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Computer Architectures
Computer Architectures Central Processing Unit (CPU) Pavel Píša, Michal Štepanovský, Miroslav Šnorek The lecture is based on A0B36APO lecture. Some parts are inspired by the book Paterson, D., Henessy, V.: Computer Organization and Design, The HW/SW Interface. Elsevier, ISBN: 978-0-12-370606-5 and it is used with authors' permission. Czech Technical University in Prague, Faculty of Electrical Engineering English version partially supported by: European Social Fund Prague & EU: We invests in your future. AE0B36APO Computer Architectures Ver.1.10 1 Computer based on von Neumann's concept ● Control unit Processor/microprocessor ● ALU von Neumann architecture uses common ● Memory memory, whereas Harvard architecture uses separate program and data memories ● Input ● Output Input/output subsystem The control unit is responsible for control of the operation processing and sequencing. It consists of: ● registers – they hold intermediate and programmer visible state ● control logic circuits which represents core of the control unit (CU) AE0B36APO Computer Architectures 2 The most important registers of the control unit ● PC (Program Counter) holds address of a recent or next instruction to be processed ● IR (Instruction Register) holds the machine instruction read from memory ● Another usually present registers ● General purpose registers (GPRs) may be divided to address and data or (partially) specialized registers ● SP (Stack Pointer) – points to the top of the stack; (The stack is usually used to store local variables and subroutine return addresses) ● PSW (Program Status Word) ● IM (Interrupt Mask) ● Optional Floating point (FPRs) and vector/multimedia regs. AE0B36APO Computer Architectures 3 The main instruction cycle of the CPU 1. Initial setup/reset – set initial PC value, PSW, etc. -
Microprocessor Architecture
EECE416 Microcomputer Fundamentals Microprocessor Architecture Dr. Charles Kim Howard University 1 Computer Architecture Computer System CPU (with PC, Register, SR) + Memory 2 Computer Architecture •ALU (Arithmetic Logic Unit) •Binary Full Adder 3 Microprocessor Bus 4 Architecture by CPU+MEM organization Princeton (or von Neumann) Architecture MEM contains both Instruction and Data Harvard Architecture Data MEM and Instruction MEM Higher Performance Better for DSP Higher MEM Bandwidth 5 Princeton Architecture 1.Step (A): The address for the instruction to be next executed is applied (Step (B): The controller "decodes" the instruction 3.Step (C): Following completion of the instruction, the controller provides the address, to the memory unit, at which the data result generated by the operation will be stored. 6 Harvard Architecture 7 Internal Memory (“register”) External memory access is Very slow For quicker retrieval and storage Internal registers 8 Architecture by Instructions and their Executions CISC (Complex Instruction Set Computer) Variety of instructions for complex tasks Instructions of varying length RISC (Reduced Instruction Set Computer) Fewer and simpler instructions High performance microprocessors Pipelined instruction execution (several instructions are executed in parallel) 9 CISC Architecture of prior to mid-1980’s IBM390, Motorola 680x0, Intel80x86 Basic Fetch-Execute sequence to support a large number of complex instructions Complex decoding procedures Complex control unit One instruction achieves a complex task 10 -
What Do We Mean by Architecture?
Embedded programming: Comparing the performance and development workflows for architectures Embedded programming week FABLAB BRIGHTON 2018 What do we mean by architecture? The architecture of microprocessors and microcontrollers are classified based on the way memory is allocated (memory architecture). There are two main ways of doing this: Von Neumann architecture (also known as Princeton) Von Neumann uses a single unified cache (i.e. the same memory) for both the code (instructions) and the data itself, Under pure von Neumann architecture the CPU can be either reading an instruction or reading/writing data from/to the memory. Both cannot occur at the same time since the instructions and data use the same bus system. Harvard architecture Harvard architecture uses different memory allocations for the code (instructions) and the data, allowing it to be able to read instructions and perform data memory access simultaneously. The best performance is achieved when both instructions and data are supplied by their own caches, with no need to access external memory at all. How does this relate to microcontrollers/microprocessors? We found this page to be a good introduction to the topic of microcontrollers and microprocessors, the architectures they use and the difference between some of the common types. First though, it’s worth looking at the difference between a microprocessor and a microcontroller. Microprocessors (e.g. ARM) generally consist of just the Central Processing Unit (CPU), which performs all the instructions in a computer program, including arithmetic, logic, control and input/output operations. Microcontrollers (e.g. AVR, PIC or 8051) contain one or more CPUs with RAM, ROM and programmable input/output peripherals. -
The Intro to GPGPU CPU Vs
12/12/11! The Intro to GPGPU . Dr. Chokchai (Box) Leangsuksun, PhD! Louisiana Tech University. Ruston, LA! ! CPU vs. GPU • CPU – Fast caches – Branching adaptability – High performance • GPU – Multiple ALUs – Fast onboard memory – High throughput on parallel tasks • Executes program on each fragment/vertex • CPUs are great for task parallelism • GPUs are great for data parallelism Supercomputing 20082 Education Program 1! 12/12/11! CPU vs. GPU - Hardware • More transistors devoted to data processing CUDA programming guide 3.1 3 CPU vs. GPU – Computation Power CUDA programming guide 3.1! 2! 12/12/11! CPU vs. GPU – Memory Bandwidth CUDA programming guide 3.1! What is GPGPU ? • General Purpose computation using GPU in applications other than 3D graphics – GPU accelerates critical path of application • Data parallel algorithms leverage GPU attributes – Large data arrays, streaming throughput – Fine-grain SIMD parallelism – Low-latency floating point (FP) computation © David Kirk/NVIDIA and Wen-mei W. Hwu, 2007! ECE 498AL, University of Illinois, Urbana-Champaign! 3! 12/12/11! Why is GPGPU? • Large number of cores – – 100-1000 cores in a single card • Low cost – less than $100-$1500 • Green computing – Low power consumption – 135 watts/card – 135 w vs 30000 w (300 watts * 100) • 1 card can perform > 100 desktops 12/14/09!– $750 vs 50000 ($500 * 100) 7 Two major players 4! 12/12/11! Parallel Computing on a GPU • NVIDIA GPU Computing Architecture – Via a HW device interface – In laptops, desktops, workstations, servers • Tesla T10 1070 from 1-4 TFLOPS • AMD/ATI 5970 x2 3200 cores • NVIDIA Tegra is an all-in-one (system-on-a-chip) ATI 4850! processor architecture derived from the ARM family • GPU parallelism is better than Moore’s law, more doubling every year • GPGPU is a GPU that allows user to process both graphics and non-graphics applications. -
System-On-A-Chip (Soc) & ARM Architecture
System-on-a-Chip (SoC) & ARM Architecture EE2222 Computer Interfacing and Microprocessors Partially based on System-on-Chip Design by Hao Zheng 2020 EE2222 1 Overview • A system-on-a-chip (SoC): • a computing system on a single silicon substrate that integrates both hardware and software. • Hardware packages all necessary electronics for a particular application. • which implemented by SW running on HW. • Aim for low power and low cost. • Also more reliable than multi-component systems. 2020 EE2222 2 Driven by semiconductor advances 2020 EE2222 3 Basic SoC Model 2020 EE2222 4 2020 EE2222 5 SoC vs Processors System on a chip Processors on a chip processor multiple, simple, heterogeneous few, complex, homogeneous cache one level, small 2-3 levels, extensive memory embedded, on chip very large, off chip functionality special purpose general purpose interconnect wide, high bandwidth often through cache power, cost both low both high operation largely stand-alone need other chips 2020 EE2222 6 Embedded Systems • 98% processors sold annually are used in embedded applications. 2020 EE2222 7 Embedded Systems: Design Challenges • Power/energy efficient: • mobile & battery powered • Highly reliable: • Extreme environment (e.g. temperature) • Real-time operations: • predictable performance • Highly complex • A modern automobile with 55 electronic control units • Tightly coupled Software & Hardware • Rapid development at low price 2020 EE2222 8 EECS222A: SoC Description and Modeling Lecture 1 Design Complexity Challenge Design• Productivity Complexity -
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. -
Comparative Study of Various Systems on Chips Embedded in Mobile Devices
Innovative Systems Design and Engineering www.iiste.org ISSN 2222-1727 (Paper) ISSN 2222-2871 (Online) Vol.4, No.7, 2013 - National Conference on Emerging Trends in Electrical, Instrumentation & Communication Engineering Comparative Study of Various Systems on Chips Embedded in Mobile Devices Deepti Bansal(Assistant Professor) BVCOE, New Delhi Tel N: +919711341624 Email: [email protected] ABSTRACT Systems-on-chips (SoCs) are the latest incarnation of very large scale integration (VLSI) technology. A single integrated circuit can contain over 100 million transistors. Harnessing all this computing power requires designers to move beyond logic design into computer architecture, meet real-time deadlines, ensure low-power operation, and so on. These opportunities and challenges make SoC design an important field of research. So in the paper we will try to focus on the various aspects of SOC and the applications offered by it. Also the different parameters to be checked for functional verification like integration and complexity are described in brief. We will focus mainly on the applications of system on chip in mobile devices and then we will compare various mobile vendors in terms of different parameters like cost, memory, features, weight, and battery life, audio and video applications. A brief discussion on the upcoming technologies in SoC used in smart phones as announced by Intel, Microsoft, Texas etc. is also taken up. Keywords: System on Chip, Core Frame Architecture, Arm Processors, Smartphone. 1. Introduction: What Is SoC? We first need to define system-on-chip (SoC). A SoC is a complex integrated circuit that implements most or all of the functions of a complete electronic system. -
System-On-Chip Design with Virtual Components
past designs can a huge chip be com- pleted within a reasonable time. This FEATURE solution usually entails reusing designs from previous generations of products ARTICLE and often leverages design work done by other groups in the same company. Various forms of intercompany cross licensing and technology sharing Thomas Anderson can provide access to design technol- ogy that may be reused in new ways. Many large companies have estab- lished central organizations to pro- mote design reuse and sharing, and to System-on-Chip Design look for external IP sources. One challenge faced by IP acquisi- tion teams is that many designs aren’t well suited for reuse. Designing with with Virtual Components reuse in mind requires extra time and effort, and often more logic as well— requirements likely to be at odds with the time-to-market goals of a product design team. Therefore, a merchant semiconduc- tor IP industry has arisen to provide designs that were developed specifically for reuse in a wide range of applications. These designs are backed by documen- esign reuse for tation and support similar to that d semiconductor provided by a semiconductor supplier. Here in the Recycling projects has evolved The terms “virtual component” from an interesting con- and “core” commonly denote reusable Age, designing for cept to a requirement. Today’s huge semiconductor IP that is offered for system-on-a-chip (SOC) designs rou- license as a product. The latter term is reuse may sound like tinely require millions of transistors. promoted extensively by the Virtual Silicon geometry continues to shrink Socket Interface (VSI) Alliance, a joint a great idea. -
Lecture Notes
Lecture #4-5: Computer Hardware (Overview and CPUs) CS106E Spring 2018, Young In these lectures, we begin our three-lecture exploration of Computer Hardware. We start by looking at the different types of computer components and how they interact during basic computer operations. Next, we focus specifically on the CPU (Central Processing Unit). We take a look at the Machine Language of the CPU and discover it’s really quite primitive. We explore how Compilers and Interpreters allow us to go from the High-Level Languages we are used to programming to the Low-Level machine language actually used by the CPU. Most modern CPUs are multicore. We take a look at when multicore provides big advantages and when it doesn’t. We also take a short look at Graphics Processing Units (GPUs) and what they might be used for. We end by taking a look at Reduced Instruction Set Computing (RISC) and Complex Instruction Set Computing (CISC). Stanford President John Hennessy won the Turing Award (Computer Science’s equivalent of the Nobel Prize) for his work on RISC computing. Hardware and Software: Hardware refers to the physical components of a computer. Software refers to the programs or instructions that run on the physical computer. - We can entirely change the software on a computer, without changing the hardware and it will transform how the computer works. I can take an Apple MacBook for example, remove the Apple Software and install Microsoft Windows, and I now have a Window’s computer. - In the next two lectures we will focus entirely on Hardware. -
Hardware Architecture
Hardware Architecture Components Computing Infrastructure Components Servers Clients LAN & WLAN Internet Connectivity Computation Software Storage Backup Integration is the Key ! Security Data Network Management Computer Today’s Computer Computer Model: Von Neumann Architecture Computer Model Input: keyboard, mouse, scanner, punch cards Processing: CPU executes the computer program Output: monitor, printer, fax machine Storage: hard drive, optical media, diskettes, magnetic tape Von Neumann architecture - Wiki Article (15 min YouTube Video) Components Computer Components Components Computer Components CPU Memory Hard Disk Mother Board CD/DVD Drives Adaptors Power Supply Display Keyboard Mouse Network Interface I/O ports CPU CPU CPU – Central Processing Unit (Microprocessor) consists of three parts: Control Unit • Execute programs/instructions: the machine language • Move data from one memory location to another • Communicate between other parts of a PC Arithmetic Logic Unit • Arithmetic operations: add, subtract, multiply, divide • Logic operations: and, or, xor • Floating point operations: real number manipulation Registers CPU Processor Architecture See How the CPU Works In One Lesson (20 min YouTube Video) CPU CPU CPU speed is influenced by several factors: Chip Manufacturing Technology: nm (2002: 130 nm, 2004: 90nm, 2006: 65 nm, 2008: 45nm, 2010:32nm, Latest is 22nm) Clock speed: Gigahertz (Typical : 2 – 3 GHz, Maximum 5.5 GHz) Front Side Bus: MHz (Typical: 1333MHz , 1666MHz) Word size : 32-bit or 64-bit word sizes Cache: Level 1 (64 KB per core), Level 2 (256 KB per core) caches on die. Now Level 3 (2 MB to 8 MB shared) cache also on die Instruction set size: X86 (CISC), RISC Microarchitecture: CPU Internal Architecture (Ivy Bridge, Haswell) Single Core/Multi Core Multi Threading Hyper Threading vs. -
Architecture of 8051 & Their Pin Details
SESHASAYEE INSTITUTE OF TECHNOLOGY ARIYAMANGALAM , TRICHY – 620 010 ARCHITECTURE OF 8051 & THEIR PIN DETAILS UNIT I WELCOME ARCHITECTURE OF 8051 & THEIR PIN DETAILS U1.1 : Introduction to microprocessor & microcontroller : Architecture of 8085 -Functions of each block. Comparison of Microprocessor & Microcontroller - Features of microcontroller -Advantages of microcontroller -Applications Of microcontroller -Manufactures of microcontroller. U1.2 : Architecture of 8051 : Block diagram of Microcontroller – Functions of each block. Pin details of 8051 -Oscillator and Clock -Clock Cycle -State - Machine Cycle -Instruction cycle –Reset - Power on Reset - Special function registers :Program Counter -PSW register -Stack - I/O Ports . U1.3 : Memory Organisation & I/O port configuration: ROM RAM - Memory Organization of 8051,Interfacing external memory to 8051 Microcontroller vs. Microprocessors 1. CPU for Computers 1. A smaller computer 2. No RAM, ROM, I/O on CPU chip 2. On-chip RAM, ROM, I/O itself ports... 3. Example:Intel’s x86, Motorola’s 3. Example:Motorola’s 6811, 680x0 Intel’s 8051, Zilog’s Z8 and PIC Microcontroller vs. Microprocessors Microprocessor Microcontroller 1. CPU is stand-alone, RAM, ROM, I/O, timer are separate 1. CPU, RAM, ROM, I/O and timer are all on a single 2. designer can decide on the chip amount of ROM, RAM and I/O ports. 2. fix amount of on-chip ROM, RAM, I/O ports 3. expansive 3. for applications in which 4. versatility cost, power and space are 5. general-purpose critical 4. single-purpose uP vs. uC – cont. Applications – uCs are suitable to control of I/O devices in designs requiring a minimum component – uPs are suitable to processing information in computer systems. -
Analysis of Body Bias Control Using Overhead Conditions for Real Time Systems: a Practical Approach∗
IEICE TRANS. INF. & SYST., VOL.E101–D, NO.4 APRIL 2018 1116 PAPER Analysis of Body Bias Control Using Overhead Conditions for Real Time Systems: A Practical Approach∗ Carlos Cesar CORTES TORRES†a), Nonmember, Hayate OKUHARA†, Student Member, Nobuyuki YAMASAKI†, Member, and Hideharu AMANO†, Fellow SUMMARY In the past decade, real-time systems (RTSs), which must in RTSs. These techniques can improve energy efficiency; maintain time constraints to avoid catastrophic consequences, have been however, they often require a large amount of power since widely introduced into various embedded systems and Internet of Things they must control the supply voltages of the systems. (IoTs). The RTSs are required to be energy efficient as they are used in embedded devices in which battery life is important. In this study, we in- Body bias (BB) control is another solution that can im- vestigated the RTS energy efficiency by analyzing the ability of body bias prove RTS energy efficiency as it can manage the tradeoff (BB) in providing a satisfying tradeoff between performance and energy. between power leakage and performance without affecting We propose a practical and realistic model that includes the BB energy and the power supply [4], [5].Itseffect is further endorsed when timing overhead in addition to idle region analysis. This study was con- ducted using accurate parameters extracted from a real chip using silicon systems are enabled with silicon on thin box (SOTB) tech- on thin box (SOTB) technology. By using the BB control based on the nology [6], which is a novel and advanced fully depleted sili- proposed model, about 34% energy reduction was achieved.