- Page 1 and 2: COMPILER TECHNIQUES FOR MATLAB PROG
- Page 3: COMPILER TECHNIQUES FOR MATLAB PROG
- Page 7 and 8: Contents Chapter 1 INTRODUCTION :::
- Page 9 and 10: 7 EXPERIMENTAL RESULTS ::::::::::::
- Page 11 and 12: List of Figures 3.1 Phases of the M
- Page 13 and 14: 7.7 CG speedups on the SGI Power Ch
- Page 15 and 16: 1.1 High-Level Approach for Softwar
- Page 17 and 18: executing their compiled versions.
- Page 19 and 20: structure: (e.g., upper triangular,
- Page 21 and 22: integer. The reason for this is tha
- Page 23 and 24: the high-level semantics of the APL
- Page 25 and 26: Chapter 3 OVERALL STRATEGY 3.1 Rest
- Page 27 and 28: Matlab Program lexical analyzer syn
- Page 29 and 30: according to the grammar rules, pro
- Page 31 and 32: S1: load %(V) S1: load %(V 1 ) S2:
- Page 33 and 34: epresenting variable V 1 will conta
- Page 35 and 36: Structural Inference One of the gre
- Page 37 and 38: eciprocal estimator, which requires
- Page 39 and 40: if (A T .eq. T COMPLEX) then if (B
- Page 41 and 42: S1: temp = 1 S2: X = function(temp)
- Page 43 and 44: if (a D1 .eq. 1) then if (a D2 .eq.
- Page 45 and 46: Chapter 4 INTERNAL REPRESENTATION 4
- Page 47 and 48: Algorithm: Dierentiation Between Va
- Page 49 and 50: entry list variable’s instances V
- Page 51 and 52: S0: load %(n) S0: load %(n 1 ) P1:
- Page 53 and 54: Chapter 5 THE STATIC INFERENCE MECH
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Type of rst Type of second paramete
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Unknown Real Complex Integer Logica
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A = zeros(5,1) for ... ... A(1:5) =
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Assignment to a constant: Attribute
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A B B A scalar vector(p,1) vector(
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Unknown . . . κ i κ j κ l κ m N
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S1: B = rand(2) B 1 = rand(2) S2: A
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[L, U, P] = lu(A) y = Ln (P b) x =
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MATLAB, and x would be computed in
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if (a D1 .eq. 1) then if (c D1 .ne.
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S1: A = ones(5) S2: B = function(A)
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6.2 Dynamic Shape Inference The use
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if (k .gt. P D1 .or. k .gt. P D2) t
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A pointer (P s) to an AST node corr
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x 1 will be already pointing to m 1
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P nr also set to m 1 . Therefore, P
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ALLOCATE statement can be placed ou
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Test Programs: Problem size Lines S
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FD: isanumeric approximation method
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for j = 1:n ... r = sqrt(L(j,j) - s
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1000 SGI Power Challenge 400 Speedu
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7.2.2 Comparison of Compiler Genera
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10 83 91 17 9 8 SPARCstation 10 Spe
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were selected: AQ, due to its real
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inference phases AQ CG 3D Di FD no
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7 6 SGI Power Challenge CG 5 Second
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program. Notice that although the M
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uns, there were no preallocations o
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Chapter 8 CONCLUSIONS AND FUTURE DI
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of techniques for the generation of
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[BE94] William Blume and Rudolf Eig
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[GHR94] E. Gallopoulos, E. Houstis,
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[Pac93] Pacic-Sierra Research Corpo