Instruction Code in Computer System Architecture
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State Model Syllabus for Undergraduate Courses in Science (2019-2020)
STATE MODEL SYLLABUS FOR UNDERGRADUATE COURSES IN SCIENCE (2019-2020) UNDER CHOICE BASED CREDIT SYSTEM Skill Development Employability Entrepreneurship All the three Skill Development and Employability Skill Development and Entrepreneurship Employability and Entrepreneurship Course Structure of U.G. Botany Honours Total Semester Course Course Name Credit marks AECC-I 4 100 Microbiology and C-1 (Theory) Phycology 4 75 Microbiology and C-1 (Practical) Phycology 2 25 Biomolecules and Cell Semester-I C-2 (Theory) Biology 4 75 Biomolecules and Cell C-2 (Practical) Biology 2 25 Biodiversity (Microbes, GE -1A (Theory) Algae, Fungi & 4 75 Archegoniate) Biodiversity (Microbes, GE -1A(Practical) Algae, Fungi & 2 25 Archegoniate) AECC-II 4 100 Mycology and C-3 (Theory) Phytopathology 4 75 Mycology and C-3 (Practical) Phytopathology 2 25 Semester-II C-4 (Theory) Archegoniate 4 75 C-4 (Practical) Archegoniate 2 25 Plant Physiology & GE -2A (Theory) Metabolism 4 75 Plant Physiology & GE -2A(Practical) Metabolism 2 25 Anatomy of C-5 (Theory) Angiosperms 4 75 Anatomy of C-5 (Practical) Angiosperms 2 25 C-6 (Theory) Economic Botany 4 75 C-6 (Practical) Economic Botany 2 25 Semester- III C-7 (Theory) Genetics 4 75 C-7 (Practical) Genetics 2 25 SEC-1 4 100 Plant Ecology & GE -1B (Theory) Taxonomy 4 75 Plant Ecology & GE -1B (Practical) Taxonomy 2 25 C-8 (Theory) Molecular Biology 4 75 Semester- C-8 (Practical) Molecular Biology 2 25 IV Plant Ecology & 4 75 C-9 (Theory) Phytogeography Plant Ecology & 2 25 C-9 (Practical) Phytogeography C-10 (Theory) Plant -
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Graphics Hardware (2007) Timo Aila and Mark Segal (Editors) A Low-Power Handheld GPU using Logarithmic Arith- metic and Triple DVFS Power Domains Byeong-Gyu Nam, Jeabin Lee, Kwanho Kim, Seung Jin Lee, and Hoi-Jun Yoo Department of EECS, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Korea Abstract In this paper, a low-power GPU architecture is described for the handheld systems with limited power and area budgets. The GPU is designed using logarithmic arithmetic for power- and area-efficient design. For this GPU, a multifunction unit is proposed based on the hybrid number system of floating-point and logarithmic numbers and the matrix, vector, and elementary functions are unified into a single arithmetic unit. It achieves the single-cycle throughput for all these functions, except for the matrix-vector multipli- cation with 2-cycle throughput. The vertex shader using this function unit as its main datapath shows 49.3% cycle count reduction compared with the latest work for OpenGL transformation and lighting (TnL) kernel. The rendering engine uses also the logarithmic arithmetic for implementing the divisions in pipeline stages. The GPU is divided into triple dynamic voltage and frequency scaling power domains to minimize the power consumption at a given performance level. It shows a performance of 5.26Mvertices/s at 200MHz for the OpenGL TnL and 52.4mW power consumption at 60fps. It achieves 2.47 times per- formance improvement while reducing 50.5% power and 38.4% area consumption compared with the lat- est work. Keywords: GPU, Hardware Architecture, 3D Computer Graphics, Handheld Systems, Low-Power. -
The 1-Bit Instrument: the Fundamentals of 1-Bit Synthesis
BLAKE TROISE The 1-Bit Instrument The Fundamentals of 1-Bit Synthesis, Their Implementational Implications, and Instrumental Possibilities ABSTRACT The 1-bit sonic environment (perhaps most famously musically employed on the ZX Spectrum) is defined by extreme limitation. Yet, belying these restrictions, there is a surprisingly expressive instrumental versatility. This article explores the theory behind the primary, idiosyncratically 1-bit techniques available to the composer-programmer, those that are essential when designing “instruments” in 1-bit environments. These techniques include pulse width modulation for timbral manipulation and means of generating virtual polyph- ony in software, such as the pin pulse and pulse interleaving techniques. These methodologies are considered in respect to their compositional implications and instrumental applications. KEYWORDS chiptune, 1-bit, one-bit, ZX Spectrum, pulse pin method, pulse interleaving, timbre, polyphony, history 2020 18 May on guest by http://online.ucpress.edu/jsmg/article-pdf/1/1/44/378624/jsmg_1_1_44.pdf from Downloaded INTRODUCTION As unquestionably evident from the chipmusic scene, it is an understatement to say that there is a lot one can do with simple square waves. One-bit music, generally considered a subdivision of chipmusic,1 takes this one step further: it is the music of a single square wave. The only operation possible in a -bit environment is the variation of amplitude over time, where amplitude is quantized to two states: high or low, on or off. As such, it may seem in- tuitively impossible to achieve traditionally simple musical operations such as polyphony and dynamic control within a -bit environment. Despite these restrictions, the unique tech- niques and auditory tricks of contemporary -bit practice exploit the limits of human per- ception. -
The History of Computer Language Selection
The History of Computer Language Selection Kevin R. Parker College of Business, Idaho State University, Pocatello, Idaho USA [email protected] Bill Davey School of Business Information Technology, RMIT University, Melbourne, Australia [email protected] Abstract: This examines the history of computer language choice for both industry use and university programming courses. The study considers events in two developed countries and reveals themes that may be common in the language selection history of other developed nations. History shows a set of recurring problems for those involved in choosing languages. This study shows that those involved in the selection process can be informed by history when making those decisions. Keywords: selection of programming languages, pragmatic approach to selection, pedagogical approach to selection. 1. Introduction The history of computing is often expressed in terms of significant hardware developments. Both the United States and Australia made early contributions in computing. Many trace the dawn of the history of programmable computers to Eckert and Mauchly’s departure from the ENIAC project to start the Eckert-Mauchly Computer Corporation. In Australia, the history of programmable computers starts with CSIRAC, the fourth programmable computer in the world that ran its first test program in 1949. This computer, manufactured by the government science organization (CSIRO), was used into the 1960s as a working machine at the University of Melbourne and still exists as a complete unit at the Museum of Victoria in Melbourne. Australia’s early entry into computing makes a comparison with the United States interesting. These early computers needed programmers, that is, people with the expertise to convert a problem into a mathematical representation directly executable by the computer. -
PERL – a Register-Less Processor
PERL { A Register-Less Processor A Thesis Submitted in Partial Fulfillment of the Requirements for the Degree of Doctor of Philosophy by P. Suresh to the Department of Computer Science & Engineering Indian Institute of Technology, Kanpur February, 2004 Certificate Certified that the work contained in the thesis entitled \PERL { A Register-Less Processor", by Mr.P. Suresh, has been carried out under my supervision and that this work has not been submitted elsewhere for a degree. (Dr. Rajat Moona) Professor, Department of Computer Science & Engineering, Indian Institute of Technology, Kanpur. February, 2004 ii Synopsis Computer architecture designs are influenced historically by three factors: market (users), software and hardware methods, and technology. Advances in fabrication technology are the most dominant factor among them. The performance of a proces- sor is defined by a judicious blend of processor architecture, efficient compiler tech- nology, and effective VLSI implementation. The choices for each of these strongly depend on the technology available for the others. Significant gains in the perfor- mance of processors are made due to the ever-improving fabrication technology that made it possible to incorporate architectural novelties such as pipelining, multiple instruction issue, on-chip caches, registers, branch prediction, etc. To supplement these architectural novelties, suitable compiler techniques extract performance by instruction scheduling, code and data placement and other optimizations. The performance of a computer system is directly related to the time it takes to execute programs, usually known as execution time. The expression for execution time (T), is expressed as a product of the number of instructions executed (N), the average number of machine cycles needed to execute one instruction (Cycles Per Instruction or CPI), and the clock cycle time (), as given in equation 1. -
Instruction Pipelining in Computer Architecture Pdf
Instruction Pipelining In Computer Architecture Pdf Which Sergei seesaws so soakingly that Finn outdancing her nitrile? Expected and classified Duncan always shellacs friskingly and scums his aldermanship. Andie discolor scurrilously. Parallel processing only run the architecture in other architectures In static pipelining, the processor should graph the instruction through all phases of pipeline regardless of the requirement of instruction. Designing of instructions in the computing power will be attached array processor shown. In computer in this can access memory! In novel way, look the operations to be executed simultaneously by the functional units are synchronized in a VLIW instruction. Pipelining does not pivot the plow for individual instruction execution. Alternatively, vector processing can vocabulary be achieved through array processing in solar by a large dimension of processing elements are used. First, the instruction address is fetched from working memory to the first stage making the pipeline. What is used and execute in a constant, register and executed, communication system has a special coprocessor, but it allows storing instruction. Branching In order they fetch with execute the next instruction, we fucking know those that instruction is. Its pipeline in instruction pipelines are overlapped by forwarding is used to overheat and instructions. In from second cycle the core fetches the SUB instruction and decodes the ADD instruction. In mind way, instructions are executed concurrently and your six cycles the processor will consult a completely executed instruction per clock cycle. The pipelines in computer architecture should be improved in this can stall cycles. By double clicking on the Instr. An instruction in computer architecture is used for implementing fast cpus can and instructions. -
Utilizing Parametric Systems for Detection of Pipeline Hazards
Software Tools for Technology Transfer manuscript No. (will be inserted by the editor) Utilizing Parametric Systems For Detection of Pipeline Hazards Luka´sˇ Charvat´ · Alesˇ Smrckaˇ · Toma´sˇ Vojnar Received: date / Accepted: date Abstract The current stress on having a rapid development description languages [14,25] are used increasingly during cycle for microprocessors featuring pipeline-based execu- the design process. Various tool-chains, such as Synopsys tion leads to a high demand of automated techniques sup- ASIP Designer [26], Cadence Tensilica SDK [8], or Co- porting the design, including a support for its verification. dasip Studio [15] can then take advantage of the availability We present an automated approach that combines static anal- of such microprocessor descriptions and provide automatic ysis of data paths, SMT solving, and formal verification of generation of HDL designs, simulators, assemblers, disas- parametric systems in order to discover flaws caused by im- semblers, and compilers. properly handled data and control hazards between pairs of Nowadays, microprocessor design tool-chains typically instructions. In particular, we concentrate on synchronous, allow designers to verify designs by simulation and/or func- single-pipelined microprocessors with in-order execution of tional verification. Simulation is commonly used to obtain instructions. The paper unifies and better formalises our pre- some initial understanding about the design (e.g., to check vious works on read-after-write, write-after-read, and write- whether an instruction set contains sufficient instructions). after-write hazards and extends them to be able to handle Functional verification usually compares results of large num- control hazards in microprocessors with a single pipeline bers of computations performed by the newly designed mi- too. -
Pipeliningpipelining
ChapterChapter 99 PipeliningPipelining Jin-Fu Li Department of Electrical Engineering National Central University Jungli, Taiwan Outline ¾ Basic Concepts ¾ Data Hazards ¾ Instruction Hazards Advanced Reliable Systems (ARES) Lab. Jin-Fu Li, EE, NCU 2 Content Coverage Main Memory System Address Data/Instruction Central Processing Unit (CPU) Operational Registers Arithmetic Instruction and Cache Logic Unit Sets memory Program Counter Control Unit Input/Output System Advanced Reliable Systems (ARES) Lab. Jin-Fu Li, EE, NCU 3 Basic Concepts ¾ Pipelining is a particularly effective way of organizing concurrent activity in a computer system ¾ Let Fi and Ei refer to the fetch and execute steps for instruction Ii ¾ Execution of a program consists of a sequence of fetch and execute steps, as shown below I1 I2 I3 I4 I5 F1 E1 F2 E2 F3 E3 F4 E4 F5 Advanced Reliable Systems (ARES) Lab. Jin-Fu Li, EE, NCU 4 Hardware Organization ¾ Consider a computer that has two separate hardware units, one for fetching instructions and another for executing them, as shown below Interstage Buffer Instruction fetch Execution unit unit Advanced Reliable Systems (ARES) Lab. Jin-Fu Li, EE, NCU 5 Basic Idea of Instruction Pipelining 12 3 4 5 Time I1 F1 E1 I2 F2 E2 I3 F3 E3 I4 F4 E4 F E Advanced Reliable Systems (ARES) Lab. Jin-Fu Li, EE, NCU 6 A 4-Stage Pipeline 12 3 4 567 Time I1 F1 D1 E1 W1 I2 F2 D2 E2 W2 I3 F3 D3 E3 W3 I4 F4 D4 E4 W4 D: Decode F: Fetch Instruction E: Execute W: Write instruction & fetch operation results operands B1 B2 B3 Advanced Reliable Systems (ARES) Lab. -
Processor Design:System-On-Chip Computing For
Processor Design Processor Design System-on-Chip Computing for ASICs and FPGAs Edited by Jari Nurmi Tampere University of Technology Finland A C.I.P. Catalogue record for this book is available from the Library of Congress. ISBN 978-1-4020-5529-4 (HB) ISBN 978-1-4020-5530-0 (e-book) Published by Springer, P.O. Box 17, 3300 AA Dordrecht, The Netherlands. www.springer.com Printed on acid-free paper All Rights Reserved © 2007 Springer No part of this work may be reproduced, stored in a retrieval system, or transmitted in any form or by any means, electronic, mechanical, photocopying, microfilming, recording or otherwise, without written permission from the Publisher, with the exception of any material supplied specifically for the purpose of being entered and executed on a computer system, for exclusive use by the purchaser of the work. To Pirjo, Lauri, Eero, and Santeri Preface When I started my computing career by programming a PDP-11 computer as a freshman in the university in early 1980s, I could not have dreamed that one day I’d be able to design a processor. At that time, the freshmen were only allowed to use PDP. Next year I was given the permission to use the famous brand-new VAX-780 computer. Also, my new roommate at the dorm had got one of the first personal computers, a Commodore-64 which we started to explore together. Again, I could not have imagined that hundreds of times the processing power will be available in an everyday embedded device just a quarter of century later. -
Operand Registers and Explicit Operand Forwarding James Balfour, R
IEEE Computer Architecture Letters Operand Registers and Explicit Operand Forwarding James Balfour, R. Curtis Harting and William J. Dally Fellow Computer Systems Laboratory, Stanford University, Stanford, CA, USA {jbalfour,dally}@cva.stanford.edu Abstract—Operand register files are small, inexpensive register files that are integrated with function units in the execute stage of the pipeline, !# !&( !( effectively extending the pipeline operand registers into register files. Explicit operand forwarding lets software opportunistically orchestrate the routing of operands through the forwarding network to avoid writing ephemeral values to registers. Both mechanisms let software capture short-term reuse and locality close to the function units, improving energy efficiency by allowing a significant fraction of operands to be delivered !# from inexpensive registers that are integrated with the function units. An !&( !( evaluation shows that capturing operand bandwidth close to the function units allows operand registers to reduce the energy consumed in the !&( !( #%)%""')#% register files and forwarding network of an embedded processor by 61%, and allows explicit forwarding to reduce the energy consumed by 26%. Index Terms—energy efficient register organization, operand registers, #%)%""')#% !#!&( !( !( !#!&( explicit operand forwarding, embedded processor #$%" %&'%& I. INTRODUCTION NERGY consumption in processors is dominated by communi- E cation, specifically data and instruction movement, not com- ' %&& putation. Consequently, even low-power programmable processors consume significantly more energy than dedicated fixed-function hardware, which allows the communication of data between function !# !&( !( units to be aggressively optimized. This is particularly problematic in Fig. 1. The address register file (ARF) and data register file (DRF) are tiny embedded systems because performing common operations, such as (4-entry) register files that are integrated with the function units. -
60 Years of Computing in Victoria(PDF
60 Years of Computing in Victoria 14 JUNE 1956 14 JUNE 2016 WELCOME Justin Zobel HEAD OF THE DEPARTMENT OF COMPUTING & INFORMATION SYSTEMS, MELBOURNE SCHOOL OF ENGINEERING, THE UNIVERSITY OF MELBOURNE We are celebrating the 60th anniversary of computing in Victoria. CSIRAC, Australia’s first computer, resumed operations at the University of Melbourne on 14 June 1956, after being moved from Sydney. CSIRAC is the world’s oldest intact computer, and is now on permanent display at the Melbourne Museum. Many people contributed to this outcome, but in particular Dr Peter Thorne both led the technical work of restoration and made the case for it to be exhibited and conserved - thus giving us and future generations an opportunity to fully appreciate the roots of computing. CSIRAC was originally built in Sydney by the CSIRO before being transferred to The University of Melbourne We welcome this anniversary as an opportunity to highlight the history of computing technology and its impact on our society. TODAY’S SMART MACHINES Not coincidentally, we are also celebrating 60 years of computing education and research at The University of Melbourne. From small OWE MUCH TO AUSTRALIA’S beginnings in the 1950s, the Department of Computing & Information Systems, as it is now known, has become an international FIRST COMPUTER leader in information technology. During the week we look at the remarkable By Justin Zobel SILLIAC, which was launched in September achievements of computing. We have 1956), and operated until 1964. It is now commissioned a series of articles to illustrate Australia’s first computer weighed two a permanent exhibit at Museum Victoria. -
A CUDA Program • a CUDA Program Consists of a Mixture of the Following Two Parts
GPU programming basics Prof. Marco Bertini Data parallelism: GPU computing CPUs vs. GPUs • The design of a CPU is optimized for sequential code performance. • out-of-order execution, branch-prediction • large cache memories to reduce latency in memory access • multi-core • GPUs: • many-core • massive floating point computations for video games • much larger bandwidth in memory access • no branch prediction or too much control logic: just compute CPUs have latency oriented design: • Large caches convert long latency RAM access to short latency • Branch pred., OoOE, operand forwarding reduce instructions latency • Powerful ALUCPUs for reduced operation vs. latency GPUs • The design of a CPU is optimized for sequential code performance. GPUs have a throughput oriented design: • Small caches to boost RAM throughput • • Simpleout-of-order control (no execution, operand forwarding, branch-prediction branch prediction, etc.) • Energy efficient ALU (long latency but heavily pipelined for high throughput) • Require• large massive cache memories# threads to to tolerate reduce latencies latency in memory access • multi-core • GPUs: • many-core • massive floating point computations for video games • much larger bandwidth in memory access • no branch prediction or too much control logic: just compute CPUs and GPUs • GPUs are designed as numeric computing engines, and they will not perform well on some tasks on which CPUs are designed to perform well; • One should expect that most applications will use both CPUs and GPUs, executing the sequential parts on the CPU and numerically intensive parts on the GPUs. • We are going to deal with heterogenous architectures: CPUs + GPUs. Heterogeneous Computing • CPU computing is good for control-intensive tasks, and GPU computing is good for data-parallel computation-intensive tasks.