Performance and Evaluation of Lisp Systems - Dreamsongs

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§ 3.4 Takl 107 3.4.4 Raw Data Raw Time Takl Implementation CPU GC Real Paging SAIL 2.81 0.00 4.02 Lambda 10.70 0.00 Lambda (MC) 5.31 0.00 3600 6.44 0.00 3600 + IFU 4.95 0.00 Dandelion 14.00 0.00 Dolphin 45.60 0.00 Dorado 3.62 0.00 S-1 2.92 PSL-SUN 9.91 0.00 PSL-20 2.52 0.00 PSL-3081 0.61 0.00 PSL-Cray 0.30 0.00 PSL-750 15.45 0.00 PSL-750 (VMS) 12.36 0.00 PSL-780 5.27 0.00 PSL-DN300 12.90 0.00 PSL-DN600 10.92 0.00 PSL-DN160 3.98 0.00 PSL-HP200 5.73 0.00 PSL-HP-UX 6.39 0.00 InterLispVax 780 9.87 MV4000 CL 17.93 MV8000 CL 10.80 MV10000 CL 5.52 3600 + FPA 4.95 0.00 750 NIL 39.13 39.27 8600 CL 2.03 0.00
108 Raw Time Takl Implementation CPU GC Real Paging 780 CL 7.34 0.00 785 CL 5.26 0.00 750 CL 12.35 0.00 730 CL 34.15 0.00 Perq 21.73 750 Franz TrlOn & LclfYes 12.60 0.00 TrlOn & LclfNo 18.40 0.00 TrlOff & LclfYes 12.37 0.00 TrlOff & LclfNo 47.02 0.00 780 Franz TrlOn & LclfYes 6.17 0.00 TrlOn & LclfNo 9.72 0.00 TrlOff & LclfYes 6.18 0.00 TrlOff & LclfNo 24.67 0.00 Franz 68000 TrlOn & LclfYes 12.82 66.64 TrlOn & LclfNo 16.00 67.14 TrlOff & LclfYes 12.82 46.05 TrlOff & LclfNo 43.12 46.38 InterLisp-10 3.78 0.00 LM-2 25.90
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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
Page 65 and 66: 56 The arguments to the function ar
Page 67 and 68: 58 2.8 Spice Lisp Spice Lisp is an
Page 69 and 70: 60 3. Activating the frame by makin
Page 71 and 72: 62 The benchmarks were run on a Per
Page 73 and 74: 64 than there is for one without, a
Page 75 and 76: 66 2.10 Portable Standard Lisp Port
Page 77 and 78: 68 7. Finishing up and tuning 2.10.
Page 79 and 80: 70 Apollo Dn300 This is an MC68010-
Page 81 and 82: 72 2.10.5 Function Call Compiled-to
Page 83 and 84: 74 array utility package. Additiona
Page 85 and 86: 76 2.12 Data General Common Lisp Da
Page 87 and 88: 78 To determine the type, the high
Page 89 and 90: 80 2. The benchmark results contain
Page 91 and 92: 82 little else but function calls (
Page 93 and 94: 84 ;PUSH, ADJSP both do bounds ;che
Page 95 and 96: 86 Raw Time Tak Implementation CPU
Page 97 and 98: 88 Tak Times On Symbolics LM-2 4.44
Page 99 and 100: 90 Tak Times On SAIL (KLB) in MacLi
Page 101 and 102: 92 In TAKF, changing the variable F
Page 103 and 104: 94 In Vax NIL, there appears to be
Page 105 and 106: 96 3.2.4 Raw Data Raw Time Stak Imp
Page 107 and 108: 98 As Peter Deutsch has pointed out
Page 109 and 110: 100 that THROW uses is linear in th
Page 111 and 112: 102 3.3.4 Raw Data Raw Time Ctak Im
Page 113 and 114: 104 It measures EBOX milliseconds.
Page 115: 106 Because of the average size of
Page 119 and 120: 110 3.5 Takr 3.5.1 The Program (def
Page 121 and 122: 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
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158 node. The number of nodes visit
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160 3.9.3 Translation Notes In INTE
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162 (TSELECT (LAMBDA (N Q) (for N (
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164 (TIMIT (LAMBDA NIL (TIMEALL (SE
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166 Raw Time Traverse Initializatio
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168 Raw Time Traverse Implementatio
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170 3.10 Derivative 3.10.1 The Prog
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172 3.10.4 Raw Data Raw Time Deriv
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174 The benchmark should solve a pr
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176 (defun dderiv (a) (cond ((atom
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178 3.11.4 Raw Data Raw Time Dderiv
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180 I find it rather startling that
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182 3.12.2 Analysis This benchmark
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184 Raw Time Fdderiv Implementation
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186 3.13 Division by 2 3.13.1 The P
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188 3.13.4 Raw Data Raw Time Iterat
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190 Raw Time Recursive Div2 Impleme
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192 If naive users write cruddy cod
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194 l6 (cond ((< k j) (setq j (- j
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196 3.14.3 Translation Notes The IN
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198 (for J to LE1 do (* Loop thru b
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200 3.14.4 Raw Data Raw Time FFT Im
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202 This is not to say Franz’s co
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204 (defun place (i j) (let ((end (
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206 (definePiece 2 1 0 1) (definePi
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208 During the search, the first ei
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210 (CONSTANTS SIZE TYPEMAX D CLASS
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212 (START (LAMBDA NIL (for M from
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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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Performance and Evaluation of Lisp Systems - Dreamsongs

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