Programmable Digital Signal Processor (PDSP): a Survey
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On the Hardware Reduction of Z-Datapath of Vectoring CORDIC
On the Hardware Reduction of z-Datapath of Vectoring CORDIC R. Stapenhurst*, K. Maharatna**, J. Mathew*, J.L.Nunez-Yanez* and D. K. Pradhan* *University of Bristol, Bristol, UK **University of Southampton, Southampton, UK [email protected] Abstract— In this article we present a novel design of a hardware wordlength larger than 18-bits the hardware requirement of it optimal vectoring CORDIC processor. We present a mathematical becomes more than the classical CORDIC. theory to show that using bipolar binary notation it is possible to eliminate all the arithmetic computations required along the z- In this particular work we propose a formulation to eliminate datapath. Using this technique it is possible to achieve three and 1.5 all the arithmetic operations along the z-datapath for conventional times reduction in the number of registers and adder respectively two-sided vector rotation and thereby reducing the hardware compared to classical CORDIC. Following this, a 16-bit vectoring while increasing the accuracy. Also the resulting architecture CORDIC is designed for the application in Synchronizer for IEEE shows significant hardware saving as the wordlength increases. 802.11a standard. The total area and dynamic power consumption Although we stick to the 2’s complement number system, without of the processor is 0.14 mm2 and 700μW respectively when loss of generality, this formulation can be adopted easily for synthesized in 0.18μm CMOS library which shows its effectiveness redundant arithmetic and higher radix formulation. A 16-bit as a low-area low-power processor. processor developed following this formulation requires 0.14 mm2 area and consumes 700 μW dynamic power when synthesized in 0.18μm CMOS library. -
Chapter 5 Multiprocessors and Thread-Level Parallelism
Computer Architecture A Quantitative Approach, Fifth Edition Chapter 5 Multiprocessors and Thread-Level Parallelism Copyright © 2012, Elsevier Inc. All rights reserved. 1 Contents 1. Introduction 2. Centralized SMA – shared memory architecture 3. Performance of SMA 4. DMA – distributed memory architecture 5. Synchronization 6. Models of Consistency Copyright © 2012, Elsevier Inc. All rights reserved. 2 1. Introduction. Why multiprocessors? Need for more computing power Data intensive applications Utility computing requires powerful processors Several ways to increase processor performance Increased clock rate limited ability Architectural ILP, CPI – increasingly more difficult Multi-processor, multi-core systems more feasible based on current technologies Advantages of multiprocessors and multi-core Replication rather than unique design. Copyright © 2012, Elsevier Inc. All rights reserved. 3 Introduction Multiprocessor types Symmetric multiprocessors (SMP) Share single memory with uniform memory access/latency (UMA) Small number of cores Distributed shared memory (DSM) Memory distributed among processors. Non-uniform memory access/latency (NUMA) Processors connected via direct (switched) and non-direct (multi- hop) interconnection networks Copyright © 2012, Elsevier Inc. All rights reserved. 4 Important ideas Technology drives the solutions. Multi-cores have altered the game!! Thread-level parallelism (TLP) vs ILP. Computing and communication deeply intertwined. Write serialization exploits broadcast communication -
18-447 Computer Architecture Lecture 6: Multi-Cycle and Microprogrammed Microarchitectures
18-447 Computer Architecture Lecture 6: Multi-Cycle and Microprogrammed Microarchitectures Prof. Onur Mutlu Carnegie Mellon University Spring 2015, 1/28/2015 Agenda for Today & Next Few Lectures n Single-cycle Microarchitectures n Multi-cycle and Microprogrammed Microarchitectures n Pipelining n Issues in Pipelining: Control & Data Dependence Handling, State Maintenance and Recovery, … n Out-of-Order Execution n Issues in OoO Execution: Load-Store Handling, … 2 Reminder on Assignments n Lab 2 due next Friday (Feb 6) q Start early! n HW 1 due today n HW 2 out n Remember that all is for your benefit q Homeworks, especially so q All assignments can take time, but the goal is for you to learn very well 3 Lab 1 Grades 25 20 15 10 5 Number of Students 0 30 40 50 60 70 80 90 100 n Mean: 88.0 n Median: 96.0 n Standard Deviation: 16.9 4 Extra Credit for Lab Assignment 2 n Complete your normal (single-cycle) implementation first, and get it checked off in lab. n Then, implement the MIPS core using a microcoded approach similar to what we will discuss in class. n We are not specifying any particular details of the microcode format or the microarchitecture; you can be creative. n For the extra credit, the microcoded implementation should execute the same programs that your ordinary implementation does, and you should demo it by the normal lab deadline. n You will get maximum 4% of course grade n Document what you have done and demonstrate well 5 Readings for Today n P&P, Revised Appendix C q Microarchitecture of the LC-3b q Appendix A (LC-3b ISA) will be useful in following this n P&H, Appendix D q Mapping Control to Hardware n Optional q Maurice Wilkes, “The Best Way to Design an Automatic Calculating Machine,” Manchester Univ. -
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. -
Parallel Computer Architecture
Parallel Computer Architecture Introduction to Parallel Computing CIS 410/510 Department of Computer and Information Science Lecture 2 – Parallel Architecture Outline q Parallel architecture types q Instruction-level parallelism q Vector processing q SIMD q Shared memory ❍ Memory organization: UMA, NUMA ❍ Coherency: CC-UMA, CC-NUMA q Interconnection networks q Distributed memory q Clusters q Clusters of SMPs q Heterogeneous clusters of SMPs Introduction to Parallel Computing, University of Oregon, IPCC Lecture 2 – Parallel Architecture 2 Parallel Architecture Types • Uniprocessor • Shared Memory – Scalar processor Multiprocessor (SMP) processor – Shared memory address space – Bus-based memory system memory processor … processor – Vector processor bus processor vector memory memory – Interconnection network – Single Instruction Multiple processor … processor Data (SIMD) network processor … … memory memory Introduction to Parallel Computing, University of Oregon, IPCC Lecture 2 – Parallel Architecture 3 Parallel Architecture Types (2) • Distributed Memory • Cluster of SMPs Multiprocessor – Shared memory addressing – Message passing within SMP node between nodes – Message passing between SMP memory memory nodes … M M processor processor … … P … P P P interconnec2on network network interface interconnec2on network processor processor … P … P P … P memory memory … M M – Massively Parallel Processor (MPP) – Can also be regarded as MPP if • Many, many processors processor number is large Introduction to Parallel Computing, University of Oregon, -
Micro-Circuits for High Energy Physics*
MICRO-CIRCUITS FOR HIGH ENERGY PHYSICS* Paul F. Kunz Stanford Linear Accelerator Center Stanford University, Stanford, California, U.S.A. ABSTRACT Microprogramming is an inherently elegant method for implementing many digital systems. It is a mixture of hardware and software techniques with the logic subsystems controlled by "instructions" stored Figure 1: Basic TTL Gate in a memory. In the past, designing microprogrammed systems was difficult, tedious, and expensive because the available components were capable of only limited number of functions. Today, however, large blocks of microprogrammed systems have been incorporated into a A input B input C output single I.e., thus microprogramming has become a simple, practical method. false false true false true true true false true true true false 1. INTRODUCTION 1.1 BRIEF HISTORY OF MICROCIRCUITS Figure 2: Truth Table for NAND Gate. The first question which arises when one talks about microcircuits is: What is a microcircuit? The answer is simple: a complete circuit within a single integrated-circuit (I.e.) package or chip. The next question one might ask is: What circuits are available? The answer to this question is also simple: it depends. It depends on the economics of the circuit for the semiconductor manufacturer, which depends on the technology he uses, which in turn changes as a function of time. Thus to understand Figure 3: Logical NOT Circuit. what microcircuits are available today and what makes them different from those of yesterday it is interesting to look into the economics of producing microcircuits. The basic element in a logic circuit is a gate, which is a circuit with a number of inputs and one output and it performs a basic logical function such as AND, OR, or NOT. -
Datapath Design I Systems I
Systems I Datapath Design I Topics Sequential instruction execution cycle Instruction mapping to hardware Instruction decoding Overview How do we build a digital computer? Hardware building blocks: digital logic primitives Instruction set architecture: what HW must implement Principled approach Hardware designed to implement one instruction at a time Plus connect to next instruction Decompose each instruction into a series of steps Expect that most steps will be common to many instructions Extend design from there Overlap execution of multiple instructions (pipelining) Later in this course Parallel execution of many instructions In more advanced computer architecture course 2 Y86 Instruction Set Byte 0 1 2 3 4 5 nop 0 0 addl 6 0 halt 1 0 subl 6 1 rrmovl rA, rB 2 0 rA rB andl 6 2 irmovl V, rB 3 0 8 rB V xorl 6 3 rmmovl rA, D(rB) 4 0 rA rB D jmp 7 0 mrmovl D(rB), rA 5 0 rA rB D jle 7 1 OPl rA, rB 6 fn rA rB jl 7 2 jXX Dest 7 fn Dest je 7 3 call Dest 8 0 Dest jne 7 4 ret 9 0 jge 7 5 pushl rA A 0 rA 8 jg 7 6 popl rA B 0 rA 8 3 Building Blocks fun Combinational Logic A A = Compute Boolean functions of L U inputs B 0 Continuously respond to input changes MUX Operate on data and implement 1 control Storage Elements valA A srcA Store bits valW Register W file dstW Addressable memories valB B Non-addressable registers srcB Clock Loaded only as clock rises Clock 4 Hardware Control Language Very simple hardware description language Can only express limited aspects of hardware operation Parts we want to explore and modify Data -
Computer Architecture Out-Of-Order Execution
Computer Architecture Out-of-order Execution By Yoav Etsion With acknowledgement to Dan Tsafrir, Avi Mendelson, Lihu Rappoport, and Adi Yoaz 1 Computer Architecture 2013– Out-of-Order Execution The need for speed: Superscalar • Remember our goal: minimize CPU Time CPU Time = duration of clock cycle × CPI × IC • So far we have learned that in order to Minimize clock cycle ⇒ add more pipe stages Minimize CPI ⇒ utilize pipeline Minimize IC ⇒ change/improve the architecture • Why not make the pipeline deeper and deeper? Beyond some point, adding more pipe stages doesn’t help, because Control/data hazards increase, and become costlier • (Recall that in a pipelined CPU, CPI=1 only w/o hazards) • So what can we do next? Reduce the CPI by utilizing ILP (instruction level parallelism) We will need to duplicate HW for this purpose… 2 Computer Architecture 2013– Out-of-Order Execution A simple superscalar CPU • Duplicates the pipeline to accommodate ILP (IPC > 1) ILP=instruction-level parallelism • Note that duplicating HW in just one pipe stage doesn’t help e.g., when having 2 ALUs, the bottleneck moves to other stages IF ID EXE MEM WB • Conclusion: Getting IPC > 1 requires to fetch/decode/exe/retire >1 instruction per clock: IF ID EXE MEM WB 3 Computer Architecture 2013– Out-of-Order Execution Example: Pentium Processor • Pentium fetches & decodes 2 instructions per cycle • Before register file read, decide on pairing Can the two instructions be executed in parallel? (yes/no) u-pipe IF ID v-pipe • Pairing decision is based… On data -
This Thesis Has Been Submitted in Fulfilment of the Requirements for a Postgraduate Degree (E.G
This thesis has been submitted in fulfilment of the requirements for a postgraduate degree (e.g. PhD, MPhil, DClinPsychol) at the University of Edinburgh. Please note the following terms and conditions of use: This work is protected by copyright and other intellectual property rights, which are retained by the thesis author, unless otherwise stated. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This thesis cannot be reproduced or quoted extensively from without first obtaining permission in writing from the author. The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the author. When referring to this work, full bibliographic details including the author, title, awarding institution and date of the thesis must be given. Towards the Development of Flexible, Reliable, Reconfigurable, and High- Performance Imaging Systems by Jalal Khalifat A thesis submitted in partial fulfilment of the requirements for the degree of DOCTOR OF PHILOSOPHY The University of Edinburgh May 2016 Declaration I hereby declare that this thesis was composed and originated entirely by myself except where explicitly stated in the text, and that this work has not been submitted for any other degree or professional qualifications. Jalal Khalifat May 2016 Edinburgh, U.K. I Acknowledgements All praises are due to Allah, the most gracious, the most merciful, after three and a half years of continuous work, this work comes to end and it is the moment that I have to thank all the people who have supported me throughout my PhD study and who have contributed to the completion of this thesis. -
Parallel Computing
Lecture 1: Computer Organization 1 Outline • Overview of parallel computing • Overview of computer organization – Intel 8086 architecture • Implicit parallelism • von Neumann bottleneck • Cache memory – Writing cache-friendly code 2 Why parallel computing • Solving an × linear system Ax=b by using Gaussian elimination takes ≈ flops. 1 • On Core i7 975 @ 4.0 GHz,3 which is capable of about 3 60-70 Gigaflops flops time 1000 3.3×108 0.006 seconds 1000000 3.3×1017 57.9 days 3 What is parallel computing? • Serial computing • Parallel computing https://computing.llnl.gov/tutorials/parallel_comp 4 Milestones in Computer Architecture • Analytic engine (mechanical device), 1833 – Forerunner of modern digital computer, Charles Babbage (1792-1871) at University of Cambridge • Electronic Numerical Integrator and Computer (ENIAC), 1946 – Presper Eckert and John Mauchly at the University of Pennsylvania – The first, completely electronic, operational, general-purpose analytical calculator. 30 tons, 72 square meters, 200KW. – Read in 120 cards per minute, Addition took 200µs, Division took 6 ms. • IAS machine, 1952 – John von Neumann at Princeton’s Institute of Advanced Studies (IAS) – Program could be represented in digit form in the computer memory, along with data. Arithmetic could be implemented using binary numbers – Most current machines use this design • Transistors was invented at Bell Labs in 1948 by J. Bardeen, W. Brattain and W. Shockley. • PDP-1, 1960, DEC – First minicomputer (transistorized computer) • PDP-8, 1965, DEC – A single bus -
Performance of Image and Video Processing with General-Purpose
Performance of Image and Video Processing with General-Purpose Processors and Media ISA Extensions y Parthasarathy Ranganathan , Sarita Adve , and Norman P. Jouppi Electrical and Computer Engineering y Western Research Laboratory Rice University Compaq Computer Corporation g fparthas,sarita @rice.edu [email protected] Abstract Media processing refers to the computing required for the creation, encoding/decoding, processing, display, and com- This paper aims to provide a quantitative understanding munication of digital multimedia information such as im- of the performance of image and video processing applica- ages, audio, video, and graphics. The last few years tions on general-purpose processors, without and with me- have seen significant advances in this area, but the true dia ISA extensions. We use detailed simulation of 12 bench- promise of media processing will be seen only when ap- marks to study the effectiveness of current architectural fea- plications such as collaborative teleconferencing, distance tures and identify future challenges for these workloads. learning, and high-quality media-rich content channels ap- Our results show that conventional techniques in current pear in ubiquitously available commodity systems. Fur- processors to enhance instruction-level parallelism (ILP) ther out, advanced human-computer interfaces, telepres- provide a factor of 2.3X to 4.2X performance improve- ence, and immersive and interactive virtual environments ment. The Sun VIS media ISA extensions provide an ad- hold even greater promise. ditional 1.1X to 4.2X performance improvement. The ILP One obstacle in achieving this promise is the high com- features and media ISA extensions significantly reduce the putational demands imposed by these applications. -
Low Power Asynchronous Digital Signal Processing
LOW POWER ASYNCHRONOUS DIGITAL SIGNAL PROCESSING A thesis submitted to the University of Manchester for the degree of Doctor of Philosophy in the Faculty of Science & Engineering October 2000 Michael John George Lewis Department of Computer Science 1 Contents Chapter 1: Introduction ....................................................................................14 Digital Signal Processing ...............................................................................15 Evolution of digital signal processors ....................................................17 Architectural features of modern DSPs .........................................................19 High performance multiplier circuits .....................................................20 Memory architecture ..............................................................................21 Data address generation .........................................................................21 Loop management ..................................................................................23 Numerical precision, overflows and rounding .......................................24 Architecture of the GSM Mobile Phone System ...........................................25 Channel equalization ..............................................................................28 Error correction and Viterbi decoding ...................................................29 Speech transcoding ................................................................................31 Half-rate and enhanced