A Tiny Guide to Programming in 32-Bit X86 Assembly Language
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Copy on Write Based File Systems Performance Analysis and Implementation
Copy On Write Based File Systems Performance Analysis And Implementation Sakis Kasampalis Kongens Lyngby 2010 IMM-MSC-2010-63 Technical University of Denmark Department Of Informatics Building 321, DK-2800 Kongens Lyngby, Denmark Phone +45 45253351, Fax +45 45882673 [email protected] www.imm.dtu.dk Abstract In this work I am focusing on Copy On Write based file systems. Copy On Write is used on modern file systems for providing (1) metadata and data consistency using transactional semantics, (2) cheap and instant backups using snapshots and clones. This thesis is divided into two main parts. The first part focuses on the design and performance of Copy On Write based file systems. Recent efforts aiming at creating a Copy On Write based file system are ZFS, Btrfs, ext3cow, Hammer, and LLFS. My work focuses only on ZFS and Btrfs, since they support the most advanced features. The main goals of ZFS and Btrfs are to offer a scalable, fault tolerant, and easy to administrate file system. I evaluate the performance and scalability of ZFS and Btrfs. The evaluation includes studying their design and testing their performance and scalability against a set of recommended file system benchmarks. Most computers are already based on multi-core and multiple processor architec- tures. Because of that, the need for using concurrent programming models has increased. Transactions can be very helpful for supporting concurrent program- ming models, which ensure that system updates are consistent. Unfortunately, the majority of operating systems and file systems either do not support trans- actions at all, or they simply do not expose them to the users. -
Pdp11-40.Pdf
processor handbook digital equipment corporation Copyright© 1972, by Digital Equipment Corporation DEC, PDP, UNIBUS are registered trademarks of Digital Equipment Corporation. ii TABLE OF CONTENTS CHAPTER 1 INTRODUCTION 1·1 1.1 GENERAL ............................................. 1·1 1.2 GENERAL CHARACTERISTICS . 1·2 1.2.1 The UNIBUS ..... 1·2 1.2.2 Central Processor 1·3 1.2.3 Memories ........... 1·5 1.2.4 Floating Point ... 1·5 1.2.5 Memory Management .............................. .. 1·5 1.3 PERIPHERALS/OPTIONS ......................................... 1·5 1.3.1 1/0 Devices .......... .................................. 1·6 1.3.2 Storage Devices ...................................... .. 1·6 1.3.3 Bus Options .............................................. 1·6 1.4 SOFTWARE ..... .... ........................................... ............. 1·6 1.4.1 Paper Tape Software .......................................... 1·7 1.4.2 Disk Operating System Software ........................ 1·7 1.4.3 Higher Level Languages ................................... .. 1·7 1.5 NUMBER SYSTEMS ..................................... 1-7 CHAPTER 2 SYSTEM ARCHITECTURE. 2-1 2.1 SYSTEM DEFINITION .............. 2·1 2.2 UNIBUS ......................................... 2-1 2.2.1 Bidirectional Lines ...... 2-1 2.2.2 Master-Slave Relation .. 2-2 2.2.3 Interlocked Communication 2-2 2.3 CENTRAL PROCESSOR .......... 2-2 2.3.1 General Registers ... 2-3 2.3.2 Processor Status Word ....... 2-4 2.3.3 Stack Limit Register 2-5 2.4 EXTENDED INSTRUCTION SET & FLOATING POINT .. 2-5 2.5 CORE MEMORY . .... 2-6 2.6 AUTOMATIC PRIORITY INTERRUPTS .... 2-7 2.6.1 Using the Interrupts . 2-9 2.6.2 Interrupt Procedure 2-9 2.6.3 Interrupt Servicing ............ .. 2-10 2.7 PROCESSOR TRAPS ............ 2-10 2.7.1 Power Failure .............. -
Distributed Cloud-Based Approaches to the Genomic Data Analysis
08 Fall Czech Technical University Faculty of Electrical Engineering Distributed cloud-based approaches to the genomic data analysis (Master’s thesis) Bc. Filip Mihalovič Supervisor: doc. Ing. Jiří Kléma, PhD. Study programme: Open Informatics Specialization: Software Engineering May 2016 ii Acknowledgements I wish to express my sincere thanks to my supervisor doc. Ing. Jiří Kléma, PhD. for sharing his expertise and for his continuous guidance. I am grateful to my family and friends for their encouragement and support during my studies. Access to computing and storage facilities owned by parties and projects contributing to the National Grid Infrastructure MetaCentrum, provided under the programme "Projects of Large Research, Development, and Innovations Infrastructures" (CESNET LM2015042), is greatly appreciated. iii iv vi Declaration I declare that I worked out the presented thesis independently and I quoted all used sources of information in accord with Methodical instructions about ethical principles for writing academic thesis. In Prague on 24th May 2016 …………………………………….. Author vii Abstract The advance of genome analysis bound to next-generation sequencing has allowed scientists to conduct research to deeper understand the biological structure of organisms. A problem of computationally demanding genome assembly based on a high volume of sequence reads is introduced. Several sequential solutions for de novo genome assembly are reviewed. Two fundamental types of genome assembly approaches exist, the sequence reconstruction via de Bruijn graph and the overlap graph method. We focus on parallelization of the genome assembly task using the overlap graph approach and the utilization of Apache Spark big data engine. We demonstrate that subtasks of genome assembly can be parallelized and computed in a distributed manner. -
The Linux Kernel Module Programming Guide
The Linux Kernel Module Programming Guide Peter Jay Salzman Michael Burian Ori Pomerantz Copyright © 2001 Peter Jay Salzman 2007−05−18 ver 2.6.4 The Linux Kernel Module Programming Guide is a free book; you may reproduce and/or modify it under the terms of the Open Software License, version 1.1. You can obtain a copy of this license at http://opensource.org/licenses/osl.php. This book is distributed in the hope it will be useful, but without any warranty, without even the implied warranty of merchantability or fitness for a particular purpose. The author encourages wide distribution of this book for personal or commercial use, provided the above copyright notice remains intact and the method adheres to the provisions of the Open Software License. In summary, you may copy and distribute this book free of charge or for a profit. No explicit permission is required from the author for reproduction of this book in any medium, physical or electronic. Derivative works and translations of this document must be placed under the Open Software License, and the original copyright notice must remain intact. If you have contributed new material to this book, you must make the material and source code available for your revisions. Please make revisions and updates available directly to the document maintainer, Peter Jay Salzman <[email protected]>. This will allow for the merging of updates and provide consistent revisions to the Linux community. If you publish or distribute this book commercially, donations, royalties, and/or printed copies are greatly appreciated by the author and the Linux Documentation Project (LDP). -
Also Includes Slides and Contents From
The Compilation Toolchain Cross-Compilation for Embedded Systems Prof. Andrea Marongiu ([email protected]) Toolchain The toolchain is a set of development tools used in association with source code or binaries generated from the source code • Enables development in a programming language (e.g., C/C++) • It is used for a lot of operations such as a) Compilation b) Preparing Libraries Most common toolchain is the c) Reading a binary file (or part of it) GNU toolchain which is part of d) Debugging the GNU project • Normally it contains a) Compiler : Generate object files from source code files b) Linker: Link object files together to build a binary file c) Library Archiver: To group a set of object files into a library file d) Debugger: To debug the binary file while running e) And other tools The GNU Toolchain GNU (GNU’s Not Unix) The GNU toolchain has played a vital role in the development of the Linux kernel, BSD, and software for embedded systems. The GNU project produced a set of programming tools. Parts of the toolchain we will use are: -gcc: (GNU Compiler Collection): suite of compilers for many programming languages -binutils: Suite of tools including linker (ld), assembler (gas) -gdb: Code debugging tool -libc: Subset of standard C library (assuming a C compiler). -bash: free Unix shell (Bourne-again shell). Default shell on GNU/Linux systems and Mac OSX. Also ported to Microsoft Windows. -make: automation tool for compilation and build Program development tools The process of converting source code to an executable binary image requires several steps, each with its own tool. -
Download and Unpack It: Tar -Zxvf Leptospirashermanidata.Tar.Gz
Hsieh et al. BMC Bioinformatics (2020) 21:528 https://doi.org/10.1186/s12859‑020‑03788‑9 SOFTWARE Open Access Clover: a clustering‑oriented de novo assembler for Illumina sequences Ming‑Feng Hsieh1, Chin Lung Lu1 and Chuan Yi Tang1,2* *Correspondence: [email protected] Abstract 1 Department of Computer Background: Next‑generation sequencing technologies revolutionized genomics Science, National Tsing Hua University, Hsinchu 30013, by producing high‑throughput reads at low cost, and this progress has prompted the Taiwan recent development of de novo assemblers. Multiple assembly methods based on de Full list of author information Bruijn graph have been shown to be efcient for Illumina reads. However, the sequenc‑ is available at the end of the article ing errors generated by the sequencer complicate analysis of de novo assembly and infuence the quality of downstream genomic researches. Results: In this paper, we develop a de Bruijn assembler, called Clover (clustering‑ oriented de novo assembler), that utilizes a novel k‑mer clustering approach from the overlap‑layout‑consensus concept to deal with the sequencing errors generated by the Illumina platform. We further evaluate Clover’s performance against several de Bruijn graph assemblers (ABySS, SOAPdenovo, SPAdes and Velvet), overlap‑layout‑con‑ sensus assemblers (Bambus2, CABOG and MSR‑CA) and string graph assembler (SGA) on three datasets (Staphylococcus aureus, Rhodobacter sphaeroides and human chromo‑ some 14). The results show that Clover achieves a superior assembly quality in terms of corrected N50 and E‑size while remaining a signifcantly competitive in run time except SOAPdenovo. In addition, Clover was involved in the sequencing projects of bacterial genomes Acinetobacter baumannii TYTH‑1 and Morganella morganii KT. -
Lecture Notes in Assembly Language
Lecture Notes in Assembly Language Short introduction to low-level programming Piotr Fulmański Łódź, 12 czerwca 2015 Spis treści Spis treści iii 1 Before we begin1 1.1 Simple assembler.................................... 1 1.1.1 Excercise 1 ................................... 2 1.1.2 Excercise 2 ................................... 3 1.1.3 Excercise 3 ................................... 3 1.1.4 Excercise 4 ................................... 5 1.1.5 Excercise 5 ................................... 6 1.2 Improvements, part I: addressing........................... 8 1.2.1 Excercise 6 ................................... 11 1.3 Improvements, part II: indirect addressing...................... 11 1.4 Improvements, part III: labels............................. 18 1.4.1 Excercise 7: find substring in a string .................... 19 1.4.2 Excercise 8: improved polynomial....................... 21 1.5 Improvements, part IV: flag register ......................... 23 1.6 Improvements, part V: the stack ........................... 24 1.6.1 Excercise 12................................... 26 1.7 Improvements, part VI – function stack frame.................... 29 1.8 Finall excercises..................................... 34 1.8.1 Excercise 13................................... 34 1.8.2 Excercise 14................................... 34 1.8.3 Excercise 15................................... 34 1.8.4 Excercise 16................................... 34 iii iv SPIS TREŚCI 1.8.5 Excercise 17................................... 34 2 First program 37 2.1 Compiling, -
Computer Architecture and Assembly Language
Computer Architecture and Assembly Language Gabriel Laskar EPITA 2015 License I Copyright c 2004-2005, ACU, Benoit Perrot I Copyright c 2004-2008, Alexandre Becoulet I Copyright c 2009-2013, Nicolas Pouillon I Copyright c 2014, Joël Porquet I Copyright c 2015, Gabriel Laskar Permission is granted to copy, distribute and/or modify this document under the terms of the GNU Free Documentation License, Version 1.2 or any later version published by the Free Software Foundation; with the Invariant Sections being just ‘‘Copying this document’’, no Front-Cover Texts, and no Back-Cover Texts. Introduction Part I Introduction Gabriel Laskar (EPITA) CAAL 2015 3 / 378 Introduction Problem definition 1: Introduction Problem definition Outline Gabriel Laskar (EPITA) CAAL 2015 4 / 378 Introduction Problem definition What are we trying to learn? Computer Architecture What is in the hardware? I A bit of history of computers, current machines I Concepts and conventions: processing, memory, communication, optimization How does a machine run code? I Program execution model I Memory mapping, OS support Gabriel Laskar (EPITA) CAAL 2015 5 / 378 Introduction Problem definition What are we trying to learn? Assembly Language How to “talk” with the machine directly? I Mechanisms involved I Assembly language structure and usage I Low-level assembly language features I C inline assembly Gabriel Laskar (EPITA) CAAL 2015 6 / 378 I Programmers I Wise managers Introduction Problem definition Who do I talk to? I System gurus I Low-level enthusiasts Gabriel Laskar (EPITA) CAAL -
Appendix D an Alternative to RISC: the Intel 80X86
D.1 Introduction D-2 D.2 80x86 Registers and Data Addressing Modes D-3 D.3 80x86 Integer Operations D-6 D.4 80x86 Floating-Point Operations D-10 D.5 80x86 Instruction Encoding D-12 D.6 Putting It All Together: Measurements of Instruction Set Usage D-14 D.7 Concluding Remarks D-20 D.8 Historical Perspective and References D-21 D An Alternative to RISC: The Intel 80x86 The x86 isn’t all that complex—it just doesn’t make a lot of sense. Mike Johnson Leader of 80x86 Design at AMD, Microprocessor Report (1994) © 2003 Elsevier Science (USA). All rights reserved. D-2 I Appendix D An Alternative to RISC: The Intel 80x86 D.1 Introduction MIPS was the vision of a single architect. The pieces of this architecture fit nicely together and the whole architecture can be described succinctly. Such is not the case of the 80x86: It is the product of several independent groups who evolved the architecture over 20 years, adding new features to the original instruction set as you might add clothing to a packed bag. Here are important 80x86 milestones: I 1978—The Intel 8086 architecture was announced as an assembly language– compatible extension of the then-successful Intel 8080, an 8-bit microproces- sor. The 8086 is a 16-bit architecture, with all internal registers 16 bits wide. Whereas the 8080 was a straightforward accumulator machine, the 8086 extended the architecture with additional registers. Because nearly every reg- ister has a dedicated use, the 8086 falls somewhere between an accumulator machine and a general-purpose register machine, and can fairly be called an extended accumulator machine. -
The Von Neumann Computer Model 5/30/17, 10:03 PM
The von Neumann Computer Model 5/30/17, 10:03 PM CIS-77 Home http://www.c-jump.com/CIS77/CIS77syllabus.htm The von Neumann Computer Model 1. The von Neumann Computer Model 2. Components of the Von Neumann Model 3. Communication Between Memory and Processing Unit 4. CPU data-path 5. Memory Operations 6. Understanding the MAR and the MDR 7. Understanding the MAR and the MDR, Cont. 8. ALU, the Processing Unit 9. ALU and the Word Length 10. Control Unit 11. Control Unit, Cont. 12. Input/Output 13. Input/Output Ports 14. Input/Output Address Space 15. Console Input/Output in Protected Memory Mode 16. Instruction Processing 17. Instruction Components 18. Why Learn Intel x86 ISA ? 19. Design of the x86 CPU Instruction Set 20. CPU Instruction Set 21. History of IBM PC 22. Early x86 Processor Family 23. 8086 and 8088 CPU 24. 80186 CPU 25. 80286 CPU 26. 80386 CPU 27. 80386 CPU, Cont. 28. 80486 CPU 29. Pentium (Intel 80586) 30. Pentium Pro 31. Pentium II 32. Itanium processor 1. The von Neumann Computer Model Von Neumann computer systems contain three main building blocks: The following block diagram shows major relationship between CPU components: the central processing unit (CPU), memory, and input/output devices (I/O). These three components are connected together using the system bus. The most prominent items within the CPU are the registers: they can be manipulated directly by a computer program. http://www.c-jump.com/CIS77/CPU/VonNeumann/lecture.html Page 1 of 15 IPR2017-01532 FanDuel, et al. -
Computer Organization & Architecture Eie
COMPUTER ORGANIZATION & ARCHITECTURE EIE 411 Course Lecturer: Engr Banji Adedayo. Reg COREN. The characteristics of different computers vary considerably from category to category. Computers for data processing activities have different features than those with scientific features. Even computers configured within the same application area have variations in design. Computer architecture is the science of integrating those components to achieve a level of functionality and performance. It is logical organization or designs of the hardware that make up the computer system. The internal organization of a digital system is defined by the sequence of micro operations it performs on the data stored in its registers. The internal structure of a MICRO-PROCESSOR is called its architecture and includes the number lay out and functionality of registers, memory cell, decoders, controllers and clocks. HISTORY OF COMPUTER HARDWARE The first use of the word ‘Computer’ was recorded in 1613, referring to a person who carried out calculation or computation. A brief History: Computer as we all know 2day had its beginning with 19th century English Mathematics Professor named Chales Babage. He designed the analytical engine and it was this design that the basic frame work of the computer of today are based on. 1st Generation 1937-1946 The first electronic digital computer was built by Dr John V. Atanasoff & Berry Cliford (ABC). In 1943 an electronic computer named colossus was built for military. 1946 – The first general purpose digital computer- the Electronic Numerical Integrator and computer (ENIAC) was built. This computer weighed 30 tons and had 18,000 vacuum tubes which were used for processing. -
Compiler Construction
Compiler Construction Chapter 11 Compiler Construction Compiler Construction 1 A New Compiler • Perhaps a new source language • Perhaps a new target for an existing compiler • Perhaps both Compiler Construction Compiler Construction 2 Source Language • Larger, more complex languages generally require larger, more complex compilers • Is the source language expected to evolve? – E.g., Java 1.0 ! Java 1.1 ! . – A brand new language may undergo considerable change early on – A small working prototype may be in order – Compiler writers must anticipate some amount of change and their design must therefore be flexible – Lexer and parser generators (like Lex and Yacc) are therefore better than hand- coding the lexer and parser when change is inevitable Compiler Construction Compiler Construction 3 Target Language • The nature of the target language and run-time environment influence compiler construction considerably • A new processor and/or its assembler may be buggy Buggy targets make it difficult to debug compilers for that target! • A successful source language will persist over several target generations – E.g., 386 ! 486 ! Pentium ! . – Thus the design of the IR is important – Modularization of machine-specific details is also important Compiler Construction Compiler Construction 4 Compiler Performance Issues • Compiler speed • Generated code quality • Error diagnostics • Portability • Maintainability Compiler Construction Compiler Construction 5 Compiler Speed • Reduce the number of modules • Reduce the number of passes Perhaps generate machine