Performance and Evaluation of Lisp Systems - Dreamsongs

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§ 3.9 Traverse 165 3.9.4 Raw Data Raw Time Traverse Initialization Implementation CPU GC Real Paging SAIL 6.69 45.14 51.82 Lambda 18.70 1.20 Lambda (MC) 11.50 0.14 3600 8.62 0.33 3600 + IFU 6.37 0.25 Dandelion 48.00 1.16 Dolphin 100.00 1.25 Dorado 20.50 0.49 S-1 1.93 PSL-SUN 30.07 0.00 PSL-20 7.59 0.00 PSL-3081 1.80 0.00 PSL-Cray PSL-750 35.53 0.00 PSL-750 (VMS) 31.20 0.00 PSL-780 15.06 0.00 PSL-DN300 PSL-DN600 PSL-DN160 29.84 0.00 PSL-HP200 13.54 0.00 PSL-HP-UX 14.89 0.00 InterLispVax 780 24.78 MV4000 CL 96.26 MV8000 CL 74.39 MV10000 CL 27.77 3600 + FPA 6.37 0.25 750 NIL 38.92 39.71 8600 CL 6.12 0.00
166 Raw Time Traverse Initialization Implementation CPU GC Real Paging 780 CL 20.76 0.00 785 CL 13.10 0.00 750 CL 35.44 0.00 730 CL 94.77 0.00 Perq 46.53 750 Franz TrlOn & LclfYes 32.98 19.30 TrlOn & LclfNo 35.44 19.72 TrlOff & LclfYes 33.17 20.75 TrlOff & LclfNo 51.23 21.03 780 Franz TrlOn & LclfYes 18.47 11.80 TrlOn & LclfNo 20.42 11.77 TrlOff & LclfYes 18.70 12.73 TrlOff & LclfNo 29.61 12.82 Franz 68000 TrlOn & LclfYes 43.32 21.17 TrlOn & LclfNo 44.98 21.10 TrlOff & LclfYes 55.16 24.52 TrlOff & LclfNo 70.64 24.48 InterLisp-10 37.62 6.09 LM-2 41.23
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Performance and Evaluation of Lisp
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ii When I began the adventure on wh
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Acknowledgements This book is reall
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Contents Chapter 1 Introduction . .
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Performance and Evaluation of Lisp
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2 to be a plethora of facts, only t
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4 An instruction pipeline is used t
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6 to assign any location the name o
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8 voking a closure) can be accompli
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10 (Lisp machine, SEUS [Weyhrauch 1
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12 which takes a function with some
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14 free objects or until a threshol
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16 1.1.2.6 Arithmetic Arithmetic is
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18 Different rounding modes in the
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20 1.3 Major Lisp Facilities There
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22 by studying the size of the tabl
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24 1.4.1 Know What is Being Measure
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26 With 100 such functions and no l
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28 the MacLisp compiler generates f
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30 machine will perform background
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32 2.1.2 Function Call MacLisp func
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34 2.2 MIT CADR Symbolics Inc. and
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36 2.3 Symbolics 2.3.1 3600 The 360
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38 Most of the 3600’s architectur
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40 Like the CADR, the compiler for
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42 2.4 LMI Lambda LISP Machine, Inc
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44 bits in the tag field of every o
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46 2.5 S-1 Lisp S-1 Lisp runs on th
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48 7 Program Counter 8 GC Pointer (
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50 2.5.4 Systemic Quantities Vector
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52 The next time FOO is invoked, th
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54 2.7 NIL NIL (New Implementation
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56 The arguments to the function ar
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58 2.8 Spice Lisp Spice Lisp is an
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60 3. Activating the frame by makin
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62 The benchmarks were run on a Per
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64 than there is for one without, a
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66 2.10 Portable Standard Lisp Port
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68 7. Finishing up and tuning 2.10.
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70 Apollo Dn300 This is an MC68010-
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72 2.10.5 Function Call Compiled-to
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74 array utility package. Additiona
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76 2.12 Data General Common Lisp Da
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78 To determine the type, the high
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80 2. The benchmark results contain
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82 little else but function calls (
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84 ;PUSH, ADJSP both do bounds ;che
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86 Raw Time Tak Implementation CPU
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88 Tak Times On Symbolics LM-2 4.44
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90 Tak Times On SAIL (KLB) in MacLi
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92 In TAKF, changing the variable F
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94 In Vax NIL, there appears to be
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96 3.2.4 Raw Data Raw Time Stak Imp
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98 As Peter Deutsch has pointed out
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100 that THROW uses is linear in th
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102 3.3.4 Raw Data Raw Time Ctak Im
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104 It measures EBOX milliseconds.
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106 Because of the average size of
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108 Raw Time Takl Implementation CP
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110 3.5 Takr 3.5.1 The Program (def
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112 of 8.2. Meter for Tak0 TAK0 817
Page 123 and 124: 114 Raw Time Takr Implementation CP
Page 125 and 126: 116 3.6 Boyer Here is what Bob Boye
Page 127 and 128: 118 (defun rewrite-with-lemmas (ter
Page 129 and 130: 120 (equal (equal (plus a b) (zero)
Page 131 and 132: 122 (equal (power-eval (big-plus x
Page 133 and 134: 124 (equal (numberp (greatest-facto
Page 135 and 136: 126 (equal (times x (add1 y)) (if (
Page 137 and 138: 128 (defun test () (prog (ans term)
Page 139 and 140: 130 the program uses the axioms sto
Page 141 and 142: 132 Meter for Add-Lemma during TEST
Page 143 and 144: 134 Raw Time Boyer Implementation C
Page 145 and 146: 136 3.7 Browse 3.7.1 The Program ;;
Page 147 and 148: 138 ((eq (char1 (car pat)) #\*) (le
Page 149 and 150: 140 The symbol names are GENSYMed;
Page 151 and 152: 142 Meter for Match Car’s 1319800
Page 153 and 154: 144 Raw Time Browse Implementation
Page 155 and 156: 146 3.8 Destructive 3.8.1 The Progr
Page 157 and 158: 148 3.8.3 Translation Notes Meter f
Page 159 and 160: 150 3.8.4 Raw Data Raw Time Destruc
Page 161 and 162: 152 Very few programs that I have b
Page 163 and 164: 154 (defun traverse-remove (n q) (c
Page 165 and 166: 156 (defmacro init-traverse() (prog
Page 167 and 168: 158 node. The number of nodes visit
Page 169 and 170: 160 3.9.3 Translation Notes In INTE
Page 171 and 172: 162 (TSELECT (LAMBDA (N Q) (for N (
Page 173: 164 (TIMIT (LAMBDA NIL (TIMEALL (SE
Page 177 and 178: 168 Raw Time Traverse Implementatio
Page 179 and 180: 170 3.10 Derivative 3.10.1 The Prog
Page 181 and 182: 172 3.10.4 Raw Data Raw Time Deriv
Page 183 and 184: 174 The benchmark should solve a pr
Page 185 and 186: 176 (defun dderiv (a) (cond ((atom
Page 187 and 188: 178 3.11.4 Raw Data Raw Time Dderiv
Page 189 and 190: 180 I find it rather startling that
Page 191 and 192: 182 3.12.2 Analysis This benchmark
Page 193 and 194: 184 Raw Time Fdderiv Implementation
Page 195 and 196: 186 3.13 Division by 2 3.13.1 The P
Page 197 and 198: 188 3.13.4 Raw Data Raw Time Iterat
Page 199 and 200: 190 Raw Time Recursive Div2 Impleme
Page 201 and 202: 192 If naive users write cruddy cod
Page 203 and 204: 194 l6 (cond ((< k j) (setq j (- j
Page 205 and 206: 196 3.14.3 Translation Notes The IN
Page 207 and 208: 198 (for J to LE1 do (* Loop thru b
Page 209 and 210: 200 3.14.4 Raw Data Raw Time FFT Im
Page 211 and 212: 202 This is not to say Franz’s co
Page 213 and 214: 204 (defun place (i j) (let ((end (
Page 215 and 216: 206 (definePiece 2 1 0 1) (definePi
Page 217 and 218: 208 During the search, the first ei
Page 219 and 220: 210 (CONSTANTS SIZE TYPEMAX D CLASS
Page 221 and 222: 212 (START (LAMBDA NIL (for M from
Page 223 and 224: 214 3.15.4 Raw Data Raw Time Puzzle
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216 Presumably this is because 2-di
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218 (defun try (i depth) (cond ((=
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220 Meter for Try =’s 19587224 Re
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222 (LAST-POSITION (LAMBDA NIL (OR
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224 3.16.4 Raw Data Raw Time Triang
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226 I also tried TRIANG, but gave u
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228 The test pattern is a tree that
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230 Raw Time Fprint Implementation
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232 3.18 File Read 3.18.1 The Progr
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234 Raw Time Fread Implementation C
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236 3.19 Terminal Print 3.19.1 The
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238 Raw Time Tprint Implementation
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240 3.20 Polynomial Manipulation 3.
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242 (defun pplus (x y) (cond ((pcoe
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244 (defun ptimes3 (y) (prog (e u c
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246 The variables in the polynomial
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248 Meter for (Bench 2) Signp’s 3
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250 3.20.3 Raw Data Raw Time Frpoly
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252 Raw Time Frpoly Power = 2 r2 =
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256 Raw Time Frpoly Power = 5 r = x
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262 Raw Time Frpoly Power = 10 r =
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268 Raw Time Frpoly Power = 15 r =
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274 Well, it certainly is hard to e
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276 sophisticated Lisp implementati
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278 [Foderaro 1982] Foderaro, J. K.
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280
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282 context-switching, 7. Cray-1, 4
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284 multi-processing Lisp, 7. MV400
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