10. Assembly Language, Models of Computation
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System Design for a Computational-RAM Logic-In-Memory Parailel-Processing Machine
System Design for a Computational-RAM Logic-In-Memory ParaIlel-Processing Machine Peter M. Nyasulu, B .Sc., M.Eng. A thesis submitted to the Faculty of Graduate Studies and Research in partial fulfillment of the requirements for the degree of Doctor of Philosophy Ottaw a-Carleton Ins titute for Eleceical and Computer Engineering, Department of Electronics, Faculty of Engineering, Carleton University, Ottawa, Ontario, Canada May, 1999 O Peter M. Nyasulu, 1999 National Library Biôiiothkque nationale du Canada Acquisitions and Acquisitions et Bibliographie Services services bibliographiques 39S Weiiington Street 395. nie WeUingtm OnawaON KlAW Ottawa ON K1A ON4 Canada Canada The author has granted a non- L'auteur a accordé une licence non exclusive licence allowing the exclusive permettant à la National Library of Canada to Bibliothèque nationale du Canada de reproduce, ban, distribute or seU reproduire, prêter, distribuer ou copies of this thesis in microform, vendre des copies de cette thèse sous paper or electronic formats. la forme de microficbe/nlm, de reproduction sur papier ou sur format électronique. The author retains ownership of the L'auteur conserve la propriété du copyright in this thesis. Neither the droit d'auteur qui protège cette thèse. thesis nor substantial extracts fkom it Ni la thèse ni des extraits substantiels may be printed or otherwise de celle-ci ne doivent être imprimés reproduced without the author's ou autrement reproduits sans son permission. autorisation. Abstract Integrating several 1-bit processing elements at the sense amplifiers of a standard RAM improves the performance of massively-paralle1 applications because of the inherent parallelism and high data bandwidth inside the memory chip. -
CS 2210: Theory of Computation
CS 2210: Theory of Computation Spring, 2019 Administrative Information • Background survey • Textbook: E. Rich, Automata, Computability, and Complexity: Theory and Applications, Prentice-Hall, 2008. • Book website: http://www.cs.utexas.edu/~ear/cs341/automatabook/ • My Office Hours: – Monday, 6:00-8:00pm, Searles 224 – Tuesday, 1:00-2:30pm, Searles 222 • TAs – Anjulee Bhalla: Hours TBA, Searles 224 – Ryan St. Pierre, Hours TBA, Searles 224 What you can expect from the course • How to do proofs • Models of computation • What’s the difference between computability and complexity? • What’s the Halting Problem? • What are P and NP? • Why do we care whether P = NP? • What are NP-complete problems? • Where does this make a difference outside of this class? • How to work the answers to these questions into the conversation at a cocktail party… What I will expect from you • Problem Sets (25%): – Goal: Problems given on Mondays and Wednesdays – Due the next Monday – Graded by following Monday – A learning tool, not a testing tool – Collaboration encouraged; more on this in next slide • Quizzes (15%) • Exams (2 non-cumulative, 30% each): – Closed book, closed notes, but… – Can bring in 8.5 x 11 page with notes on both sides • Class participation: Tiebreaker Other Important Things • Go to the TA hours • Study and work on problem sets in groups • Collaboration Issues: – Level 0 (In-Class Problems) • No restrictions – Level 1 (Homework Problems) • Verbal collaboration • But, individual write-ups – Level 2 (not used in this course) • Discussion with TAs only – Level 3 (Exams) • Professor clarifications only Right now… • What does it mean to study the “theory” of something? • Experience with theory in other disciplines? • Relationship to practice? – “In theory, theory and practice are the same. -
The Problem with Threads
The Problem with Threads Edward A. Lee Electrical Engineering and Computer Sciences University of California at Berkeley Technical Report No. UCB/EECS-2006-1 http://www.eecs.berkeley.edu/Pubs/TechRpts/2006/EECS-2006-1.html January 10, 2006 Copyright © 2006, by the author(s). All rights reserved. Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. To copy otherwise, to republish, to post on servers or to redistribute to lists, requires prior specific permission. Acknowledgement This work was supported in part by the Center for Hybrid and Embedded Software Systems (CHESS) at UC Berkeley, which receives support from the National Science Foundation (NSF award No. CCR-0225610), the State of California Micro Program, and the following companies: Agilent, DGIST, General Motors, Hewlett Packard, Infineon, Microsoft, and Toyota. The Problem with Threads Edward A. Lee Professor, Chair of EE, Associate Chair of EECS EECS Department University of California at Berkeley Berkeley, CA 94720, U.S.A. [email protected] January 10, 2006 Abstract Threads are a seemingly straightforward adaptation of the dominant sequential model of computation to concurrent systems. Languages require little or no syntactic changes to sup- port threads, and operating systems and architectures have evolved to efficiently support them. Many technologists are pushing for increased use of multithreading in software in order to take advantage of the predicted increases in parallelism in computer architectures. -
Dop – a Cpu Core for Teaching Basics of Computer Architecture
DOP – A CPU CORE FOR TEACHING BASICS OF COMPUTER ARCHITECTURE Milos Becvar, Alois Pluhacek and Jiri Danecek Department of Computer Science and Engineering Faculty of Electrical Engineering Czech Technical University in Prague, Abstract: A simple 16-bit processor core called DOP and its teaching environment is presented. The DOP processor illustrates the basic principles of computer organization and is therefore used in the introductory hardware course. Its major features are simplicity, availability of an FPGA implementation and a C compiler. This paper presents the description of the core, HW and SW tools and teaching methodology. computing performance. The DOP processor core was 1. INTRODUCTION developed at our department together with various SW and HW visualization tools (Danecek et al., 1994a). An introductory computer hardware course should teach students to the fundamental principles of computer The goal of this paper is to describe this processor core internal functionality. Students, who are familiar with and its learning environment for teaching basics of programming in high-level languages, are required to computer organization. The paper is organized as understand the interaction between a processor, a follows - section 2 outlines the introductory course and memory and I/O devices, an internal organization of characterizes the students, section 3 describes the DOP processor, computer arithmetic and basics of digital processor core, section 4 describes the SW and HW design. Our experience has shown that it is not an easy tools supporting this processor and finally section 5 task for most of them. The functionality of the processor outlines the use of the DOP in our introductory course. -
Computer Architecture: Dataflow (Part I)
Computer Architecture: Dataflow (Part I) Prof. Onur Mutlu Carnegie Mellon University A Note on This Lecture n These slides are from 18-742 Fall 2012, Parallel Computer Architecture, Lecture 22: Dataflow I n Video: n http://www.youtube.com/watch? v=D2uue7izU2c&list=PL5PHm2jkkXmh4cDkC3s1VBB7- njlgiG5d&index=19 2 Some Required Dataflow Readings n Dataflow at the ISA level q Dennis and Misunas, “A Preliminary Architecture for a Basic Data Flow Processor,” ISCA 1974. q Arvind and Nikhil, “Executing a Program on the MIT Tagged- Token Dataflow Architecture,” IEEE TC 1990. n Restricted Dataflow q Patt et al., “HPS, a new microarchitecture: rationale and introduction,” MICRO 1985. q Patt et al., “Critical issues regarding HPS, a high performance microarchitecture,” MICRO 1985. 3 Other Related Recommended Readings n Dataflow n Gurd et al., “The Manchester prototype dataflow computer,” CACM 1985. n Lee and Hurson, “Dataflow Architectures and Multithreading,” IEEE Computer 1994. n Restricted Dataflow q Sankaralingam et al., “Exploiting ILP, TLP and DLP with the Polymorphous TRIPS Architecture,” ISCA 2003. q Burger et al., “Scaling to the End of Silicon with EDGE Architectures,” IEEE Computer 2004. 4 Today n Start Dataflow 5 Data Flow Readings: Data Flow (I) n Dennis and Misunas, “A Preliminary Architecture for a Basic Data Flow Processor,” ISCA 1974. n Treleaven et al., “Data-Driven and Demand-Driven Computer Architecture,” ACM Computing Surveys 1982. n Veen, “Dataflow Machine Architecture,” ACM Computing Surveys 1986. n Gurd et al., “The Manchester prototype dataflow computer,” CACM 1985. n Arvind and Nikhil, “Executing a Program on the MIT Tagged-Token Dataflow Architecture,” IEEE TC 1990. -
Ece585 Lec2.Pdf
ECE 485/585 Microprocessor System Design Lecture 2: Memory Addressing 8086 Basics and Bus Timing Asynchronous I/O Signaling Zeshan Chishti Electrical and Computer Engineering Dept Maseeh College of Engineering and Computer Science Source: Lecture based on materials provided by Mark F. Basic I/O – Part I ECE 485/585 Outline for next few lectures Simple model of computation Memory Addressing (Alignment, Byte Order) 8088/8086 Bus Asynchronous I/O Signaling Review of Basic I/O How is I/O performed Dedicated/Isolated /Direct I/O Ports Memory Mapped I/O How do we tell when I/O device is ready or command complete? Polling Interrupts How do we transfer data? Programmed I/O DMA ECE 485/585 Simplified Model of a Computer Control Control Data, Address, Memory Data Path Microprocessor Keyboard Mouse [Fetch] Video display [Decode] Printer [Execute] I/O Device Hard disk drive Audio card Ethernet WiFi CD R/W DVD ECE 485/585 Memory Addressing Size of operands Bytes, words, long/double words, quadwords 16-bit half word (Intel: word) 32-bit word (Intel: doubleword, dword) 0x107 64-bit double word (Intel: quadword, qword) 0x106 Note: names are non-standard 0x105 SUN Sparc word is 32-bits, double is 64-bits 0x104 0x103 Alignment 0x102 Can multi-byte operands begin at any byte address? 0x101 Yes: non-aligned 0x100 No: aligned. Low order address bit(s) will be zero ECE 485/585 Memory Operand Alignment …Intel IA speak (i.e. word = 16-bits = 2 bytes) 0x107 0x106 0x105 0x104 0x103 0x102 0x101 0x100 Aligned Unaligned Aligned Unaligned Aligned Unaligned word word Double Double Quad Quad address address word word word word -----0 address address address address -----00 ----000 ECE 485/585 Memory Operand Alignment Why do we care? Unaligned memory references Can cause multiple memory bus cycles for a single operand May also span cache lines Requiring multiple evictions, multiple cache line fills Complicates memory system and cache controller design Some architectures restrict addresses to be aligned Even in architectures without alignment restrictions (e.g. -
Programmable Digital Microcircuits - a Survey with Examples of Use
- 237 - PROGRAMMABLE DIGITAL MICROCIRCUITS - A SURVEY WITH EXAMPLES OF USE C. Verkerk CERN, Geneva, Switzerland 1. Introduction For most readers the title of these lecture notes will evoke microprocessors. The fixed instruction set microprocessors are however not the only programmable digital mi• crocircuits and, although a number of pages will be dedicated to them, the aim of these notes is also to draw attention to other useful microcircuits. A complete survey of programmable circuits would fill several books and a selection had therefore to be made. The choice has rather been to treat a variety of devices than to give an in- depth treatment of a particular circuit. The selected devices have all found useful ap• plications in high-energy physics, or hold promise for future use. The microprocessor is very young : just over eleven years. An advertisement, an• nouncing a new era of integrated electronics, and which appeared in the November 15, 1971 issue of Electronics News, is generally considered its birth-certificate. The adver• tisement was for the Intel 4004 and its three support chips. The history leading to this announcement merits to be recalled. Intel, then a very young company, was working on the design of a chip-set for a high-performance calculator, for and in collaboration with a Japanese firm, Busicom. One of the Intel engineers found the Busicom design of 9 different chips too complicated and tried to find a more general and programmable solu• tion. His design, the 4004 microprocessor, was finally adapted by Busicom, and after further négociation, Intel acquired marketing rights for its new invention. -
Actor Model of Computation
Published in ArXiv http://arxiv.org/abs/1008.1459 Actor Model of Computation Carl Hewitt http://carlhewitt.info This paper is dedicated to Alonzo Church and Dana Scott. The Actor model is a mathematical theory that treats “Actors” as the universal primitives of concurrent digital computation. The model has been used both as a framework for a theoretical understanding of concurrency, and as the theoretical basis for several practical implementations of concurrent systems. Unlike previous models of computation, the Actor model was inspired by physical laws. It was also influenced by the programming languages Lisp, Simula 67 and Smalltalk-72, as well as ideas for Petri Nets, capability-based systems and packet switching. The advent of massive concurrency through client- cloud computing and many-core computer architectures has galvanized interest in the Actor model. An Actor is a computational entity that, in response to a message it receives, can concurrently: send a finite number of messages to other Actors; create a finite number of new Actors; designate the behavior to be used for the next message it receives. There is no assumed order to the above actions and they could be carried out concurrently. In addition two messages sent concurrently can arrive in either order. Decoupling the sender from communications sent was a fundamental advance of the Actor model enabling asynchronous communication and control structures as patterns of passing messages. November 7, 2010 Page 1 of 25 Contents Introduction ............................................................ 3 Fundamental concepts ............................................ 3 Illustrations ............................................................ 3 Modularity thru Direct communication and asynchrony ............................................................. 3 Indeterminacy and Quasi-commutativity ............... 4 Locality and Security ............................................ -
The Hpc C Compiler 2.1 Introduction
™ MICROCONTROLLER DEVELOPMENT SUPPORT ( MOLE HPC™ C COMPILER USER'S MANUAL ( ( ( ( ~ National Semiconductor Corporation Customer Order Number 424410883-001 NSC Publication Number 424410883-001C October 1988 HPC™ C Compiler User's Manual @l 1988 National Semiconductor Corporation 2900 Semiconductor Drive P.O. Box 58090 Santa Clara. California 95052-8090 CONTENTS Chapter 1 OVERVIEW 1.1 INTRODUCTION............................. 1-1 1.2 MANUAL ORGANIZATION. .. 1-2 1.3 DOCUMENTATION CONVENTIONS. .. 1-2 1.3.1 General Conventions . .. 1-2 1.3.2 Conventions in Syntax Descriptions ............. 1-2 1.3.3 Example Conventions. .. 1-3 1.3.4 Additional Conventions .................... 1-3 Chapter 2 THE HPC C COMPILER 2.1 INTRODUCTION............................. 2-1 2.2 COMPILER COMMAND SYNTAX 2-1 Chapter 3 BASIC DEFINITIONS 3.1 INTRODUCTION............................. 3-1 3.2 NAMES.................................. 3-1 3.3 CONSTANTS............................... 3-1 3.4 ESCAPE SEQUENCES . .. 3-2 3.5 COMMENTS............................... 3-3 3.6 DATA TYPES. .. 3-3 3.7 PREPROCESSOR DIRECTIVES . .. 3-4 3.8 PROGRAM ORGANIZATION. .. 3-4 3.9 INITIALIZATION OF VARIABLES . .. 3-4 3.10 OPERATORS . .. 3-5 3.11 IN-LINE MICROASSEMBLER CODE . .. 3-5 Chapter 4 IMPLEMENTATION-DEPENDENT CONSIDERATIONS 4.1 INTRODUCTION............................. 4-1 4.2 MEMORy................................. 4-1 4.3 STORAGE CLASSES . .. 4-1 4.3.1 Storage Class Modifiers. .. 4-1 4.4 C STACK FORMAT . .. 4-3 4.5 USING IN-LINE MICROASSEMBLER CODE. .. 4-4 4.6 EFFICIENCY CONSIDERATIONS . .. 4-6 4.6.1 Declaration Syntax . .. 4-9 4.7 STATEMENTS AND IMPLEMENTATION .............. 4-10 4.8 RUN-TIME NOTES ........................... 4-11 v Appendix A CCHPC SPECIFICATIONS Appendix B CONVERTING BETWEEN STANDARD C AND CCHPC Appendix C INVOCATION LINE SYNTAX C.l INTRODUCTION............................ -
Computer Architecture Lecture 1: Introduction and Basics Where We Are
Computer Architecture Lecture 1: Introduction and Basics Where we are “C” as a model of computation Programming Programmer’s view of a computer system works How does an assembly program end up executing as Architect/microarchitect’s view: digital logic? How to design a computer that meets system design goals. What happens in-between? Choices critically affect both How is a computer designed the SW programmer and using logic gates and wires the HW designer to satisfy specific goals? HW designer’s view of a computer system works CO Digital logic as a model of computation 2 Levels of Transformation “The purpose of computing is insight” (Richard Hamming) We gain and generate insight by solving problems How do we ensure problems are solved by electrons? Problem Algorithm Program/Language Runtime System (VM, OS, MM) ISA (Architecture) Microarchitecture Logic Circuits Electrons 3 The Power of Abstraction Levels of transformation create abstractions Abstraction: A higher level only needs to know about the interface to the lower level, not how the lower level is implemented E.g., high-level language programmer does not really need to know what the ISA is and how a computer executes instructions Abstraction improves productivity No need to worry about decisions made in underlying levels E.g., programming in Java vs. C vs. assembly vs. binary vs. by specifying control signals of each transistor every cycle Then, why would you want to know what goes on underneath or above? 4 Crossing the Abstraction Layers As long as everything goes well, not knowing what happens in the underlying level (or above) is not a problem. -
WCAE 2003 Workshop on Computer Architecture Education
WCAE 2003 Proceedings of the Workshop on Computer Architecture Education in conjunction with The 30th International Symposium on Computer Architecture DQG 2003 Federated Computing Research Conference Town and Country Resort and Convention Center b San Diego, California June 8, 2003 Workshop on Computer Architecture Education Sunday, June 8, 2003 Session 1. Welcome and Keynote 8:45–10:00 8:45 Welcome Edward F. Gehringer, workshop organizer 8:50 Keynote address, “Teaching and teaching computer Architecture: Two very different topics (Some opinions about each),” Yale Patt, teacher, University of Texas at Austin 1 Break 10:00–10:30 Session 2. Teaching with New Architectures 10:30–11:20 10:30 “Intel Itanium floating-point architecture,” Marius Cornea, John Harrison, and Ping Tak Peter Tang, Intel Corp. ................................................................................................................................. 5 10:50 “DOP — A CPU core for teaching basics of computer architecture,” Miloš BeþváĜ, Alois Pluháþek and JiĜí DanƟþek, Czech Technical University in Prague ................................................................. 14 11:05 Discussion Break 11:20–11:30 Session 3. Class Projects 11:30–12:30 11:30 “Superscalar out-of-order demystified in four instructions,” James C. Hoe, Carnegie Mellon University ......................................................................................................................................... 22 11:50 “Bridging the gap between undergraduate and graduate experience in -
A Model of Computation for VLSI with Related Complexity Results
A Model of Computation for VLSI with Related Complexity Results BERNARD CHAZELLE AND LOUIS MONIER Carnegie-Mellon University, Pittsburgh, Pennsylvania Abstract. A new model of computation for VLSI, based on the assumption that time for propagating information is at least linear in the distance, is proposed. While accommodating for basic laws of physics, the model is designed to be general and technology independent. Thus, from a complexity viewpoint, it is especially suited for deriving lower bounds and trade-offs. New results for a number of problems, including fan-in, transitive functions, matrix multiplication, and sorting are presented. As regards upper bounds, it must be noted that, because of communication costs, the model clearly favors regular and pipelined architectures (e.g., systolic arrays). Categories and Subject Descriptors: B.7.1 [Integrated Circuits]: Types and Design Styles-%91 (very- large-scale integration) General Terms: Algorithms, Theory Additional Key Words and Phrases: Chip complexity, lower bounds 1. Introduction The importance of having general models of computation for very-large-scale integration (VLSI) is apparent for various reasons, chief of which are the need for evaluating and comparing circuit performance, establishing lower bounds and trade-offs on area, time, and energy, and, more generally, building a complexity theory of VLSI computation. Although models must be simple and general enough to allow for mathematical analysis, they must also reflect reality regardless of the size of the circuit. We justify the latter claim by observing that if today’s circuits are still relatively small, the use of high-level design languages combined with larger integration, bigger chips, and improved yield may make asymptotic analysis quite relevant in the near future.