Lecture 2: History
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Elementary Functions: Towards Automatically Generated, Efficient
Elementary functions : towards automatically generated, efficient, and vectorizable implementations Hugues De Lassus Saint-Genies To cite this version: Hugues De Lassus Saint-Genies. Elementary functions : towards automatically generated, efficient, and vectorizable implementations. Other [cs.OH]. Université de Perpignan, 2018. English. NNT : 2018PERP0010. tel-01841424 HAL Id: tel-01841424 https://tel.archives-ouvertes.fr/tel-01841424 Submitted on 17 Jul 2018 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. Délivré par l’Université de Perpignan Via Domitia Préparée au sein de l’école doctorale 305 – Énergie et Environnement Et de l’unité de recherche DALI – LIRMM – CNRS UMR 5506 Spécialité: Informatique Présentée par Hugues de Lassus Saint-Geniès [email protected] Elementary functions: towards automatically generated, efficient, and vectorizable implementations Version soumise aux rapporteurs. Jury composé de : M. Florent de Dinechin Pr. INSA Lyon Rapporteur Mme Fabienne Jézéquel MC, HDR UParis 2 Rapporteur M. Marc Daumas Pr. UPVD Examinateur M. Lionel Lacassagne Pr. UParis 6 Examinateur M. Daniel Menard Pr. INSA Rennes Examinateur M. Éric Petit Ph.D. Intel Examinateur M. David Defour MC, HDR UPVD Directeur M. Guillaume Revy MC UPVD Codirecteur À la mémoire de ma grand-mère Françoise Lapergue et de Jos Perrot, marin-pêcheur bigouden. -
Reconfigurable Embedded Control Systems: Problems and Solutions
RECONFIGURABLE EMBEDDED CONTROL SYSTEMS: PROBLEMS AND SOLUTIONS By Dr.rer.nat.Habil. Mohamed Khalgui ⃝c Copyright by Dr.rer.nat.Habil. Mohamed Khalgui, 2012 v Martin Luther University, Germany Research Manuscript for Habilitation Diploma in Computer Science 1. Reviewer: Prof.Dr. Hans-Michael Hanisch, Martin Luther University, Germany, 2. Reviewer: Prof.Dr. Georg Frey, Saarland University, Germany, 3. Reviewer: Prof.Dr. Wolf Zimmermann, Martin Luther University, Germany, Day of the defense: Monday January 23rd 2012, Table of Contents Table of Contents vi English Abstract x German Abstract xi English Keywords xii German Keywords xiii Acknowledgements xiv Dedicate xv 1 General Introduction 1 2 Embedded Architectures: Overview on Hardware and Operating Systems 3 2.1 Embedded Hardware Components . 3 2.1.1 Microcontrollers . 3 2.1.2 Digital Signal Processors (DSP): . 4 2.1.3 System on Chip (SoC): . 5 2.1.4 Programmable Logic Controllers (PLC): . 6 2.2 Real-Time Embedded Operating Systems (RTOS) . 8 2.2.1 QNX . 9 2.2.2 RTLinux . 9 2.2.3 VxWorks . 9 2.2.4 Windows CE . 10 2.3 Known Embedded Software Solutions . 11 2.3.1 Simple Control Loop . 12 2.3.2 Interrupt Controlled System . 12 2.3.3 Cooperative Multitasking . 12 2.3.4 Preemptive Multitasking or Multi-Threading . 12 2.3.5 Microkernels . 13 2.3.6 Monolithic Kernels . 13 2.3.7 Additional Software Components: . 13 2.4 Conclusion . 14 3 Embedded Systems: Overview on Software Components 15 3.1 Basic Concepts of Components . 15 3.2 Architecture Description Languages . 17 3.2.1 Acme Language . -
YANLI: a Powerful Natural Language Front-End Tool
AI Magazine Volume 8 Number 1 (1987) (© AAAI) John C. Glasgow I1 YANLI: A Powerful Natural Language Front-End Tool An important issue in achieving acceptance of computer sys- Since first proposed by Woods (1970), ATNs have be- tems used by the nonprogramming community is the ability come a popular method of defining grammars for natural to communicate with these systems in natural language. Of- language parsing programs. This popularity is due to the ten, a great deal of time in the design of any such system is flexibility with which ATNs can be applied to hierarchically devoted to the natural language front end. An obvious way to describable phenomenon and to their power, which is that of simplify this task is to provide a portable natural language a universal Turing machine. As discussed later, a grammar front-end tool or facility that is sophisticated enough to allow in the form of an ATN (written in LISP) is more informative for a reasonable variety of input; allows modification; and, than a grammar in Backus-Naur notation. As an example, yet, is easy to use. This paper describes such a tool that is the first few lines of a grammar for an English sentence writ- based on augmented transition networks (ATNs). It allows ten in Backus-Naur notation might look like the following: for user input to be in sentence or nonsentence form or both, provides a detailed parse tree that the user can access, and sentence : := [subject] predicate also provides the facility to generate responses and save in- subject ::= noun-group formation. -
Turing's Influence on Programming — Book Extract from “The Dawn of Software Engineering: from Turing to Dijkstra”
Turing's Influence on Programming | Book extract from \The Dawn of Software Engineering: from Turing to Dijkstra" Edgar G. Daylight∗ Eindhoven University of Technology, The Netherlands [email protected] Abstract Turing's involvement with computer building was popularized in the 1970s and later. Most notable are the books by Brian Randell (1973), Andrew Hodges (1983), and Martin Davis (2000). A central question is whether John von Neumann was influenced by Turing's 1936 paper when he helped build the EDVAC machine, even though he never cited Turing's work. This question remains unsettled up till this day. As remarked by Charles Petzold, one standard history barely mentions Turing, while the other, written by a logician, makes Turing a key player. Contrast these observations then with the fact that Turing's 1936 paper was cited and heavily discussed in 1959 among computer programmers. In 1966, the first Turing award was given to a programmer, not a computer builder, as were several subsequent Turing awards. An historical investigation of Turing's influence on computing, presented here, shows that Turing's 1936 notion of universality became increasingly relevant among programmers during the 1950s. The central thesis of this paper states that Turing's in- fluence was felt more in programming after his death than in computer building during the 1940s. 1 Introduction Many people today are led to believe that Turing is the father of the computer, the father of our digital society, as also the following praise for Martin Davis's bestseller The Universal Computer: The Road from Leibniz to Turing1 suggests: At last, a book about the origin of the computer that goes to the heart of the story: the human struggle for logic and truth. -
Church-Turing Thesis: Every Function F: {0,1}* -> {0,1}* Which Is "Effectively Computable" Is Computable by a Turing Machine
Church-Turing Thesis: Every function f: {0,1}* -> {0,1}* which is "effectively computable" is computable by a Turing Machine. Observation: Every Turing Machine (equivalently, every python program, or evey program in your favorite language) M can be encoded by a finite binary string #M. Moreover, our encoding guarantees #M != #M' whenever M and M' are different Turing Machines (different programs). Recall: Every finite binary string can be thought of as a natural number written in binary, and vice versa. Therefore, we can think of #M as a natural number. E.g. If #M = 1057, then we are talking about the 1057th Turing Machine, or 1057th python program. Intuitive takeaway: At most, there are as many different Turing Machines (Programs) as there are natural numbers. We will now show that some (in fact most) decision problems f: {0,1}* -> {0,1} are not computable by a TM (python program). If a decision problem is not comptuable a TM/program then we say it is "undecidable". Theorem: There are functions from {0,1}* to {0,1} which are not computable by a Turing Machine (We say, undecidable). Corollary: Assuming the CT thesis, there are functions which are not "effectively computable". Proof of Theorem: - Recall that we can think of instead of of {0,1}* - "How many" functions f: -> {0,1} are there? - We can think of each each such function f as an infinite binary string - For each x in (0,1), we can write its binary expansion as an infinite binary string to the right of a decimal point - The string to the right of the decimal point can be interpreted as a function f_x from natural numbers to {0,1} -- f_x(i) = ith bit of x to the right of the decimal point - In other words: for each x in (0,1) we get a different function f_x from natural numbers to {0,1}, so there are at least as many decision problems as there are numbers in (0,1). -
Computers Friday, February 12, 2021 11:00 AM
1 Introduction: Computers Friday, February 12, 2021 11:00 AM Welcome! CMSC 240 - Principles of Computer Organization Class website: https://cs.brynmawr.edu/Courses/cs240/Spring2021/ What is a computer? A device with • A processor (CPU - Central Processing Unit) • Storage/memory (RAM, Disk, USB Stick) • A keyboard • A mouse • A monitor • A printer Not all computers have all of the above. Except the CPU and memory. Japan's Fugaku Supercomputer is one of the world's fastest computer as of Summer 2020. Performance is over 400 petaflops (over a million times faster than the desktop shown on the right). Question: What was the first ever computer? 240 Lectures Page 1 1 Computers - Old & New Friday, February 12, 2021 11:00 AM The Difference Engine #2: A Mechanical Computer ENIAC Electronic Numerical Integrator and Computer February 15, 1946. ENIAC Day is this week! https://eniacday.org/ Check it out. Question: What is the difference between the ENIAC, the Apple Mac, the Iphone, and the Fugaku??? 240 Lectures Page 2 1 Turing Machines Friday, February 12, 2021 11:00 AM 1937: Alan M. Turing Turing Machine [A mathematical abstraction of mechanical computation.] Turing Machines for adding and multiplying Universal Turing Machine Church-Turing Thesis (tl;dr) Anything that can be computed can be computed by a Turing machine. Key Idea: A computer is essentially a Turing Machine. A computer is a universal computing device. 240 Lectures Page 3 1 Put on Watch List… Friday, February 12, 2021 8:55 AM 240 Lectures Page 4 1 von Neumann Architecture Friday, February 12, 2021 11:00 AM John von Neumann, 1945 Stored Program Computers Aka von Neumann Architecture Most computers today are based on this architecture. -
Vax 6135 Car Vax Uk - Service Parts List
VAX 6135 CAR VAX UK - SERVICE PARTS LIST Item Vax Part No. Description Price Code Service Item Item Vax Part No. Description Price Code Service Item 2 1-2-31-01-006 FILTER-FOAM-EXHAUST S1 CS 34 1-2-30-01-015 SEAL-FILTER/RESERVOIR K1 S 5 1-2-11-04-007 CABLE CLAMP L1 CS 35 1-3-15-03-007 FILTER HSG ASSY-UNIV-BLACK T3 S 29 1-2-31-01-002 FILTER DISC-BONDINI A1 CS 39 1-2-14-02-001 BALL VALVE N1 S 32 1-2-31-01-007 FILTER -FIBRE-MOULDED X1 CS 40 1-3-09-06-007 RESERVOIR ASSY-UNIV-BLACK W3 S 44 1-3-13-02-001 UPHOLSTERY TOOL Y1 CS 41 1-2-30-02-002 SEAL-CONICAL DUCT D2 S 47 1-2-39-01-010 CREVICE TOOL Y1 CS 42 1-2-30-02-003 SEAL-EXHAUST D2 S 48 1-3-13-01-001 DUSTBRUSH H2 CS 43 1-2-124731-12 RECOVERY BUCKET/SPIDER ASSY Z3 S 50 1-2-13-02-002 TUBE-EXTN-STAINLESS B3 CS 45 1-2-32-01-002 CASTOR-TWO WHEEL X1 S 52 1-3-18-01-022 HOSE & GRIP ASSY W3 CS 60 1-9-124423-00 TUBE-PUMP TO QRV A1 S 53 1-9-124962-00 WASH HEAD J3 CS 62 1-1-06-01-073 FEMALE QRV ASSY S2 S 54 1-9-124961-00 FLOOR BRUSH F3 CS 63 1-3-124422-00 ELBOW-QRV-ET408 C2 S 64 1-2-11-03-007 RETAINER CLIP-SPRING H1 CS 65 1-2-13-04-008 INLET TUBE-PVC A1 S 74 1-2-124594-00 UPHOLSTERY WASH TOOL K3 CS 66 1-3-124424-00 FIXING STRAP-ET408 L1 S 75 1-9-125226-00 TURBO TOOL-100mm R3 CS 67 1-7-124677-00 FILTER-WATER-INLET E2 S 77 1-9-125549-00 CREVICE TOOL-EXTRA LONG G2 CS 68 1-5-124419-00 PUMP-ET408 S3 S 101 1-2-124805-00 WATER TUBE ASSY-STRAIGHT Z2 CS 69 1-6-124425-00 SEAL-PUMP ET408 L1 S 3 1-3-124588-03 COVER-ACCESS-B R GREEN X1 NS 99 1-2-07-03-001 DUCT-CONICAL X1 S 6 1-2-36-04-004 CORD PROTECTOR A1 NS 102 -
CS 6290 Chapter 1
Spring 2011 Prof. Hyesoon Kim Xbox 360 System Architecture, „Anderews, Baker • 3 CPU cores – 4-way SIMD vector units – 8-way 1MB L2 cache (3.2 GHz) – 2 way SMT • 48 unified shaders • 3D graphics units • 512-Mbyte DRAM main memory • FSB (Front-side bus): 5.4 Gbps/pin/s (16 pins) • 10.8 Gbyte/s read and write • Xbox 360: Big endian • Windows: Little endian http://msdn.microsoft.com/en-us/library/cc308005(VS.85).aspx • L2 cache : – Greedy allocation algorithm – Different workloads have different working set sizes • 2-way 32 Kbyte L1 I-cache • 4-way 32 Kbyte L1 data cache • Write through, no write allocation • Cache block size :128B (high spatial locality) • 2-way SMT, • 2 insts/cycle, • In-order issue • Separate vector/scalar issue queue (VIQ) Vector Vector Execution Unit Instructions Scalar Scalar Execution Unit • First game console by Microsoft, released in 2001, $299 Glorified PC – 733 Mhz x86 Intel CPU, 64MB DRAM, NVIDIA GPU (graphics) – Ran modified version of Windows OS – ~25 million sold • XBox 360 – Second generation, released in 2005, $299-$399 – All-new custom hardware – 3.2 Ghz PowerPC IBM processor (custom design for XBox 360) – ATI graphics chip (custom design for XBox 360) – 34+ million sold (as of 2009) • Design principles of XBox 360 [Andrews & Baker] - Value for 5-7 years -!ig performance increase over last generation - Support anti-aliased high-definition video (720*1280*4 @ 30+ fps) - extremely high pixel fill rate (goal: 100+ million pixels/s) - Flexible to suit dynamic range of games - balance hardware, homogenous resources - Programmability (easy to program) Slide is from http://www.cis.upenn.edu/~cis501/lectures/12_xbox.pdf • Code name of Xbox 360‟s core • Shared cell (playstation processor) ‟s design philosophy. -
Universal Turing Machine
15-251 Great Theoretical Ideas in Computer Science Lecture 21 - Dan Kilgallin Turing Machines Goals Describe the nature of computation Mathematically formalize the behavior of a program running on a computer system Compare the capabilities of different programming languages Turing Machines What can we do to make a DFA better? Idea: Give it some memory! How much memory? Infinite! What kind of memory? Sequential access (e. g. CD, hard drive) or RAM? An infinite amount of RAM requires remembering really big numbers and needlessly complicates proofs Turing Machines: Definition A Turing Machine consists of A DFA to store the machine state, called the controller An array that is infinitely long in both directions, called the tape A pointer to some particular cell in the array, called the head Operation The head begins at cell 0 on the tape The DFA begins in some initial state Symbols from some alphabet are written on a finite portion of the tape, beginning at cell 1 Operation At each step, the machine uses as input: The state of the controller The symbol written on the cell which the head is at Using this, the machine will: Transition to some state in the DFA (possibly the same state) Write some symbol (possibly the same symbol) on the tape Move the head left or right one cell Two Flavors! The machine will stop computation if the DFA enters one of a pre-defined set of "halting" states A "decision" machine will, if it reaches a halting state, output either "Yes" or "No" (i.e. there are "accepting" and "rejecting" halt states) A "function" machine will, if it reaches a halting state, have some string of symbols written on the tape. -
MPC5634M Microcontroller Data Sheet, Rev
Freescale Semiconductor MPC5634M Rev. 9.2, 01/2015 MPC5634M Microcontroller Datasheet This is the MPC5634M Datasheet set consisting of the following files: • MPC5634M Datasheet Addendum (MPC5634M_AD), Rev. 1 • MPC5634M Datasheet (MPC5634M), Rev. 9 © Freescale Semiconductor, Inc., 2015. All rights reserved. Freescale Semiconductor MPC5634M_AD Datasheet Addendum Rev. 1.0, 01/2015 MPC5634M Microcontroller Datasheet Addendum This addendum describes corrections to the MPC5634M Table of Contents Microcontroller Datasheet, order number MPC5634M. 1 Addendum List for Revision 9 . 2 For convenience, the addenda items are grouped by 2 Revision History . 2 revision. Please check our website at http://www.freescale.com/powerarchitecture for the latest updates. The current version available of the MPC5634M Microcontroller Datasheet is Revision 9. © Freescale Semiconductor, Inc., 2015. All rights reserved. 1 Addendum List for Revision 9 4 Table 1. MPC5634M Rev 9 Addendum Location Description Section 4.11, “Temperature In “Temperature Sensor Electrical Characteristics” table, update the Min and Max value of Sensor Electrical “Accuracy” parameter to -20oC and +20oC, respectively. Characteristics”, Page 81 2 Revision History Table 2 provides a revision history for this datasheet addendum document. Table 2. Revision History Table Rev. Number Substantive Changes Date of Release 1.0 Initial release. 12/2014 MPC5634M_AD, Rev. 1.0 2 Freescale Semiconductor How to Reach Us: Information in this document is provided solely to enable system and software Home Page: implementers to use Freescale products. There are no express or implied copyright freescale.com licenses granted hereunder to design or fabricate any integrated circuits based on the Web Support: information in this document. freescale.com/support Freescale reserves the right to make changes without further notice to any products herein. -
Automated Synthesis of Symbolic Instruction Encodings from I/O Samples
Automated Synthesis of Symbolic Instruction Encodings from I/O Samples Patrice Godefroid Ankur Taly Microsoft Research Stanford University PLDI’2012 Page 1 June 2012 Need for Symbolic Instruction Encodings Symbolic Execution is a key l 1 : m o v eax, i n p 1 component of precise binary m o v c l , i n p 2 program analysis tools s h l eax, c l j n z l2 j m p l3 - SAGE, BitBlaze, BAP, etc. l 2 : d i v ebx, eax // Is this safe ? - Static analysis tools / / I s e a x ! = 0 ? l 3 : … PLDI’2012 Page 2 June 2012 Problem: Symbolic Instruction Encoding Bit Vector[X] Instruction Bit Vector[Y] Inp 1 ? Op1 Inpn Opm Problem: Given a processor and an instruction name, symbolically describe the input-output function for the instruction • Express the encoding as bit-vector constraints (ex: SMT-Lib format) PLDI’2012 Page 3 June 2012 So far, only manual solutions… • From the instruction architecture manual (X86, ARM, …) implemented by the processor Limitations: • Tedious, expensive - X86 has more than 300 unique instructions, each with ~10 OPCodes, 2000 pages • Error-prone - Written in English, many corner cases • Imprecise - Spec is often under-specified • Partial - Not all instructions are covered X86 spec for SHLD • Can we trust the spec ? PLDI’2012 Page 4 June 2012 Here: Automated Synthesis Approach Searches for a function f that respects truth table Partial Truth- table S Sample inputs Synthesis Function (C with in-lined engine f assembly) Goals: • As automated as possible so that we can boot-strap a symbolic execution engine on an arbitrary instruction -
Sources a Brief History of Computer Science ●Schneider and Gersting, an Invitation to Computer Science ●Primary Source CSCE 181, Yoonsuck Choe ●Slides from Prof
* Sources A Brief History of Computer Science ●Schneider and Gersting, An Invitation to Computer Science ●primary source CSCE 181, Yoonsuck Choe ●Slides from Prof. John Keyser Slides with dark blue background header: Prof. Jennifer Welch’s slides ●American University’s Computing History Museum • ●http://www.computinghistorymuseum.org/ from Spring 2010 CSCE 181. ●Virginia Tech’s History of Computing website: ●http://ei.cs.vt.edu/~history Slides with blank background: Yoonsuck Choe • ●Computer History Museum ●http://www.computerhistory.org/ ●IEEE Annals of the History of Computing (Journal) ●http://www.computer.org/portal/site/annals/index.jsp ●Andrew Hodges’ website about Alan Turing ●http://http://www.turing.org.uk/turing/index.html * More Sources Early Mathematics & Computation ●Babylonians and Egyptians, > 3000 yrs ago James Burke, Connections, MacMillan: London, 1978. • ●numerical methods for generating tables of square Photos taken by Yoonsuck Choe at the Computer History roots, multiplication, trig • ●Applications: navigation, agriculture, taxation Museum in Mountainview, CA. December 2011. ●Greeks, > 3000 yrs ago ●geometry and logic ●Indians, ~ 600 AD ●started using placeholders and a decimal number system, similar to modern ●idea spread to Middle East ●Arabs and Persians ~ 800 AD ●algorithms * * A Famous Arab Mathematician Abu Jafar Mohammed Ibn Musa Al-Khowarizmi Early Computing Devices ●In early 800s AD ●Abacus ●Worked at center of learning in Baghdad ●About 3000 BC ●Wrote book: Hisab Al Jabr Wal- ●Different types, developed