uses of transitivity). -
RISC-V Bitmanip Extension Document Version 0.90
RISC-V Bitmanip Extension Document Version 0.90 Editor: Clifford Wolf Symbiotic GmbH [email protected] June 10, 2019 Contributors to all versions of the spec in alphabetical order (please contact editors to suggest corrections): Jacob Bachmeyer, Allen Baum, Alex Bradbury, Steven Braeger, Rogier Brussee, Michael Clark, Ken Dockser, Paul Donahue, Dennis Ferguson, Fabian Giesen, John Hauser, Robert Henry, Bruce Hoult, Po-wei Huang, Rex McCrary, Lee Moore, Jiˇr´ıMoravec, Samuel Neves, Markus Oberhumer, Nils Pipenbrinck, Xue Saw, Tommy Thorn, Andrew Waterman, Thomas Wicki, and Clifford Wolf. This document is released under a Creative Commons Attribution 4.0 International License. Contents 1 Introduction 1 1.1 ISA Extension Proposal Design Criteria . .1 1.2 B Extension Adoption Strategy . .2 1.3 Next steps . .2 2 RISC-V Bitmanip Extension 3 2.1 Basic bit manipulation instructions . .4 2.1.1 Count Leading/Trailing Zeros (clz, ctz)....................4 2.1.2 Count Bits Set (pcnt)...............................5 2.1.3 Logic-with-negate (andn, orn, xnor).......................5 2.1.4 Pack two XLEN/2 words in one register (pack).................6 2.1.5 Min/max instructions (min, max, minu, maxu)................7 2.1.6 Single-bit instructions (sbset, sbclr, sbinv, sbext)............8 2.1.7 Shift Ones (Left/Right) (slo, sloi, sro, sroi)...............9 2.2 Bit permutation instructions . 10 2.2.1 Rotate (Left/Right) (rol, ror, rori)..................... 10 2.2.2 Generalized Reverse (grev, grevi)....................... 11 2.2.3 Generalized Shuffleshfl ( , unshfl, shfli, unshfli).............. 14 2.3 Bit Extract/Deposit (bext, bdep)............................ 22 2.4 Carry-less multiply (clmul, clmulh, clmulr).................... -
KTS-A Memory Management Control User's Guide Digital Equipment Corporation • Maynard, Massachusetts
--- KTS-A memory management control user's guide E K- KTOSA-U G-001 digital equipment corporation • maynard, massachusetts 1st Edition , July 1978 Copyright © 1978 by Digital Equipment Corporation The material in this manual is for informational purposes and is subject to change without notice. Digital Equipment Corporation assumes no responsibility for any errors which may appear in this manual. Printed in U.S.A. This document was set on DIGITAL's DECset-8000 com puterized typesetting system. The following are trademarks of Digital Equipment Corporation, Maynard, Massachusetts: DIGITAL D ECsystem-10 MASSBUS DEC DECSYSTEM-20 OMNIBUS POP DIBOL OS/8 DECUS EDUSYSTEM RSTS UNI BUS VAX RSX VMS IAS CONTENTS Page CHAPTER 1 INTRODUCTION 1 . 1 SCOPE OF MANUAL ..................................................................................................................... 1-1 1.2 GENERAL DESCRI PTION ............................................................................................................. 1-1 1 .3 KT8-A SPECIFICATION S.............................................................................................................. 1-3 1.4 RELATED DOCUMENTS ............................................................................................................... 1-4 1 .5 SOFTWARE ..................................................................................................................................... 1-5 1.5.1 Diagnostic .............................................................................................................................