Process and Quality Control and Calibration Programs of the National Bureau of Standards

Total Page:16

File Type:pdf, Size:1020Kb

Process and Quality Control and Calibration Programs of the National Bureau of Standards NBSIR 87-3596 Process and Quality Control and Calibration Programs of the National Bureau of Standards U.S. DEPARTMENT OF COMMERCE National Bureau of Standards Gaithersburg, MD 20899 June 1987 Final Report Prepared for: The U.S. Congress in Response to Public Law 99.574 NBSIR 87-3596 PROCESS AND QUALITY CONTROL AND CALIBRATION PROGRAMS OF THE NATIONAL BUREAU OF STANDARDS U.S. DEPARTMENT OF COMMERCE National Bureau of Standards Gaithersburg, MD 20899 June 1987 Final Report Prepared for: The U.S. Congress in Response to Public Law 99.574 U.S. DEPARTMENT OF COMMERCE, Malcolm Baldrige, Secretary NATIONAL BUREAU OF STANDARDS. Ernest Ambler. Director , , , FOREWORD 99- 574^- October charged the Public Law , enacted 28, 1986, Director of the National Bureau of Standards (NBS) to ask the Bureau's major clients about their needs for research and services related to NBS "process and quality control and calibration programs". This report is in response to that request. (Excerpt from P.L. 99-574) PROCESS AND QUALITY CONTROL AND CALIBRATION PROGRAMS Sec. 9 (a) The Director of the National Bureau of Standards shall hold discussions with representatives of Federal agencies, including the Department of Defense, the Department of Energy, the National Aeronautics and Space Administration, the Federal Aviation Administra- tion, the National Institutes of Health, the Nuclear Regulatory Commission, and the Federal Communications Commission, which use (or the contractors of which depend on) the process and quality control and calibra- tion programs of the Bureau, and with companies, organizations and major engineering societies from the private sector, in order to determine the extent of the demand for research and services under such programs the appropriate methods of paying for research and services under such programs and with willingness of , Federal agencies and the private sector to pay for such research and services. (b) Within six months after the date of the enactment of this Act^, the Director shall submit to the Committee on Science and Technology of the House of Representatives and the Committee on Commerce, Science, and Transportation of the Senate a report of the Director's findings based on the discussions held under subsections (a) together with recommendations for such legislative actions as may be needed to implement a comprehensive Federal process and quality control and calibration program. 1 Public Law 99-574, Section 9, Parts (a) and (b) National Bureau of Standards Authorization Act. ^ The National Bureau of Standards was later granted a two -month extension of this deadline. i ‘ TABLE OF CONTENTS Foreword i Table of Contents iii Executive Summary v I. NBS ROLES, PRODUCTS, & CUSTOMERS A. Introduction 1 B . NBS Measurement Services 8 C. Customers 21 II. COMMON CUSTOMER THEMES A. Lead Agency Status 29 B. Cost Recovery and Pricing of Services 33 C. Measurement and the Current National Concern with Competitiveness 37 III. SENIOR MANAGEMENT VISITS BY NBS TO ITS CUSTOMERS A. Results 41 B. Attendees 55 Appendix A. Customer Needs for Calibrations & Special Tests 73 Appendix B. Customer Needs for Standard Reference Materials 103 Appendix C. Defense Department Needs for Measurement Research & Services 151 Appendix D. The Status of Emerging Technologies: An Economic/Technological Assessment to the Year 2000 177 iii EXECUTIVE SUMMARY General Observations There has been an explosion in applied science in the last two decades that is manifested in a considerable number of emerg- ing technologies Computers and robots are revolutionizing the manufacturing industries. Ceramics, polymers, and composites are revolutionizing the materials industries. Biotechnology is re- volutionizing the chemical, agricultural, medical, and drug in- dustries. Computers, telecommunications, and optoelectronics are revolutionizing financial, information, and government services and operations as well as manufacturing. New materials that be- come superconducting at near- room temperature hold tremendous promise for the electric power, medical, and transportation indus- tries . Movement from basic commodities and materials to higher- value-added products and systems is inevitable and irreversible. Opportunities afforded by the new technologies and challenges from worldwide competition will compel industry to build highly- flexible manufacturing facilities. Customers will benefit from a previously undreamed of variety of products. The Nation is facing a challenge. Economic competition is increasing throughout the world. The technology- induced rise of new industries and revamping of older industries is taking place in a context of intense global competition. New technologies, new industries, new products and services mean that a new technolog- ical infrastructure -- including measurements, test methods, stan- dards, and evaluated data -- has to be constructed and integrated. The private sector is underinvesting in the science and tech- nology which underlies industrial process design, process control, and quality assurance. Because it is difficult to capture the returns from investment in this science and technology, industry ^•Under the direction of Deputy Secretary of Commerce Clarence J. Brown, NBS Director Ernest Ambler recently chaired a Department of Commerce committee to identify emerging technologies and barriers to their expedient commercial application. The Department's re- port, "The Status of Emerging Technologies: An Economic/Technolog- ical Assessment to the Year 2000", is included as Appendix D. v systematically underinvests in its production, to the detriment of national economic growth and international competitiveness. American firms and Government agencies believe that imple- mentation of process control and quality assurance in the United States is and ought to be primarily the responsibility of the producers of the Nation's goods and services, that is, the indi- vidual firms, organizations, and agencies. NBS shares this view. No Federal program, no matter how competent or well-meaning, can assume decision-making responsibility for those who take the risks and reap the rewards. In order to respond effectively to the global competitive challenge, our customers see a need for new measurement services at earlier stages in the product or program development process. This comes at a time when the mechanism for generating these ser- vices has become reactive to the product or program needs so that measurement support is often available late in the cycle . This inhibits first- to -market strategies, slows down product introduc- tion, and can cause major setbacks in Government programs. The National Bureau of Standards also faces a challenge. While measurements and standards for existing technologies and industries continue to require NBS support, new research and ser- vices are needed to bring measurement uniformity and compatibility to an array of new technologies. New, emerging technologies have enlarged the scope of measurement requirements; and new kinds of automated processes have changed the scale of measurement support required (e.g., for real-time, in-situ measurement ). Customer Reactions When asked about the need for a national program for process and quality control, nearly all of the Bureau's industrial cus- tomers expressed the view that the current implementation of the Nation's process control and calibration program, which assigns NBS the role of a central reference laboratory, is the most ap- propriate national program. The firms, Government agencies, and other laboratories we visited recognize the importance of process control and quality assurance to their organizations and to the Nation. vi . Our customers also believe that the National Bureau of Stan- dards plays a unique role with respect to infrastructure support for process control and quality assurance in the Nation. Our customers believe that NBS must provide the measurement foundation needed for process control and quality assurance in the private and public sectors. Many would like to see NBS explicitly design- ated the lead national laboratory^ for advanced thinking and ex- perimentation in the measurement science and technology that un- derlies gains in process control and quality assurance. Our customers also endorse the Bureau's unique, non- regula- tory role that relies on voluntary participation by industry. They believe that NBS should provide technical tools and informa- tion to lubricate our free enterprise engine; measurement tools and information which underlie the process control and quality assurance of all firms and facilitate company- to -company consis- tency in key measurements, but which do not interfere with their proprietary interests. The customers we visited recognize the symbiotic relationship that exists between forefront research and measurement services. They find the Bureau's measurement services valuable because they are linked to U.S. national standards maintained by NBS. Measure- ment services are seen as mechanisms for transferring measurement science and theory into practice in industry and elsewhere. Even though a particular service may seem to be provided through rela- tively routine operations, customers value the fact that each measurement service is built on a sound experimental and theoret- ical basis, is validated, and is capable of rapid adaptation to high levels of performance. 9 "Lead Agency" is the term applied to an agency with a mis- sion that crosses agency lines. A "lead agency's" authorization and funding may require
Recommended publications
  • Introduction to Measurements & Error Analysis
    Introduction to Measurements & Error Analysis The Uncertainty of Measurements Some numerical statements are exact: Mary has 3 brothers, and 2 + 2 = 4. However, all measurements have some degree of uncertainty that may come from a variety of sources. The process of evaluating this uncertainty associated with a measurement result is often called uncertainty analysis or error analysis. The complete statement of a measured value should include an estimate of the level of confidence associated with the value. Properly reporting an experimental result along with its uncertainty allows other people to make judgments about the quality of the experiment, and it facilitates meaningful comparisons with other similar values or a theoretical prediction. Without an uncertainty estimate, it is impossible to answer the basic scientific question: “Does my result agree with a theoretical prediction or results from other experiments?” This question is fundamental for deciding if a scientific hypothesis is confirmed or refuted. When we make a measurement, we generally assume that some exact or true value exists based on how we define what is being measured. While we may never know this true value exactly, we attempt to find this ideal quantity to the best of our ability with the time and resources available. As we make measurements by different methods, or even when making multiple measurements using the same method, we may obtain slightly different results. So how do we report our findings for our best estimate of this elusive true value? The most common way to show the range of values that we believe includes the true value is: measurement = best estimate ± uncertainty (units) Let’s take an example.
    [Show full text]
  • Software Testing
    Software Testing PURPOSE OF TESTING CONTENTS I. Software Testing Background II. Software Error Case Studies 1. Disney Lion King 2. Intel Pentium Floating Point Division Bug 3. NASA Mars Polar Lander 4. Patriot Missile Defense System 5. Y2K Bug III. What is Bug? 1. Terms for Software Failure 2. Software Bug: A Formal Definition 3. Why do Bugs occur? and cost of bug. 4. What exactly does a Software Tester do? 5. What makes a good Software Tester? IV. Software Development Process 1. Product Components 2. What Effort Goes into a Software Product? 3. What parts make up a Software Product? 4. Software Project Staff V. Software Development Lifecycle Models 1. Big Bang Model 2. Code and Fix Model 3. Waterfall Model 4. Spiral Model VI. The Realities of Software Testing VII. Software Testing Terms and Definition 1. Precision and Accuracy 2. Verification and Validation 3. Quality Assurance and Quality Control Anuradha Bhatia Software Testing I. Software Testing Background 1. Software is a set of instructions to perform some task. 2. Software is used in many applications of the real world. 3. Some of the examples are Application software, such as word processors, firmware in an embedded system, middleware, which controls and co-ordinates distributed systems, system software such as operating systems, video games, and websites. 4. All of these applications need to run without any error and provide a quality service to the user of the application. 5. The software has to be tested for its accurate and correct working. Software Testing: Testing can be defined in simple words as “Performing Verification and Validation of the Software Product” for its correctness and accuracy of working.
    [Show full text]
  • Breathe London-NPL-Statistical Methods for Characterisation Of
    Statistical methods for performance characterisation of lower-cost sensors J D Hayward, A Forbes, N A Martin, S Bell, G Coppin, G Garcia and D Fryer 1.1 Introduction This appendix summarises the progress of employing the Breathe London monitoring data together with regulated reference measurements to investigate the application of machine learning tools to extract information with a view to quantifying measurement uncertainty. The Breathe London project generates substantial data from the instrumentation deployed, and the analysis requires a comparison against the established reference methods. The first task was to develop programs to extract the various datasets being employed from different providers and to store them in a stan- dardised format for further processing. This data curation allowed us to audit the data, establishing errors in the AQMesh data and the AirView cars as well as monitor any variances in the data sets caused by conditions such as fog/extreme temperatures. This includes writing a program to parse the raw AirView data files from the high quality refer- ence grade instruments installed in the mobile platforms (Google AirView cars), programs to commu- nicate with and download data from the Applications Program Interfaces (APIs) provided by both Air Monitors (AQMesh sensor systems) and Imperial College London (formerly King’s College London) (London Air Quality Network), and a program that automatically downloads CSV files from the DE- FRA website, which contains the air quality data from the Automatic Urban Rural Network (AURN). This part of the development has had to overcome significant challenges including the accommo- dation of different pollutant concentration units from the different database sources, different file formats, and the incorporation of data flags to describe the data ratification status.
    [Show full text]
  • EXPERIMENTAL METHOD Linear Dimension, Weight and Density
    UNIVERSITI TEKNIKAL No Dokumen: No. Isu/Tarikh: MALAYSIA MELAKA SB/MTU/T1/BMCU1022/1 4/06-07-2009 EXPERIMENTAL METHOD No. Semakan/Tarikh Jumlah Muka Surat Linear Dimension, Weight and Density 4/09-09-2009 4 OBJECTIVE Investigation of different types of equipment for linear dimension measurements and to study measurement accuracy and precision using commonly used measuring equipments. LEARNING OUTCOME At the end of this laboratory session, students should be able to 1. Identify various dimensional measuring equipments commonly used in a basic engineering laboratory. 2. Apply dimensional measuring equipments to measure various objects accurately. 3. Compare the measured data measured using different measuring equipments. 4. Determine the measured dimensional difference using different equipments correctly. 5. Answer basic questions related to the made measurement correctly. 6. Present the measured data in form of report writing according to the normal technical report standard and make clear conclusions of the undertaken tasks. THEORY Basic physical quantity is referred to a quantity which is measurable such as weight, length and time. These quantities could be combined and formed what one called the derived quantities. Some of the examples of derived quantities include parameter such as area, volume, density, velocity, force and many others. Measurement is a comparison process between standard quantities (true value) with measured quantity. Measurement apparatus complete with unit and dimension must be used in order to make a good and correct measurement. Accuracy means how close the measured value to the standard (true) value. Precision of measurement refers to repeatable values of the measurement and the results showed that its uncertainty is of the lowest degree.
    [Show full text]
  • Implementation and Performance Analysis of Precision Time Protocol on Linux Based System-On-Chip Platform
    Implementation and Performance Analysis of Precision Time Protocol on Linux based System-On-Chip Platform Mudassar Ahmed [email protected] MASTERPROJECT Kiel University of Applied Science MSc. Information Engineering in Kiel im Mai 2018 Declaration I hereby declare and confirm that this project is entirely the result of my own original work. Where other sources of information have been used, they have been indicated as such and properly acknowledged. I further declare that this or similar work has not been submitted for credit elsewhere. Kiel, May 9, 2018 Mudassar Ahmed [email protected] i Contents Declaration i Abstract iv List of Symbols and Abbreviations vii 1 Introduction 1 1.1 Research Objectives and Goals . 2 1.2 Approach . 2 1.3 Outline . 2 2 Literature Review 3 2.1 Time Synchronization . 3 2.2 Time Synchronization Technologies . 4 2.3 Overview of IEEE 1588 Precision Time Protocol (PTP) . 4 2.3.1 Scope of PTP Standard: . 5 2.3.2 Protocol Standard Messages . 5 2.3.3 Protocol Standard Devices . 6 2.3.4 Message Exchange and Delay Computation . 7 2.3.5 Protocol Hierarchy Establishment Mechanism . 9 3 PTP Infrastructure in Linux 11 3.1 Timestamping Mechanisms . 11 3.1.1 Software Timestamping . 11 3.1.2 Hardware Timestamping . 12 3.1.3 Linux kernel Support for Timestamping . 13 3.2 PTP Clock Infrastructure and Control API . 14 4 Design and Implementation 16 4.1 Tools and technologies . 16 4.1.1 LinuxPTP . 16 4.1.2 PTPd . 18 4.1.3 stress-ng . 18 4.1.4 iPerf .
    [Show full text]
  • Understanding Measurement Uncertainty in Certified Reference Materials 02 Accuracy and Precision White Paper Accuracy and Precision White Paper 03
    → White Paper Understanding measurement uncertainty in certified reference materials 02 Accuracy and Precision White Paper Accuracy and Precision White Paper 03 The importance of measurement uncertainty. This paper provides an overview of the importance of measurement uncertainty in the manufacturing and use of certified reference gases. It explains the difference between error and uncertainty, accuracy and precision. No measurement can be made with 100 percent accuracy. There is Every stage of the process, every measurement device used always a degree of uncertainty, but for any important measurement, introduces some uncertainty. Identifying and quantifying each source it’s essential to identify every source of uncertainty and to quantify the of uncertainty in order to present a test result with a statement uncertainty introduced by each source. quantifying the uncertainty associated with the result can be challenging. But no measurement is complete unless it is accompanied In every field of commerce and industry, buyers require certified by such a statement. measurements to give them assurances of the quality of goods supplied: the tensile strength of steel; the purity of a drug; the heating This white paper will provide an overview of sources of measurement power of natural gas, for example. uncertainty relating to the manufacture and use of certified reference gases. It will explain how uncertainty reported with a test result can Suppliers rely on test laboratories, either their own or third parties, be calculated and it will explain the important differences between to perform the analysis or measurement necessary to provide these uncertainty, accuracy and precision. assurances. Those laboratories in turn rely on the accuracy and precision of their test instruments, the composition of reference materials, and the rigour of their procedures, to deliver reliable and accurate measurements.
    [Show full text]
  • ECE3340 Introduction to the Limit of Computer Numerical Capability – Precision and Accuracy Concepts PROF
    ECE3340 Introduction to the limit of computer numerical capability – precision and accuracy concepts PROF. HAN Q. LE Computing errors …~ 99 – 99.9% of computing numerical errors are likely due to user’s coding errors (syntax, algorithm)… and the tiny remaining portion may be due to user’s lack of understanding how numerical computation works… Hope this course will help you on this problems Homework/Classwork 1 CHECK OUT THE PERFORMANCE OF YOUR COMPUTER CW Click open this APP Click to ask your machine the smallest number it can handle (this example shows 64-bit x86 architecture) Log base 2 of the number Do the same for the largest HW number Click to ask the computer the smallest relative difference between two number that it can tell apart. This is called machine epsilon If you use an x86 64-bit CPU, the above is what you get. HW-Problem 1 Use any software (C++, C#, MATLAB, Excel,…) but not Mathematica (because it is too smart and can handle the test below) to do this: 1. Let’s denote xmax be the largest number your computer can handle in the APP test. Let x be a number just below xmax , such as ~0.75 xmax. (For example, I choose x=1.5*10^308). Double it (2*x) and print the result. 2. Let xmin be your computer smallest number. Choose x just above it. Then find 0.5*x and print output. Here is an example what happens in Excel: Excel error: instead of giving the correct answer 3*10^308, Number just slightly less than it gives error output.
    [Show full text]
  • Accurate Measurement of Small Execution Times – Getting Around Measurement Errors Carlos Moreno, Sebastian Fischmeister
    1 Accurate Measurement of Small Execution Times – Getting Around Measurement Errors Carlos Moreno, Sebastian Fischmeister Abstract—Engineers and researchers often require accurate example, a typical mitigation approach consists of executing measurements of small execution times or duration of events in F multiple times, as shown below: a program. Errors in the measurement facility can introduce time start = get_current_time() important challenges, especially when measuring small intervals. Repeat N times: Mitigating approaches commonly used exhibit several issues; in Execute F particular, they only reduce the effect of the error, and never time end = get_current_time() eliminate it. In this letter, we propose a technique to effectively // execution time = (end - start) / N eliminate measurement errors and obtain a robust statistical The execution time that we obtain is subject to the mea- estimate of execution time or duration of events in a program. surement error divided by N; by choosing a large enough The technique is simple to implement, yet it entirely eliminates N, we can make this error arbitrarily low. However, this the systematic (non-random) component of the measurement error, as opposed to simply reduce it. Experimental results approach has several potential issues: (1) repeating N times confirm the effectiveness of the proposed method. can in turn introduce an additional unknown overhead, if coded as a for loop. Furthermore, this is subject to uncertainty in I. MOTIVATION that the compiler may or may not implement loop unrolling, meaning that the user could be unaware of whether this Software engineers and researchers often require accurate overhead is present; (2) the efficiency of the error reduction measurements of small execution times or duration of events in process is low; that is, we require a large N (thus, potentially a program.
    [Show full text]
  • Guidance for the Validation of Analytical Methodology and Calibration of Equipment Used for Testing of Illicit Drugs in Seized Materials and Biological Specimens
    Vienna International Centre, PO Box 500, 1400 Vienna, Austria Tel.: (+43-1) 26060-0, Fax: (+43-1) 26060-5866, www.unodc.org Guidance for the Validation of Analytical Methodology and Calibration of Equipment used for Testing of Illicit Drugs in Seized Materials and Biological Specimens FOR UNITED NATIONS USE ONLY United Nations publication ISBN 978-92-1-148243-0 Sales No. E.09.XI.16 *0984578*Printed in Austria ST/NAR/41 V.09-84578—October 2009—200 A commitment to quality and continuous improvement Photo credits: UNODC Photo Library Laboratory and Scientific Section UNITED NATIONS OFFICE ON DRUGS AND CRIME Vienna Guidance for the Validation of Analytical Methodology and Calibration of Equipment used for Testing of Illicit Drugs in Seized Materials and Biological Specimens A commitment to quality and continuous improvement UNITED NATIONS New York, 2009 Acknowledgements This manual was produced by the Laboratory and Scientific Section (LSS) of the United Nations Office on Drugs and Crime (UNODC) and its preparation was coor- dinated by Iphigenia Naidis and Satu Turpeinen, staff of UNODC LSS (headed by Justice Tettey). LSS wishes to express its appreciation and thanks to the members of the Standing Panel of the UNODC’s International Quality Assurance Programme, Dr. Robert Anderson, Dr. Robert Bramley, Dr. David Clarke, and Dr. Pirjo Lillsunde, for the conceptualization of this manual, their valuable contributions, the review and finali- zation of the document.* *Contact details of named individuals can be requested from the UNODC Laboratory and Scientific Section (P.O. Box 500, 1400 Vienna, Austria). ST/NAR/41 UNITED NATIONS PUBLICATION Sales No.
    [Show full text]
  • The Trade-Off Between Accuracy and Precision in Latent Variable Models of Mediation Processes
    Journal of Personality and Social Psychology © 2011 American Psychological Association 2011, Vol. 101, No. 6, 1174–1188 0022-3514/11/$12.00 DOI: 10.1037/a0024776 The Trade-Off Between Accuracy and Precision in Latent Variable Models of Mediation Processes Alison Ledgerwood Patrick E. Shrout University of California, Davis New York University Social psychologists place high importance on understanding mechanisms and frequently employ mediation analyses to shed light on the process underlying an effect. Such analyses can be conducted with observed variables (e.g., a typical regression approach) or latent variables (e.g., a structural equation modeling approach), and choosing between these methods can be a more complex and consequential decision than researchers often realize. The present article adds to the literature on mediation by examining the relative trade-off between accuracy and precision in latent versus observed variable modeling. Whereas past work has shown that latent variable models tend to produce more accurate estimates, we demonstrate that this increase in accuracy comes at the cost of increased standard errors and reduced power, and examine this relative trade-off both theoretically and empirically in a typical 3-variable mediation model across varying levels of effect size and reliability. We discuss implications for social psychologists seeking to uncover mediating variables and provide 3 practical recommendations for maximizing both accuracy and precision in mediation analyses. Keywords: mediation, latent variable, structural
    [Show full text]
  • Numeric Issues in Test Software Correctness
    NUMERIC ISSUES IN TEST SOFTWARE CORRECTNESS Robert G. Hayes, Raytheon Infrared Operations, 805.562.2336, [email protected] Gary B. Hughes, Ph.D., Raytheon Infrared Operations 805.562.2348, [email protected] Phillip M. Dorin, Ph.D., Loyola Marymount University, 310.338.0000, [email protected] Raymond J. Toal, Ph.D., Loyola Marymount University, 310.338.2773, [email protected] ABSTRACT Test system designers are comfortable with the concepts of precision and accuracy with regard to measurements achieved with modern instrumentation. In a well-designed test system, great care is taken to ensure accurate measurements, with rigorous attention to instrument specifications and calibration. However, measurement values are subjected to representation and manipulation as limited precision floating-point numbers by test software. This paper investigates some of the issues related to floating point representation of measurement values, as well as the consequences of algorithm selection. To illustrate, we consider the test case of standard deviation calculations as used in the testing of Infrared Focal Plane Arrays. We consider the concept of using statistically-based techniques for selection of an appropriate algorithm based on measurement values, and offer guidelines for the proper expression and manipulation of measurement values within popular test software programming frameworks. Keywords: measurement accuracy, preCIsIOn, floating-point representation, standard deviation, statistically based algorithm selection, Monte Carlo techniques. 1 INTRODUCTION Some well-known software bugs have resulted in security compromises, sensItive data corruption, bills for items never purchased, spacecraft crashing on other planets, and the loss of human life. Ensuring correctness of software is a necessity. We work toward software correctness via two approaches: testing and formal verification.
    [Show full text]
  • Precise and Accurate Processor Simulation Harold W
    Precise and Accurate Processor Simulation Harold W. Cain, Kevin M. Lepak, Brandon A. Schwartz, and Mikko H. Lipasti Computer Sciences Department Electrical and Computer Engineering University of Wisconsin University of Wisconsin 1210 W. Dayton Street 1415 Engineering Drive Madison, WI 53706 Madison, WI 53706 {cain,baschwar}@cs.wisc.edu {lepak,mikko}@ece.wisc.edu Abstract Outside of the industrial design cycle, simulators are also Precise and accurate simulation of processors and com- heavily used in the computer architecture academic puter systems is a painstaking, time-consuming, and research community. Within this context, simulators are error-prone task. Abstraction and simplification are primarily used as a vehicle for demonstrating or comparing powerful tools for reducing the cost and complexity of the utility of new architectural features, compilation tech- simulation, but are known to reduce precision. Similarly, niques, or microarchitectural techniques, rather than for limiting and simplifying the workloads that are used to helping to guide an actual design project. As a result, aca- drive simulation can simplify the task of the computer demic simulators are rarely used for functional or perfor- architect, while placing the accuracy of the simulation at mance validation, but strictly for proof of concept, design risk. Historically, precision has been favored over accu- space exploration, or quantitative trade-off analysis. racy, resulting in simulators that are able to analyze Simulation can occur at various levels of abstraction. minute machine model variations while mispredicting— Some possible approaches and their benefits and draw- sometimes dramatically—the actual performance of the backs are summarized in Table 1. For example, flexible processor being simulated.
    [Show full text]