Floating-Point Operator V7.1 Logicore IP Product Guide
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Decimal Layouts for IEEE 754 Strawman3
IEEE 754-2008 ECMA TC39/TG1 – 25 September 2008 Mike Cowlishaw IBM Fellow Overview • Summary of the new standard • Binary and decimal specifics • Support in hardware, standards, etc. • Questions? 2 Copyright © IBM Corporation 2008. All rights reserved. IEEE 754 revision • Started in December 2000 – 7.7 years – 5.8 years in committee (92 participants + e-mail) – 1.9 years in ballot (101 voters, 8 ballots, 1200+ comments) • Removes many ambiguities from 754-1985 • Incorporates IEEE 854 (radix-independent) • Recommends or requires more operations (functions) and more language support 3 Formats • Separates sets of floating-point numbers (and the arithmetic on them) from their encodings (‘interchange formats’) • Includes the 754-1985 basic formats: – binary32, 24 bits (‘single’) – binary64, 53 bits (‘double’) • Adds three new basic formats: – binary128, 113 bits (‘quad’) – decimal64, 16-digit (‘double’) – decimal128, 34-digit (‘quad’) 4 Why decimal? A web page… • Parking at Manchester airport… • £4.20 per day … … for 10 days … … calculated on-page using ECMAScript Answer shown: 5 Why decimal? A web page… • Parking at Manchester airport… • £4.20 per day … … for 10 days … … calculated on-page using ECMAScript Answer shown: £41.99 (Programmer must have truncated to two places.) 6 Where it costs real money… • Add 5% sales tax to a $ 0.70 telephone call, rounded to the nearest cent • 1.05 x 0.70 using binary double is exactly 0.734999999999999986677323704 49812151491641998291015625 (should have been 0.735) • rounds to $ 0.73, instead of $ 0.74 -
Floating Point Representation (Unsigned) Fixed-Point Representation
Floating point representation (Unsigned) Fixed-point representation The numbers are stored with a fixed number of bits for the integer part and a fixed number of bits for the fractional part. Suppose we have 8 bits to store a real number, where 5 bits store the integer part and 3 bits store the fractional part: 1 0 1 1 1.0 1 1 $ 2& 2% 2$ 2# 2" 2'# 2'$ 2'% Smallest number: Largest number: (Unsigned) Fixed-point representation Suppose we have 64 bits to store a real number, where 32 bits store the integer part and 32 bits store the fractional part: "# "% + /+ !"# … !%!#!&. (#(%(" … ("% % = * !+ 2 + * (+ 2 +,& +,# "# "& & /# % /"% = !"#× 2 +!"&× 2 + ⋯ + !&× 2 +(#× 2 +(%× 2 + ⋯ + ("%× 2 0 ∞ (Unsigned) Fixed-point representation Range: difference between the largest and smallest numbers possible. More bits for the integer part ⟶ increase range Precision: smallest possible difference between any two numbers More bits for the fractional part ⟶ increase precision "#"$"%. '$'#'( # OR "$"%. '$'#'(') # Wherever we put the binary point, there is a trade-off between the amount of range and precision. It can be hard to decide how much you need of each! Scientific Notation In scientific notation, a number can be expressed in the form ! = ± $ × 10( where $ is a coefficient in the range 1 ≤ $ < 10 and + is the exponent. 1165.7 = 0.0004728 = Floating-point numbers A floating-point number can represent numbers of different order of magnitude (very large and very small) with the same number of fixed bits. In general, in the binary system, a floating number can be expressed as ! = ± $ × 2' $ is the significand, normally a fractional value in the range [1.0,2.0) . -
IEEE Standard 754 for Binary Floating-Point Arithmetic
Work in Progress: Lecture Notes on the Status of IEEE 754 October 1, 1997 3:36 am Lecture Notes on the Status of IEEE Standard 754 for Binary Floating-Point Arithmetic Prof. W. Kahan Elect. Eng. & Computer Science University of California Berkeley CA 94720-1776 Introduction: Twenty years ago anarchy threatened floating-point arithmetic. Over a dozen commercially significant arithmetics boasted diverse wordsizes, precisions, rounding procedures and over/underflow behaviors, and more were in the works. “Portable” software intended to reconcile that numerical diversity had become unbearably costly to develop. Thirteen years ago, when IEEE 754 became official, major microprocessor manufacturers had already adopted it despite the challenge it posed to implementors. With unprecedented altruism, hardware designers had risen to its challenge in the belief that they would ease and encourage a vast burgeoning of numerical software. They did succeed to a considerable extent. Anyway, rounding anomalies that preoccupied all of us in the 1970s afflict only CRAY X-MPs — J90s now. Now atrophy threatens features of IEEE 754 caught in a vicious circle: Those features lack support in programming languages and compilers, so those features are mishandled and/or practically unusable, so those features are little known and less in demand, and so those features lack support in programming languages and compilers. To help break that circle, those features are discussed in these notes under the following headings: Representable Numbers, Normal and Subnormal, Infinite -
IEEE 754 Format (From Last Time)
IEEE 754 Format (from last time) ● Single precision format S Exponent Significand 1 8 23 The exponent is represented in bias 127 notation. Why? ● Example: 52.25 = 00110100.010000002 5 Normalize: 001.10100010000002 x 2 (127+5) 0 10000100 10100010000000000000000 0100 0010 0101 0001 0000 0000 0000 0000 52.25 = 0x42510000 08/29/2017 Comp 411 - Fall 2018 1 IEEE 754 Limits and Features ● SIngle precision limitations ○ A little more than 7 decimal digits of precision ○ Minimum positive normalized value: ~1.18 x 10-38 ○ Maximum positive normalized value: ~3.4 x 1038 ● Inaccuracies become evident after multiple single precision operations ● Double precision format 08/29/2017 Comp 411 - Fall 2018 2 IEEE 754 Special Numbers ● Zero - ±0 A floating point number is considered zero when its exponent and significand are both zero. This is an exception to our “hidden 1” normalization trick. There are also a positive and negative zeros. S 000 0000 0 000 0000 0000 0000 0000 0000 ● Infinity - ±∞ A floating point number with a maximum exponent (all ones) is considered infinity which can also be positive or negative. S 111 1111 1 000 0000 0000 0000 0000 0000 ● Not a Number - NaN for ±0/±0, ±∞/±∞, log(-42), etc. S 111 1111 1 non-zero 08/29/2017 Comp 411 - Fall 2018 3 A Quick Wake-up exercise What decimal value is represented by 0x3f800000, when interpreted as an IEEE 754 single precision floating point number? 08/29/2017 Comp 411 - Fall 2018 4 Bits You can See The smallest element of a visual display is called a “pixel”. -
SPARC Assembly Language Reference Manual
SPARC Assembly Language Reference Manual 2550 Garcia Avenue Mountain View, CA 94043 U.S.A. A Sun Microsystems, Inc. Business 1995 Sun Microsystems, Inc. 2550 Garcia Avenue, Mountain View, California 94043-1100 U.S.A. All rights reserved. This product or document is protected by copyright and distributed under licenses restricting its use, copying, distribution and decompilation. No part of this product or document may be reproduced in any form by any means without prior written authorization of Sun and its licensors, if any. Portions of this product may be derived from the UNIX® system, licensed from UNIX Systems Laboratories, Inc., a wholly owned subsidiary of Novell, Inc., and from the Berkeley 4.3 BSD system, licensed from the University of California. Third-party software, including font technology in this product, is protected by copyright and licensed from Sun’s Suppliers. RESTRICTED RIGHTS LEGEND: Use, duplication, or disclosure by the government is subject to restrictions as set forth in subparagraph (c)(1)(ii) of the Rights in Technical Data and Computer Software clause at DFARS 252.227-7013 and FAR 52.227-19. The product described in this manual may be protected by one or more U.S. patents, foreign patents, or pending applications. TRADEMARKS Sun, Sun Microsystems, the Sun logo, SunSoft, the SunSoft logo, Solaris, SunOS, OpenWindows, DeskSet, ONC, ONC+, and NFS are trademarks or registered trademarks of Sun Microsystems, Inc. in the United States and other countries. UNIX is a registered trademark in the United States and other countries, exclusively licensed through X/Open Company, Ltd. OPEN LOOK is a registered trademark of Novell, Inc. -
X86-64 Machine-Level Programming∗
x86-64 Machine-Level Programming∗ Randal E. Bryant David R. O'Hallaron September 9, 2005 Intel’s IA32 instruction set architecture (ISA), colloquially known as “x86”, is the dominant instruction format for the world’s computers. IA32 is the platform of choice for most Windows and Linux machines. The ISA we use today was defined in 1985 with the introduction of the i386 microprocessor, extending the 16-bit instruction set defined by the original 8086 to 32 bits. Even though subsequent processor generations have introduced new instruction types and formats, many compilers, including GCC, have avoided using these features in the interest of maintaining backward compatibility. A shift is underway to a 64-bit version of the Intel instruction set. Originally developed by Advanced Micro Devices (AMD) and named x86-64, it is now supported by high end processors from AMD (who now call it AMD64) and by Intel, who refer to it as EM64T. Most people still refer to it as “x86-64,” and we follow this convention. Newer versions of Linux and GCC support this extension. In making this switch, the developers of GCC saw an opportunity to also make use of some of the instruction-set features that had been added in more recent generations of IA32 processors. This combination of new hardware and revised compiler makes x86-64 code substantially different in form and in performance than IA32 code. In creating the 64-bit extension, the AMD engineers also adopted some of the features found in reduced-instruction set computers (RISC) [7] that made them the favored targets for optimizing compilers. -
Automatic Hardware Generation for Reconfigurable Architectures
Razvan˘ Nane Automatic Hardware Generation for Reconfigurable Architectures Automatic Hardware Generation for Reconfigurable Architectures PROEFSCHRIFT ter verkrijging van de graad van doctor aan de Technische Universiteit Delft, op gezag van de Rector Magnificus prof. ir. K.C.A.M Luyben, voorzitter van het College voor Promoties, in het openbaar te verdedigen op donderdag 17 april 2014 om 10:00 uur door Razvan˘ NANE Master of Science in Computer Engineering Delft University of Technology geboren te Boekarest, Roemenie¨ Dit proefschrift is goedgekeurd door de promotor: Prof. dr. K.L.M. Bertels Samenstelling promotiecommissie: Rector Magnificus voorzitter Prof. dr. K.L.M. Bertels Technische Universiteit Delft, promotor Prof. dr. E. Visser Technische Universiteit Delft Prof. dr. W.A. Najjar University of California Riverside Prof. dr.-ing. M. Hubner¨ Ruhr-Universitat¨ Bochum Dr. H.P. Hofstee IBM Austin Research Laboratory Dr. ir. A.C.J. Kienhuis Universiteit van Leiden Dr. ir. J.S.S.M Wong Technische Universiteit Delft Prof. dr. ir. Geert Leus Technische Universiteit Delft, reservelid Automatic Hardware Generation for Reconfigurable Architectures Dissertation at Delft University of Technology Copyright c 2014 by R. Nane All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without permission of the author. ISBN 978-94-6186-271-6 Printed by CPI Koninklijke Wohrmann,¨ Zutphen, The Netherlands To my family Automatic Hardware Generation for Reconfigurable Architectures Razvan˘ Nane Abstract ECONFIGURABLE Architectures (RA) have been gaining popularity rapidly in the last decade for two reasons. -
FPGA Based Quadruple Precision Floating Point Arithmetic for Scientific Computations
International Journal of Advanced Computer Research (ISSN (print): 2249-7277 ISSN (online): 2277-7970) Volume-2 Number-3 Issue-5 September-2012 FPGA Based Quadruple Precision Floating Point Arithmetic for Scientific Computations 1Mamidi Nagaraju, 2Geedimatla Shekar 1Department of ECE, VLSI Lab, National Institute of Technology (NIT), Calicut, Kerala, India 2Asst.Professor, Department of ECE, Amrita Vishwa Vidyapeetham University Amritapuri, Kerala, India Abstract amounts, and fractions are essential to many computations. Floating-point arithmetic lies at the In this project we explore the capability and heart of computer graphics cards, physics engines, flexibility of FPGA solutions in a sense to simulations and many models of the natural world. accelerate scientific computing applications which Floating-point computations suffer from errors due to require very high precision arithmetic, based on rounding and quantization. Fast computers let IEEE 754 standard 128-bit floating-point number programmers write numerically intensive programs, representations. Field Programmable Gate Arrays but computed results can be far from the true results (FPGA) is increasingly being used to design high due to the accumulation of errors in arithmetic end computationally intense microprocessors operations. Implementing floating-point arithmetic in capable of handling floating point mathematical hardware can solve two separate problems. First, it operations. Quadruple Precision Floating-Point greatly speeds up floating-point arithmetic and Arithmetic is important in computational fluid calculations. Implementing a floating-point dynamics and physical modelling, which require instruction will require at a generous estimate at least accurate numerical computations. However, twenty integer instructions, many of them conditional modern computers perform binary arithmetic, operations, and even if the instructions are executed which has flaws in representing and rounding the on an architecture which goes to great lengths to numbers. -
View of Methodology 21
KNOWLEDGE-GUIDEDMETHODOLOGYFOR SOFTIPANALYSIS BY BHANUPRATAPSINGH Submitted in partial fulfillment of the requirements For the degree of Doctor of Philosophy Dissertation Advisor: Dr. Christos Papachristou Department of Electrical Engineering and Computer Science CASEWESTERNRESERVEUNIVERSITY January 2015 CASEWESTERNRESERVEUNIVERSITY SCHOOLOFGRADUATESTUDIES we hereby approve the thesis of BHANUPRATAPSINGH candidate for the PH.D. degree. chair of the committee DR.CHRISTOSPAPACHRISTOU DR.FRANCISMERAT DR.DANIELSAAB DR.HONGPINGZHAO DR.FRANCISWOLFF date AUG 2 1 , 2 0 1 4 ∗ We also certify that written approval has been obtained for any propri- etary material contained therein. Dedicated to my family and friends. CONTENTS 1 introduction1 1.1 Motivation and Statement of Problem . 1 1.1.1 Statement of Problem . 6 1.2 Major Contributions of the Research . 7 1.2.1 Expert System Based Approach . 7 1.2.2 Specification Analysis Methodology . 9 1.2.3 RTL Analysis Methodology . 9 1.2.4 Spec and RTL Correspondence . 10 1.3 Thesis Outline . 10 2 background and related work 11 Abstract . 11 2.1 Existing Soft-IP Verification Techniques . 11 2.1.1 Simulation Based Methods . 11 2.1.2 Formal Techniques . 13 2.2 Prior Work . 15 2.2.1 Specification Analysis . 15 2.2.2 Reverse Engineering . 17 2.2.3 IP Quality and RTL Analysis . 19 2.2.4 KB System . 20 3 overview of methodology 21 Abstract . 21 3.1 KB System Overview . 21 3.1.1 Knowledge Base Organization . 24 3.2 Specification KB Overview . 26 3.3 RTL KB Overview . 29 iv contents v 3.4 Confidence and Coverage Metrics . 30 3.5 Introduction to CLIPS and XML . -
X86 Intrinsics Cheat Sheet Jan Finis [email protected]
x86 Intrinsics Cheat Sheet Jan Finis [email protected] Bit Operations Conversions Boolean Logic Bit Shifting & Rotation Packed Conversions Convert all elements in a packed SSE register Reinterpet Casts Rounding Arithmetic Logic Shift Convert Float See also: Conversion to int Rotate Left/ Pack With S/D/I32 performs rounding implicitly Bool XOR Bool AND Bool NOT AND Bool OR Right Sign Extend Zero Extend 128bit Cast Shift Right Left/Right ≤64 16bit ↔ 32bit Saturation Conversion 128 SSE SSE SSE SSE Round up SSE2 xor SSE2 and SSE2 andnot SSE2 or SSE2 sra[i] SSE2 sl/rl[i] x86 _[l]rot[w]l/r CVT16 cvtX_Y SSE4.1 cvtX_Y SSE4.1 cvtX_Y SSE2 castX_Y si128,ps[SSE],pd si128,ps[SSE],pd si128,ps[SSE],pd si128,ps[SSE],pd epi16-64 epi16-64 (u16-64) ph ↔ ps SSE2 pack[u]s epi8-32 epu8-32 → epi8-32 SSE2 cvt[t]X_Y si128,ps/d (ceiling) mi xor_si128(mi a,mi b) mi and_si128(mi a,mi b) mi andnot_si128(mi a,mi b) mi or_si128(mi a,mi b) NOTE: Shifts elements right NOTE: Shifts elements left/ NOTE: Rotates bits in a left/ NOTE: Converts between 4x epi16,epi32 NOTE: Sign extends each NOTE: Zero extends each epi32,ps/d NOTE: Reinterpret casts !a & b while shifting in sign bits. right while shifting in zeros. right by a number of bits 16 bit floats and 4x 32 bit element from X to Y. Y must element from X to Y. Y must from X to Y. No operation is SSE4.1 ceil NOTE: Packs ints from two NOTE: Converts packed generated. -
Powerpc User Instruction Set Architecture Book I Version 2.01
PowerPC User Instruction Set Architecture Book I Version 2.01 September 2003 Manager: Joe Wetzel/Poughkeepsie/IBM Technical Content: Ed Silha/Austin/IBM Cathy May/Watson/IBM Brad Frey/Austin/IBM The following paragraph does not apply to the United Kingdom or any country or state where such provisions are inconsistent with local law. The specifications in this manual are subject to change without notice. This manual is provided “AS IS”. Interna- tional Business Machines Corp. makes no warranty of any kind, either expressed or implied, including, but not limited to, the implied warranties of merchantability and fitness for a particular purpose. International Business Machines Corp. does not warrant that the contents of this publication or the accompanying source code examples, whether individually or as one or more groups, will meet your requirements or that the publication or the accompanying source code examples are error-free. This publication could include technical inaccuracies or typographical errors. Changes are periodically made to the information herein; these changes will be incorporated in new editions of the publication. Address comments to IBM Corporation, Internal Zip 9630, 11400 Burnett Road, Austin, Texas 78758-3493. IBM may use or distribute whatever information you supply in any way it believes appropriate without incurring any obligation to you. The following terms are trademarks of the International Business Machines Corporation in the United States and/or other countries: IBM PowerPC RISC/System 6000 POWER POWER2 POWER4 POWER4+ IBM System/370 Notice to U.S. Government Users—Documentation Related to Restricted Rights—Use, duplication or disclosure is subject to restrictions set fourth in GSA ADP Schedule Contract with IBM Corporation. -
UM0434 E200z3 Powerpc Core Reference Manual
UM0434 e200z3 PowerPC core Reference manual Introduction The primary objective of this user’s manual is to describe the functionality of the e200z3 embedded microprocessor core for software and hardware developers. This book is intended as a companion to the EREF: A Programmer's Reference Manual for Freescale Book E Processors (hereafter referred to as EREF). Book E is a PowerPC™ architecture definition for embedded processors that ensures binary compatibility with the user-instruction set architecture (UISA) portion of the PowerPC architecture as it was jointly developed by Apple, IBM, and Motorola (referred to as the AIM architecture). This document distinguishes among the three levels of the architectural and implementation definition, as follows: ● The Book E architecture—Book E defines a set of user-level instructions and registers that are drawn from the user instruction set architecture (UISA) portion of the AIM definition PowerPC architecture. Book E also includes numerous supervisor-level registers and instructions as they were defined in the AIM version of the PowerPC architecture for the virtual environment architecture (VEA) and the operating environment architecture (OEA). Because the operating system resources (such as the MMU and interrupts) defined by Book E differ greatly from those defined by the AIM architecture, Book E introduces many new registers and instructions. ● Freescale Book E implementation standards (EIS)—In many cases, the Book E architecture definition provides a general framework, leaving specific details up to the implementation. To ensure consistency among its Book E implementations, Freescale has defined implementation standards that provide an additional layer of architecture between Book E and the actual devices.