Theoretical & Logic Computing Models
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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. -
Edsger Dijkstra: the Man Who Carried Computer Science on His Shoulders
INFERENCE / Vol. 5, No. 3 Edsger Dijkstra The Man Who Carried Computer Science on His Shoulders Krzysztof Apt s it turned out, the train I had taken from dsger dijkstra was born in Rotterdam in 1930. Nijmegen to Eindhoven arrived late. To make He described his father, at one time the president matters worse, I was then unable to find the right of the Dutch Chemical Society, as “an excellent Aoffice in the university building. When I eventually arrived Echemist,” and his mother as “a brilliant mathematician for my appointment, I was more than half an hour behind who had no job.”1 In 1948, Dijkstra achieved remarkable schedule. The professor completely ignored my profuse results when he completed secondary school at the famous apologies and proceeded to take a full hour for the meet- Erasmiaans Gymnasium in Rotterdam. His school diploma ing. It was the first time I met Edsger Wybe Dijkstra. shows that he earned the highest possible grade in no less At the time of our meeting in 1975, Dijkstra was 45 than six out of thirteen subjects. He then enrolled at the years old. The most prestigious award in computer sci- University of Leiden to study physics. ence, the ACM Turing Award, had been conferred on In September 1951, Dijkstra’s father suggested he attend him three years earlier. Almost twenty years his junior, I a three-week course on programming in Cambridge. It knew very little about the field—I had only learned what turned out to be an idea with far-reaching consequences. a flowchart was a couple of weeks earlier. -
The Turing Approach Vs. Lovelace Approach
Connecting the Humanities and the Sciences: Part 2. Two Schools of Thought: The Turing Approach vs. The Lovelace Approach* Walter Isaacson, The Jefferson Lecture, National Endowment for the Humanities, May 12, 2014 That brings us to another historical figure, not nearly as famous, but perhaps she should be: Ada Byron, the Countess of Lovelace, often credited with being, in the 1840s, the first computer programmer. The only legitimate child of the poet Lord Byron, Ada inherited her father’s romantic spirit, a trait that her mother tried to temper by having her tutored in math, as if it were an antidote to poetic imagination. When Ada, at age five, showed a preference for geography, Lady Byron ordered that the subject be replaced by additional arithmetic lessons, and her governess soon proudly reported, “she adds up sums of five or six rows of figures with accuracy.” Despite these efforts, Ada developed some of her father’s propensities. She had an affair as a young teenager with one of her tutors, and when they were caught and the tutor banished, Ada tried to run away from home to be with him. She was a romantic as well as a rationalist. The resulting combination produced in Ada a love for what she took to calling “poetical science,” which linked her rebellious imagination to an enchantment with numbers. For many people, including her father, the rarefied sensibilities of the Romantic Era clashed with the technological excitement of the Industrial Revolution. Lord Byron was a Luddite. Seriously. In his maiden and only speech to the House of Lords, he defended the followers of Nedd Ludd who were rampaging against mechanical weaving machines that were putting artisans out of work. -
CODEBREAKING Suggested Reading List (Can Also Be Viewed Online at Good Reads)
MARSHALL LEGACY SERIES: CODEBREAKING Suggested Reading List (Can also be viewed online at Good Reads) NON-FICTION • Aldrich, Richard. Intelligence and the War against Japan. Cambridge: Cambridge University Press, 2000. • Allen, Robert. The Cryptogram Challenge: Over 150 Codes to Crack and Ciphers to Break. Philadelphia: Running Press, 2005 • Briggs, Asa. Secret Days Code-breaking in Bletchley Park. Barnsley: Frontline Books, 2011 • Budiansky, Stephen. Battle of Wits: The Complete Story of Codebreaking in World War Two. New York: Free Press, 2000. • Churchhouse, Robert. Codes and Ciphers: Julius Caesar, the Enigma, and the Internet. Cambridge: Cambridge University Press, 2001. • Clark, Ronald W. The Man Who Broke Purple. London: Weidenfeld and Nicholson, 1977. • Drea, Edward J. MacArthur's Ultra: Codebreaking and the War Against Japan, 1942-1945. Kansas: University of Kansas Press, 1992. • Fisher-Alaniz, Karen. Breaking the Code: A Father's Secret, a Daughter's Journey, and the Question That Changed Everything. Naperville, IL: Sourcebooks, 2011. • Friedman, William and Elizebeth Friedman. The Shakespearian Ciphers Examined. Cambridge: Cambridge University Press, 1957. • Gannon, James. Stealing Secrets, Telling Lies: How Spies and Codebreakers Helped Shape the Twentieth century. Washington, D.C.: Potomac Books, 2001. • Garrett, Paul. Making, Breaking Codes: Introduction to Cryptology. London: Pearson, 2000. • Hinsley, F. H. and Alan Stripp. Codebreakers: the inside story of Bletchley Park. Oxford: Oxford University Press, 1993. • Hodges, Andrew. Alan Turing: The Enigma. New York: Walker and Company, 2000. • Kahn, David. Seizing The Enigma: The Race to Break the German U-boat Codes, 1939-1943. New York: Barnes and Noble Books, 2001. • Kahn, David. The Codebreakers: The Comprehensive History of Secret Communication from Ancient Times to the Internet. -
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. -
An Early Program Proof by Alan Turing F
An Early Program Proof by Alan Turing F. L. MORRIS AND C. B. JONES The paper reproduces, with typographical corrections and comments, a 7 949 paper by Alan Turing that foreshadows much subsequent work in program proving. Categories and Subject Descriptors: 0.2.4 [Software Engineeringj- correctness proofs; F.3.1 [Logics and Meanings of Programs]-assertions; K.2 [History of Computing]-software General Terms: Verification Additional Key Words and Phrases: A. M. Turing Introduction The standard references for work on program proofs b) have been omitted in the commentary, and ten attribute the early statement of direction to John other identifiers are written incorrectly. It would ap- McCarthy (e.g., McCarthy 1963); the first workable pear to be worth correcting these errors and com- methods to Peter Naur (1966) and Robert Floyd menting on the proof from the viewpoint of subse- (1967); and the provision of more formal systems to quent work on program proofs. C. A. R. Hoare (1969) and Edsger Dijkstra (1976). The Turing delivered this paper in June 1949, at the early papers of some of the computing pioneers, how- inaugural conference of the EDSAC, the computer at ever, show an awareness of the need for proofs of Cambridge University built under the direction of program correctness and even present workable meth- Maurice V. Wilkes. Turing had been writing programs ods (e.g., Goldstine and von Neumann 1947; Turing for an electronic computer since the end of 1945-at 1949). first for the proposed ACE, the computer project at the The 1949 paper by Alan M. -
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. -
Alan Turing, Marshall Hall, and the Alignment of WW2 Japanese Naval Intercepts
Alan Turing, Marshall Hall, and the Alignment of WW2 Japanese Naval Intercepts Peter W. Donovan arshall Hall Jr. (1910–1990) is de- The statistician Edward Simpson led the JN-25 servedly well remembered for his team (“party”) at Bletchley Park from 1943 to 1945. role in constructing the simple group His now declassified general history [12] of this of order 604800 = 27 × 33 × 52 × 7 activity noted that, in November 1943: Mas well as numerous advances in [CDR Howard Engstrom, U.S.N.] gave us combinatorics. A brief autobiography is on pages the first news we had heard of a method 367–374 of Duran, Askey, and Merzbach [5]. Hall of testing the correctness of the relative notes that Howard Engstrom (1902–1962) gave setting of two messages using only the him much help with his Ph.D. thesis at Yale in property of divisibility by three of the code 1934–1936 and later urged him to work in Naval In- groups [5-groups is the usage of this paper]. telligence (actually in the foreign communications The method was known as Hall’s weights unit Op-20-G). and was a useful insurance policy just in I was in a research division and got to see case JN-25 ever became more difficult. He work in all areas, from the Japanese codes promised to send us a write-up of it. to the German Enigma machine which Alan The JN-25 series of ciphers, used by the Japanese Turing had begun to attack in England. I Navy (I.J.N.) from 1939 to 1945, was the most made significant results on both of these important source of communications intelligence areas. -
Object Summary Collections 11/19/2019 Collection·Contains Text·"Manuscripts"·Or Collection·Contains Text·"University"·And Status·Does Not Contain Text·"Deaccessioned"
Object_Summary_Collections 11/19/2019 Collection·Contains text·"Manuscripts"·or Collection·Contains text·"University"·and Status·Does not contain text·"Deaccessioned" Collection University Archives Artifact Collection Image (picture) Object ID 1993-002 Object Name Fan, Hand Description Fan with bamboo frame with paper fan picture of flowers and butterflies. With Chinese writing, bamboo stand is black with two legs. Collection University Archives Artifact Collection Image (picture) Object ID 1993-109.001 Object Name Plaque Description Metal plaque screwed on to wood. Plaque with screws in corner and engraved lettering. Inscription: Dr. F. K. Ramsey, Favorite professor, V. M. Class of 1952. Collection University Archives Artifact Collection Image (picture) Object ID 1993-109.002 Object Name Award Description Gold-colored, metal plaque, screwed on "walnut" wood; lettering on brown background. Inscription: Present with Christian love to Frank K. Ramsey in recognition of his leadership in the CUMC/WF resotration fund drive, June 17, 1984. Collection University Archives Artifact Collection Image (picture) Object ID 1993-109.003 Object Name Plaque Description Wood with metal plaque adhered to it; plque is silver and black, scroll with graphic design and lettering. Inscription: To Frank K. Ramsey, D. V. M. in appreciation for unerring dedication to teaching excellence and continuing support of the profession. Class of 1952. Page 1 Collection University Archives Artifact Collection Image (picture) Object ID 1993-109.004 Object Name Award Description Metal plaque screwed into wood; plaque is in scroll shape on top and bottom. Inscription: 1974; Veterinary Service Award, F. K. Ramsey, Iowa Veterinary Medical Association. Collection University Archives Artifact Collection Image (picture) Object ID 1993-109.005 Object Name Award Description Metal plaque screwed onto wood; raised metal spray of leaves on lower corner; black lettering. -
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). -
A Brief History of Computers
History of Computers http://www.cs.uah.edu/~rcoleman/Common/History/History.html A Brief History of Computers Where did these beasties come from? Ancient Times Early Man relied on counting on his fingers and toes (which by the way, is the basis for our base 10 numbering system). He also used sticks and stones as markers. Later notched sticks and knotted cords were used for counting. Finally came symbols written on hides, parchment, and later paper. Man invents the concept of number, then invents devices to help keep up with the numbers of his possessions. Roman Empire The ancient Romans developed an Abacus, the first "machine" for calculating. While it predates the Chinese abacus we do not know if it was the ancestor of that Abacus. Counters in the lower groove are 1 x 10 n, those in the upper groove are 5 x 10 n Industrial Age - 1600 John Napier, a Scottish nobleman and politician devoted much of his leisure time to the study of mathematics. He was especially interested in devising ways to aid computations. His greatest contribution was the invention of logarithms. He inscribed logarithmic measurements on a set of 10 wooden rods and thus was able to do multiplication and division by matching up numbers on the rods. These became known as Napier’s Bones. 1621 - The Sliderule Napier invented logarithms, Edmund Gunter invented the logarithmic scales (lines etched on metal or wood), but it was William Oughtred, in England who invented the sliderule. Using the concept of Napier’s bones, he inscribed logarithms on strips of wood and invented the calculating "machine" which was used up until the mid-1970s when the first hand-held calculators and microcomputers appeared.