Special Issue on Charles Hamblin
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Supplementary Material HR19008 AC
Historical Records of Australian Science © Australian Academy of Science 2020 https://doi.org/10.1071/HR19008_AC Supplementary Material: Historical Records of Australian Science, 2020, 31(1), 17–25 Supplementary material. A bibliography of Australian mathematics to 1960 with observations relating to the history of Australian mathematics Graeme L. Cohen Formerly, School of Mathematical Sciences, University of Technology Sydney, NSW 2007, Australia. Email: [email protected] File S1. Lists List 1—Chronological List of Publications to 1900 2 List 2—Alphabetical by Author List of Publications from 1901 16 to 1960 (Excluding Theses and Most School Books) List 3—Alphabetical by Author List of Theses Leading to the 37 Award of a Higher Degree, to 1960 Index 45 References (further to those in the main text) 56 1 Historical Records of Australian Science © Australian Academy of Science 2020 https://doi.org/10.1071/HR19008_AC Supplementary Material: Historical Records of Australian Science, 2020, 31(1), 17–25 LISTS The main item, article HR19008, should be read first for a full understanding of what is included here. The superscript CAI before an author’s name indicates that biographical information on that author is to be found in Counting Australia In.1 List 1— Chronological List of Publications to 1900 1. RUSSELL, JOHN WM. (18-?) Exercises and examples in expert arithmetic, Kealy & Philip, Sydney. 2. BOWDEN, THOMAS (1812) Bowden’s tables, Ferguson I, 532. [‘Their object is to ascertain at a momentary glance, the difference between sterling and currency … They are calculated with a degree of precision that must have occupied considerable time and attention …’, according to Ferguson. -
Second-Generation Stack Computer Architecture
Second-Generation Stack Computer Architecture Charles Eric LaForest A thesis presented to the Independent Studies Program of the University of Waterloo in fulfilment of the thesis requirements for the degree Bachelor of Independent Studies (BIS) Independent Studies University of Waterloo Canada April 2007 ii Declaration I hereby declare that I am the sole author of this research paper. I authorize the University of Waterloo to lend this thesis to other institutions or individuals for the purpose of scholarly research. Signature: I further authorize the University of Waterloo to reproduce this research paper by photocopy- ing or other means, in total or in part, at the request of other institutions or individuals for the purpose of scholarly research. Signature: The work in this research paper is based on research carried out in the Independent Studies Program at the University of Waterloo, Canada. No part of this thesis has been submitted else- where for any other degree or qualification and is all my own work unless referenced to the contrary in the text. Copyright c 2007 by Charles Eric LaForest. The copyright of this thesis rests with the author. Quotations and information derived from it must be acknowledged. iii Second-Generation Stack Computer Architecture Charles Eric LaForest Submitted for the degree of Bachelor of Independent Studies April 2007 Abstract It is commonly held in current computer architecture literature that stack-based computers were entirely superseded by the combination of pipelined, integrated microprocessors and improved compilers. While correct, the literature omits a second, new generation of stack computers that emerged at the same time. -
Second-Generation Stack Computer Architecture
Second-Generation Stack Computer Architecture Charles Eric LaForest A thesis presented to the Independent Studies Program of the University of Waterloo in fulfilment of the thesis requirements for the degree Bachelor of Independent Studies (BIS) Independent Studies University of Waterloo Canada April 2007 ii Declaration I hereby declare that I am the sole author of this research paper. I authorize the University of Waterloo to lend this thesis to other institutions or individuals for the purpose of scholarly research. Signature: [:.,,,u..c ;(~ I further authorize the University of Waterloo to reproduce this research paper by photocopy ing or other means, in total or in part, at the request of other institutions or individuals for the pUipose of scholarly research. SignatUI·e: 6 ~ >{!. The work in this research paper is based on research carried out in the Independent Studies Program at the University of Waterloo, Canada. No part of this thesis has been submitted else where for any other degree or qualification and is all my own work unless referenced to the contrary in the text. Copyright© 2007 by Charles Eric La Forest. The copyright of this thesis rests with the author. Quotations and infonnation derived from it must be acknowledged. Ill Second-Generation Stack Computer Architecture Charles Eric LaForest Submitted for the degree of Bachelor of Independent Studies April 2007 Abstract It is commonly held in current computer architecture literature that stack-based computers were entirely superseded by the combination of pipelined, integrated microprocessors and improved compilers. While correct, the literature omits a second, new generation of stack computers that emerged at the same time. -
2.1 Accelerators to Reduce Power Consumption
Feasibility of Accelerator Generation to Alleviate Dark Silicon in a Novel Architecture Antonio ARNONE PhD UNIVERSITY OF YORK Computer Science June 2017 iii Abstract This thesis presents a novel approach to alleviating Dark Silicon problem by reduc- ing power density. Decreasing the size of transistor has generated an increasing on power consump- tion. To attempt to manage the power issue, processor design has shifted from one single core to many cores. Switching on fewer cores while the others are off helps the chip to cool down and spread power more evenly over the chip. This means that some transistors are always idle while others are working. Therefore, scaling down the size of the chip, and increasing the amount of power to be dissipated, increases the number of inactive transistors. As a result it generates Dark Silicon, which dou- bles every chip generation [63] One of the most effective techniques to deal with Dark Silicon is to implement accelerators that execute the most energy consumer software functions. In this way the CPU is able to dissipate more energy and reduce the dark silicon issue. This work explores a novel accelerator design model which could be interfaced to a Stack CPU and so could optimise the transistor logic area and improve energy effi- ciency to tackle the dark silicon problem based on heterogeneous multi-accelerators (co-processor) in stack structure. The contribution of this thesis is to develop a tool to generate coprocessors from software stack machine code. But it also employs up-to-date code optimisation strategies to enhance the code at the input stage. -
Data Structures
Data structures PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Thu, 17 Nov 2011 20:55:22 UTC Contents Articles Introduction 1 Data structure 1 Linked data structure 3 Succinct data structure 5 Implicit data structure 7 Compressed data structure 8 Search data structure 9 Persistent data structure 11 Concurrent data structure 15 Abstract data types 18 Abstract data type 18 List 26 Stack 29 Queue 57 Deque 60 Priority queue 63 Map 67 Bidirectional map 70 Multimap 71 Set 72 Tree 76 Arrays 79 Array data structure 79 Row-major order 84 Dope vector 86 Iliffe vector 87 Dynamic array 88 Hashed array tree 91 Gap buffer 92 Circular buffer 94 Sparse array 109 Bit array 110 Bitboard 115 Parallel array 119 Lookup table 121 Lists 127 Linked list 127 XOR linked list 143 Unrolled linked list 145 VList 147 Skip list 149 Self-organizing list 154 Binary trees 158 Binary tree 158 Binary search tree 166 Self-balancing binary search tree 176 Tree rotation 178 Weight-balanced tree 181 Threaded binary tree 182 AVL tree 188 Red-black tree 192 AA tree 207 Scapegoat tree 212 Splay tree 216 T-tree 230 Rope 233 Top Trees 238 Tango Trees 242 van Emde Boas tree 264 Cartesian tree 268 Treap 273 B-trees 276 B-tree 276 B+ tree 287 Dancing tree 291 2-3 tree 292 2-3-4 tree 293 Queaps 295 Fusion tree 299 Bx-tree 299 Heaps 303 Heap 303 Binary heap 305 Binomial heap 311 Fibonacci heap 316 2-3 heap 321 Pairing heap 321 Beap 324 Leftist tree 325 Skew heap 328 Soft heap 331 d-ary heap 333 Tries 335 Trie -
Fundamental Data Structures
Fundamental Data Structures PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Thu, 17 Nov 2011 21:36:24 UTC Contents Articles Introduction 1 Abstract data type 1 Data structure 9 Analysis of algorithms 11 Amortized analysis 16 Accounting method 18 Potential method 20 Sequences 22 Array data type 22 Array data structure 26 Dynamic array 31 Linked list 34 Doubly linked list 50 Stack (abstract data type) 54 Queue (abstract data type) 82 Double-ended queue 85 Circular buffer 88 Dictionaries 103 Associative array 103 Association list 106 Hash table 107 Linear probing 120 Quadratic probing 121 Double hashing 125 Cuckoo hashing 126 Hopscotch hashing 130 Hash function 131 Perfect hash function 140 Universal hashing 141 K-independent hashing 146 Tabulation hashing 147 Cryptographic hash function 150 Sets 157 Set (abstract data type) 157 Bit array 161 Bloom filter 166 MinHash 176 Disjoint-set data structure 179 Partition refinement 183 Priority queues 185 Priority queue 185 Heap (data structure) 190 Binary heap 192 d-ary heap 198 Binomial heap 200 Fibonacci heap 205 Pairing heap 210 Double-ended priority queue 213 Soft heap 218 Successors and neighbors 221 Binary search algorithm 221 Binary search tree 228 Random binary tree 238 Tree rotation 241 Self-balancing binary search tree 244 Treap 246 AVL tree 249 Red–black tree 253 Scapegoat tree 268 Splay tree 272 Tango tree 286 Skip list 308 B-tree 314 B+ tree 325 Integer and string searching 330 Trie 330 Radix tree 337 Directed acyclic word graph 339 Suffix tree 341 Suffix array 346 van Emde Boas tree 349 Fusion tree 353 References Article Sources and Contributors 354 Image Sources, Licenses and Contributors 359 Article Licenses License 362 1 Introduction Abstract data type In computing, an abstract data type (ADT) is a mathematical model for a certain class of data structures that have similar behavior; or for certain data types of one or more programming languages that have similar semantics. -
Logic A-Z from Wikipedia, the Free Encyclopedia Chapter 1
Logic A-Z From Wikipedia, the free encyclopedia Chapter 1 Antepredicament Antepredicaments, in logic, are certain previous matters requisite to a more easy and clear apprehension of the doctrine of predicaments or categories. Such are definitions of common terms, as equivocals, univocals, etc., with divisions of things, their differences, etc. They are thus called because Aristotle treated them before the predicaments, hoping that the thread of discourse might not afterwards be interrupted. 1.1 References • This article incorporates text from a publication now in the public domain: Chambers, Ephraim, ed. (1728). "*article name needed". Cyclopædia, or an Universal Dictionary of Arts and Sciences (first ed.). James and John Knapton, et al. 2 Chapter 2 Apophasis Not to be confused with Apophysis (disambiguation), Apoptosis, or Apophis (disambiguation). Apophasis is a rhetorical device wherein the speaker or writer brings up a subject by either denying it, or denying that it should be brought up.*[1] Accordingly, it can be seen as a rhetorical relative of irony. Also called paralipsis (παράλειψις) – also spelled paraleipsis or paralepsis –, or occupatio,*[2]*[3]*[4]*[5] and known also as prae- teritio, preterition, antiphrasis (ἀντίφρασις), or parasiopesis (παρασιώπησις), apophasis is usually employed to make a subversive ad hominem attack, which makes it a frequently used tactic in political speeches to make an attack on one's opponent. Using apophasis in this way is often considered to be bad form. The device is typically used to distance -
Mathemathics V.2.Indd
Chapter 5 Australia’s Mathematicians in World War 2 any Australian mathematicians served their country through world wars and other wars, whether in military service or in a civilian capacity, in some cases interrupting Muniversity studies to do so. There are many records of service ably performed and there are accounts, too, of derring-do, some wise, some not so wise. More importantly for the annals of mathe matics, there are instances of Australian mathematicians’ development of areas of appli cation of mathemat ics whose very existence is a result of the needs of war or which received great impetus at times of war. Three such areas are sketched below, along with some Australian mathematicians’ contri- butions. The fi rst is cryptography, or the mak ing and breaking of codes, a study that can be traced back at least to the days of Julius Caesar. It is fundamental to the secure trans mission of data, which is now an economic necessity as much as a military one, and mathe matical research in the area con tinues at a great pace. The second is opera tional research, now known outside England as opera tions research or man agement sci ence. The name in the fi rst instance referred specifi cally to the research of wartime opera tions, but it now refers to an area of study in its own right deal ing with all manner of problems concerned with optimi sation, for example the minimisation of cost or of time or the maximisa tion of personnel resources. The third area concerns public health: such fi elds as demography and epide mio logy.