International Journal of Soft Computing and Engineering
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Defense Industry Restructuring in Russia
S t a n f o r d U n i v e r s i t y C I S A C Center for International Security and Arms Control The Center for International Security and Arms Control, part of Stanford University’s Institute for International Studies, is a multidisciplinary community dedicated to research and train- ing in the field of international security. The Center brings together scholars, policymakers, scientists, area specialists, members of the business community, and other experts to examine a wide range of international security issues. CISAC publishes its own series of working papers and reports on its work and also sponsors a series, Studies in International Se- curity and Arms Control, through Stanford University Press. Center for International Security and Arms Control Stanford University 320 Galvez Street Stanford, California 94305-6165 (415) 723-9625 http://www-leland.stanford.edu/group/CISAC/ Contents Acknowledgments iv Executive Summary v I Introduction 1 Section One: Case Studies II The Central Aerohydrodynamic Research Institute (TsAGI) 9 III ELVIS+ and The Moscow Center for SPARC Technology (MCST) 28 IV Impuls 45 V The Mashinostroenie Enterprise 59 VI The Saratov Aviation Plant 79 Section Two: Analysis VII Privatization at Four Enterprises 111 VIII Organizational Restructuring 137 IX Principal Differences in Accounting Systems in Russia 163 and the United States X Reallocation of the Social Services 183 XI Conclusion 207 Glossary 216 1 Acknowledgments Many people have contributed to this report, and still more have contributed to the research leading up to it. In writing this report, we have not attempted to reach consensus among the authors on the interpretations to be drawn from the data. -
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. -
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. -
10. Assembly Language, Models of Computation
10. Assembly Language, Models of Computation 6.004x Computation Structures Part 2 – Computer Architecture Copyright © 2015 MIT EECS 6.004 Computation Structures L10: Assembly Language, Models of Computation, Slide #1 Beta ISA Summary • Storage: – Processor: 32 registers (r31 hardwired to 0) and PC – Main memory: Up to 4 GB, 32-bit words, 32-bit byte addresses, 4-byte-aligned accesses OPCODE rc ra rb unused • Instruction formats: OPCODE rc ra 16-bit signed constant 32 bits • Instruction classes: – ALU: Two input registers, or register and constant – Loads and stores: access memory – Branches, Jumps: change program counter 6.004 Computation Structures L10: Assembly Language, Models of Computation, Slide #2 Programming Languages 32-bit (4-byte) ADD instruction: 1 0 0 0 0 0 0 0 1 0 0 0 0 0 1 0 0 0 0 1 1 0 0 0 0 0 0 0 0 0 0 0 opcode rc ra rb (unused) Means, to the BETA, Reg[4] ß Reg[2] + Reg[3] We’d rather write in assembly language: Today ADD(R2, R3, R4) or better yet a high-level language: Coming up a = b + c; 6.004 Computation Structures L10: Assembly Language, Models of Computation, Slide #3 Assembly Language Symbolic 01101101 11000110 Array of bytes representation Assembler 00101111 to be loaded of stream of bytes 10110001 into memory ..... Source Binary text file machine language • Abstracts bit-level representation of instructions and addresses • We’ll learn UASM (“microassembler”), built into BSim • Main elements: – Values – Symbols – Labels (symbols for addresses) – Macros 6.004 Computation Structures L10: Assembly Language, Models -
Winter 2017/18
Newsletter - Calibrated for Creative Communications Vol. 15, no. 4, Winter 2017/18 Schneeberg seen from the Wienerwald, Nov. 2017 Vantage Point IT STAR representatives nd-of-year provides an excellent vantage point to assess Eachievements and shortcomings during the exiting year and Austria/OCG-R. Bieber, Bulgaria/BAS- I. Dimov, to look forward into the future. Croatia/CITA-M. Frkovic, Cyprus/CCS-P. Masouras, Czech Rep./CSKI-J. Stuller, Greece/GCS-S. Katsikas, Based on feedback from our readers, we can tick the 2017 per- Hungary/NJSZT-B. Domolki, Italy/AICA-G. Occhini, formance of the Newsletter as successful. Our Honorary Advi- Lithuania/LIKS-E. Telešius, Macedonia/MASIT- sory Board is growing and we are happy to have a stronger fe- P. Indovski, Poland/PIPS-M. Holynski, Romania/ male representation of the informatics profession. ATIC-V. Baltac, Serbia/JISA-D. Dukic, Slovakia/SSCS- I. Privara, Slovenia/SSI-N. Schlamberger In this last 2017 Issue we are pleased to introduce our new mem- bers of the NL Advisory Board, to brief you on the Russian Vir- Contents tual Computer Museum and to provide an update on develop- New members of the Advisory Board ........................... 2 ments related to Big Data and Competences. IT STAR WS and BM in Sofia ...................................... 3 Big Data: The Data Scientist ........................................ 6 Regarding IT STAR, 2017 was rather challenging and efforts were made to build upon successful activities so as to recalibrate Russian Virtual Computer Museum ............................. 9 the Association to the benefit of its members and the larger ICT ITU Information Society Report 2017 ......................... 13 community. MS News ................................................................... -
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 ............................................ -
Computer Architectures an Overview
Computer Architectures An Overview PDF generated using the open source mwlib toolkit. See http://code.pediapress.com/ for more information. PDF generated at: Sat, 25 Feb 2012 22:35:32 UTC Contents Articles Microarchitecture 1 x86 7 PowerPC 23 IBM POWER 33 MIPS architecture 39 SPARC 57 ARM architecture 65 DEC Alpha 80 AlphaStation 92 AlphaServer 95 Very long instruction word 103 Instruction-level parallelism 107 Explicitly parallel instruction computing 108 References Article Sources and Contributors 111 Image Sources, Licenses and Contributors 113 Article Licenses License 114 Microarchitecture 1 Microarchitecture In computer engineering, microarchitecture (sometimes abbreviated to µarch or uarch), also called computer organization, is the way a given instruction set architecture (ISA) is implemented on a processor. A given ISA may be implemented with different microarchitectures.[1] Implementations might vary due to different goals of a given design or due to shifts in technology.[2] Computer architecture is the combination of microarchitecture and instruction set design. Relation to instruction set architecture The ISA is roughly the same as the programming model of a processor as seen by an assembly language programmer or compiler writer. The ISA includes the execution model, processor registers, address and data formats among other things. The Intel Core microarchitecture microarchitecture includes the constituent parts of the processor and how these interconnect and interoperate to implement the ISA. The microarchitecture of a machine is usually represented as (more or less detailed) diagrams that describe the interconnections of the various microarchitectural elements of the machine, which may be everything from single gates and registers, to complete arithmetic logic units (ALU)s and even larger elements. -
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. -
Open Access Proceedings Journal of Physics: Conference Series
IOP Conference Series: Earth and Environmental Science PAPER • OPEN ACCESS Issues of compatibility of processor command architectures To cite this article: T R Zmyzgova et al 2020 IOP Conf. Ser.: Earth Environ. Sci. 421 042006 View the article online for updates and enhancements. This content was downloaded from IP address 85.143.35.46 on 13/02/2020 at 06:53 AGRITECH-II-2019 IOP Publishing IOP Conf. Series: Earth and Environmental Science 421 (2020) 042006 doi:10.1088/1755-1315/421/4/042006 Issues of compatibility of processor command architectures T R Zmyzgova, A V Solovyev, A G Rabushko, A A Medvedev and Yu V Adamenko Kurgan State University, 62 Proletarskaya street, Kurgan, 640002, Russia E-mail: [email protected] Abstract. Modern computers and computing devices are based on the principle of open architecture, according to which the computer consists of several sufficiently independent devices that perform a certain function. These devices must meet certain standards of interaction with each other. Existing standards relate to both the technical characteristics of the devices and the content of the signals exchanged between them. The article considers the issue of creating a universal architecture of processor commands. The brief analysis of the components of devices and interrelations between them (different hardware features of processors, architecture of memory models and registers of peripheral devices, mechanisms of operand processing, the number of registers and processed data types, interruptions, exceptions, etc.) is carried out. The problem of architecture standardization, which generalizes the capabilities of the most common architectures and is suitable for high-performance emulation on most computer architectures, is put. -
Background Optimization in Full System Binary Translation
Background Optimization in Full System Binary Translation Roman A. Sokolov Alexander V. Ermolovich MCST CJSC Intel CJSC Moscow, Russia Moscow, Russia Email: [email protected] Email: [email protected] Abstract—Binary translation and dynamic optimization are architecture codes fully utilizing all architectural features widely used to provide compatibility between legacy and promis- introduced to support binary translation. Besides, dynamic ing upcoming architectures on the level of executable binary optimization can benefit from utilization of actual information codes. Dynamic optimization is one of the key contributors to dynamic binary translation system performance. At the same about executables behavior which static compilers usually time it can be a major source of overhead, both in terms of don’t possess. CPU cycles and whole system latency, as long as optimization At the same time dynamic optimization can imply sig- time is included in the execution time of the application under nificant overhead as long as optimization time is included translation. One of the solutions that allow to eliminate dynamic in the execution time of application under translation. Total optimization overhead is to perform optimization simultaneously with the execution, in a separate thread. In the paper we present optimization time can be significant but will not necessarily implementation of this technique in full system dynamic binary be compensated by the translated codes speed-up if application translator. For this purpose, an infrastructure for multithreaded run time is too short. execution was implemented in binary translation system. This Also, the operation of optimizing translator can worsen the allowed running dynamic optimization in a separate thread latency (i.e., increase pause time) of interactive application or independently of and concurrently with the main thread of execution of binary codes under translation.