Lect12 - Floating Point Arithmetic and Dense Linear Algebra...

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1 Floating Point Arithmetic and Dense Linear Algebra Lecture 12 CS 594 Jack Dongarra 2 Question: ± Suppose we want to compute using four decimal arithmetic: ± S = 1.000 + 1.000x10 4 – 1.000x10 4 ± What’s the answer? ± Ariane 5 rocket ± June 1996 exploded when a 64 bit fl pt number relating to the horizontal velocity of the rocket was converted to a 16 bit signed integer. The number was larger than 32,767, and thus the conversion failed. ± $500M rocket and cargo
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2 3 Two sources of numerical error 1) Round off error 2) Truncation error 4 Round off Error ± Caused by representing a number approximately
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3 5 Problems created by round off error ± 28 Americans were killed on February 25, 1991 by an Iraqi Scud missile in Dhahran, Saudi Arabia. ± The patriot defense system failed to track and intercept the Scud. Why? 6 Problem with Patriot missile ± Clock cycle of 1/10 seconds was represented in 24-bit fixed point register created an error of 9.5 x 10 -8 seconds. ± The battery was on for 100 consecutive hours, thus causing an inaccuracy of .1 (decimal) = 00111101110011001100110011001101 (binary)
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4 7 Problem (cont.) ± The shift calculated in the ranging system of the missile was 687 meters. ± The target was considered to be out of range at a distance greater than 137 meters. 8 Truncation error ± Error caused by truncating or approximating a mathematical procedure.
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5 9 Example of Truncation Error Taking only a few terms of a Maclaurin series to approximate If only 3 terms are used, 10 Defining Floating Point Arithmetic ± Representable numbers ± Scientific notation: +/- d.d…d x r exp ± sign bit +/- ± radix r (usually 2 or 10, sometimes 16) ± significand d.d…d (how many base-r digits d?) ± exponent exp (range?) ± others? ± Operations: ± arithmetic: +,-,x,/,. .. » how to round result to fit in format ± comparison (<, =, >) ± conversion between different formats » short to long FP numbers, FP to integer ± exception handling » what to do for 0/0, 2*largest_number, etc. ± binary/decimal conversion » for I/O, when radix not 10
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6 11 IEEE Floating Point Arithmetic Standard 754 (1985) - Normalized Numbers ± Normalized Nonzero Representable Numbers: +- 1.d…d x 2 exp ± Macheps = Machine epsilon = 2 -#significand bits = relative error in each operation smallest number ± such that fl( 1 + ± ) > 1 ± OV = overflow threshold = largest number ± UN = underflow threshold = smallest number ± +- Zero: +-, significand and exponent all zero ± Why bother with -0 later Format # bits #significand bits macheps #exponent bits exponent range ---------- -------- ----------------------- ------------ -------------------- ---------------------- Single 32 23+1 2 -24 (~10 -7 ) 8 2 -126 - 2 127 (~10 +-38 ) Double 64 52+1 2 -53 (~10 -16 ) 11 2 -1022 - 2 1023 (~10 +-308 ) Double >=80 >=64 <=2 -64 (~10 -19 ) >=15 2 -16382 - 2 16383 (~10 +-4932 ) Extended ( 80 bits on all Intel machines ) 12 IEEE Floating Point Arithmetic Standard 754 - “Denorms” ± Denormalized Numbers: +-0.d…d x 2 min_exp ± sign bit, nonzero significand, minimum exponent ± Fills in gap between UN and 0 ± Underflow Exception ± occurs when exact nonzero result is less than underflow threshold UN ± Ex: UN/3 ± return a denorm, or zero
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7 13 IEEE Floating Point Arithmetic Standard 754 - +- Infinity ± +- Infinity: Sign bit, zero significand, maximum exponent ± Overflow Exception ±
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This note was uploaded on 04/01/2010 for the course COMPUTER S cs202 taught by Professor Jiuhui during the Spring '08 term at 東京国際大学.

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Lect12 - Floating Point Arithmetic and Dense Linear Algebra...

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