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Chapter 1 Scientific Computing 1.Computer Arithmetic (1.3) 2.Approximation in Scientific Computing (1.2) January 7
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Floating-Point Number System (FPNS) Mantissa Exponent Fraction
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Examples 54 In base-10 system as 54 = (5 + 4/10) x 10 1 = 5.4 x 10 1 mantissa = 5.4, fraction = 0.4, exponent = 1 In base-2 system 54 = ( 0 + 1x2 1 + 1x 2 2 + 0x2 3 + 1x2 4 + 1x2 5 ) = (0 + 2 + 4 + 0 + 16 + 32 ) = ( 1 + 1/ (2 1 ) + 0/(2 2 ) + 1/(2 3 ) + 1/(2 4 ) + 0/(2 5 )) x 2 5 mantissa = 1.6875, fraction = 0.6875, exponent=5
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Normalization 54 = ( 1 + 1/ (2 1 ) + 0/(2 2 ) + 1/(2 3 ) + 1/(2 4 ) + 0/(2 5 )) x 2 5 = 1.6875 x 32 (normalized) = ( 0 + 1/(2 1 ) + 1/(2 2 )+ 0/(2 3 ) + 1/(2 4 ) + 1/(2 5 )+0/(2 6 ) ) x 2 6 (not normalized)
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There are 126+127+1 = 254 possible exponent values How to represent zero?
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OFL = when all d 0, …, d p-1 = beta - 1 Underflow level Overflow level
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What are the 25 numbers?
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Online Demo at http://www.cse.illinois.edu/iem/floating_point/rounding_rules/
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Absolute and Relative Errors Example Approximate 43.552 with 4.3x10 has absolute error = 0.552 relative error =approx= 0.01267
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Floating-Point Arithmetics
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Cancellation
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For example: with base = 10, p =3. Take x= 23115, y = 23090, there difference of 25 is comparatively much smaller than either x or y (using chopping) what is the difference x-y in this FPNS?
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Quadratic Formula If the coefficients are too large or too small, overflow and underflow could occur. Overflow can be avoided by scaling the coefficients. Cancellation between –b and square root can be avoid by using
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Example (pages 26-27) Take ( base = 10, p=4) a=0.05010, b=-98.78, c=5.015 The correct roots (to ten significant digits) 1971.605916, 0.05077069387 b 2 -4ac = 9756, its square-root is 98.77 The computed roots using standard formula 1972, 0.09980 Using the second formula 1003, 0.05077
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