Performance and Evaluation of Lisp Systems - Dreamsongs

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§ 3.9 Traverse 157 100 nodes are formed into a circular list; two circular lists are kept—a circular list of used nodes (used) and a circular list of unused nodes (unused). The program ADD adds items to a circular list, and REMOVE removes the n th item from a circular list and travels around the list more than once if necessary. In CREATE-STRUCTURE, there is a loop that builds the random graph. This is done by selecting two random numbers, n and m. Let and n (mod length(unused)) x = unused m (mod length(used)) y = used x is removed from unused and it is made a son of y. The loop continues until unused is empty. The graph is directed, and a root is found. All nodes are in the graph, which can be proved by induction. A node is placed in used at the start of the loop. This node has neither sons nor parents; it is a single connected component. At any stage of the iteration, if unused is empty, we are done and there is one connected component in used. If unused is not empty, then a node in it is connected to the single connected component in used, and the resulting new graph in used has one connected component. The induction is complete. Because directed arcs are added to existing nodes in used, the graph has a single root, and a procedure is used to find that root by tracing back along parent arcs. This is not necessary because it is easy to prove that the root must be the node that was first placed in used. However, this step adds a little to the runtime of the benchmark. At this stage, the remainder of the benchmark is to mark the graph, starting at the root. There is a process that traverses the graph. At any node it does one of two things: If that node has already been marked, then the process is done with that node. If the node has not been marked, the process ‘flips’ the sense of each entry (sets the contents of the entry to NOT of the entry—the entries flip between NIL and T), and for each node in the sons of that node, it traverses that
158 node. The number of nodes visited by the traverser is counted by using a special variable. The marking is done 250 times to the graph. The interesting aspect of this benchmark is that it uses DEFSTRUCT in Common Lisp, so that it tests the quality of the abstract data structuring facilities of the Lisp system, as much as anything. Meter for Remove Cdr’s 1093372 =’s 553818 1−’s 529455 Car’s 66207 Eq’s 17281 Rplacd’s 12231 Rplaca’s 100 Total 2272464 Meter for Create-Structure Setf’s 24462 RANDOM 24462 ADD 12232 REMOVE 12232 Null’s 12232 Car’s 12232 SELECT 12232 PARENTS 12231 SONS 12231 Cons’s 12331 1-’s 100 =’s 100 Rplacd’s 1 FIND-ROOT 1 Total 147079 Meter for Snb 1+’s 100 Total 100 Meter for Select =’s 541492 1−’s 529260 Cdr’s 529260 Car’s 24464 Total 1624476 Meter for Add Car’s 36693 Null’s 24463 Rplacd’s 12232 Rplaca’s 12231 Conses 12231 Cdr’s 12231 Total 110081 Meter for Travers MARK 3083000 Null’s 3082750 Cdr’s 3057750 Eq’s 3058000 TRAVERS 3057750 Car’s 3057750 Setf’s 175000 1+’s 25000 ENTRY1 25000 ENTRY2 25000 ENTRY3 25000 ENTRY4 25000 ENTRY5 25000 ENTRY6 25000 Total 18747000
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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.
Page 115 and 116: 106 Because of the average size of
Page 117 and 118: 108 Raw Time Takl Implementation CP
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: 156 (defmacro init-traverse() (prog
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 and 174: 164 (TIMIT (LAMBDA NIL (TIMEALL (SE
Page 175 and 176: 166 Raw Time Traverse Initializatio
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
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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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