1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 199 200 201 202 203 204 205 206 207 208 209 210 211 212 213 214 215 216 217 218 219 220 221 222 223 224 225 226 227 228 229 230 231 232 233 234 235 236 237 238 239 240 241 242 243 244 245 246 247 248 249 250 251 252 253 254 255 256 257 258 259 260 261 262 263 264 265 266 267 268 269 270 271 272 273 274 275 276 277 278 279 280 281 282 283 284 285 286 287 288 289 290 291 292 293 294 295 296 297 298 299 300 301 302 303 304 305 306 307 308 309 310 311 312 313 314 315 316 317 318 319 320 321 322 323 324 325 326 327 328 329 330 331 332 333 334 335 336 337 338 339 340 341 342 343 344 345 346 347 348 349 350 351 352 353 354 355 356 357 358 359 360 361 362 363 364 365 366 367 368 369 370 371 372 373 374 375 376 377 378 379 380 381 382 383 384 385 386 387 388 389 390 391 392 393 394 395 396 397 398 399 400 401 402 403 404 405 406 407 408 409 410 411 412 413 414 415 416 417 418 419 420 421 422 423 424 425 426 427 428 429 430 431 432 433 434 435 436 437 438 439 440 441 442 443 444 445 446 447 448 449 450 451 452 453 454 455 456 457 458 459 460 461 462 463 464 465 466 467 468 469
|
%-----------------------------------------------------------------------------%
% Copyright (C) 2000-2001 The University of Melbourne.
% This file may only be copied under the terms of the GNU General
% Public License - see the file COPYING in the Mercury distribution.
%-----------------------------------------------------------------------------%
% File: ml_simplify_switch.m
% Main author: fjh
% This module, which is invoked by the various parts of the MLDS code generator
% that generate switches, converts MLDS switches into computed gotos
% or if-then-else chains.
% We should eventually also handle lookup switches and binary search switches
% here too.
% The choice of which exactly which simplifications will get
% performed depends on the target (e.g. whether it understands
% switches) and the --prefer-switch option.
%-----------------------------------------------------------------------------%
:- module ml_simplify_switch.
:- interface.
:- import_module mlds, ml_code_util.
:- pred ml_simplify_switch(mlds__stmt::in, mlds__context::in,
mlds__statement::out,
ml_gen_info::in, ml_gen_info::out) is det.
%-----------------------------------------------------------------------------%
:- implementation.
:- import_module ml_switch_gen, builtin_ops, type_util.
:- import_module globals, options.
:- import_module bool, int, list, map, require, std_util.
%-----------------------------------------------------------------------------%
ml_simplify_switch(Stmt0, MLDS_Context, Statement) -->
ml_gen_info_get_globals(Globals),
(
%
% Convert dense int switches into computed gotos,
% unless the target prefers switches.
%
% is this an int switch?
{ Stmt0 = switch(Type, Rval, Range, Cases, Default) },
{ is_integral_type(Type) },
% does the target want us to convert dense int
% switches into computed gotos?
{ target_supports_computed_goto(Globals) },
\+ {
target_supports_int_switch(Globals),
globals__lookup_bool_option(Globals, prefer_switch, yes)
},
% is the switch big enough?
{ list__length(Cases, NumCases) },
{ globals__lookup_int_option(Globals, dense_switch_size,
DenseSize) },
{ NumCases >= DenseSize },
% ... and dense enough?
{ globals__lookup_int_option(Globals, dense_switch_req_density,
ReqDensity) },
{ is_dense_switch(Cases, ReqDensity) }
->
{ maybe_eliminate_default(Range, Cases, Default, ReqDensity,
FirstVal, LastVal, NeedRangeCheck) },
generate_dense_switch(Cases, Default,
FirstVal, LastVal, NeedRangeCheck,
Type, Rval, MLDS_Context,
MLDS_Decls, MLDS_Statements),
{ Stmt = block(MLDS_Decls, MLDS_Statements) },
{ Statement = mlds__statement(Stmt, MLDS_Context) }
;
%
% Convert the remaining (sparse) int switches into if-then-else chains,
% unless the target prefers switches.
%
{ Stmt0 = switch(Type, Rval, _Range, Cases, Default) },
{ is_integral_type(Type) },
\+ {
target_supports_int_switch(Globals),
globals__lookup_bool_option(Globals, prefer_switch, yes)
}
->
{ Statement = ml_switch_to_if_else_chain(Cases, Default, Rval,
MLDS_Context) }
;
{ Stmt = Stmt0 },
{ Statement = mlds__statement(Stmt, MLDS_Context) }
).
:- pred is_integral_type(mlds__type::in) is semidet.
is_integral_type(mlds__native_int_type).
is_integral_type(mlds__native_char_type).
is_integral_type(mlds__mercury_type(_, int_type)).
is_integral_type(mlds__mercury_type(_, char_type)).
is_integral_type(mlds__mercury_type(_, enum_type)).
:- pred is_dense_switch(list(mlds__switch_case)::in, int::in) is semidet.
is_dense_switch(Cases, ReqDensity) :-
% Need at least two cases
NumCases = list__length(Cases),
NumCases > 2,
% The switch needs to be dense enough
find_first_and_last_case(Cases, FirstCaseVal, LastCaseVal),
CasesRange = LastCaseVal - FirstCaseVal + 1,
Density = calc_density(NumCases, CasesRange),
Density > ReqDensity.
% For switches with a default, we normally need to check that
% the variable is in range before we index into the jump table.
% However, if the range of the type is sufficiently small,
% we can make the jump table large enough to hold all
% of the values for the type.
:- pred maybe_eliminate_default(mlds__switch_range::in,
list(mlds__switch_case)::in, mlds__switch_default::in, int::in,
int::out, int::out, bool::out) is det.
maybe_eliminate_default(Range, Cases, Default, ReqDensity,
FirstVal, LastVal, NeedRangeCheck) :-
(
Default \= default_is_unreachable,
Range = range(Min, Max),
TypeRange = Max - Min + 1,
NumCases = list__length(Cases),
NoDefaultDensity = calc_density(NumCases, TypeRange),
NoDefaultDensity > ReqDensity
->
NeedRangeCheck = no,
FirstVal = Min,
LastVal = Max
;
( Default = default_is_unreachable ->
NeedRangeCheck = no
;
NeedRangeCheck = yes
),
find_first_and_last_case(Cases, FirstCaseVal, LastCaseVal),
FirstVal = FirstCaseVal,
LastVal = LastCaseVal
).
% Calculate the percentage density given the range
% and the number of cases.
:- func calc_density(int, int) = int.
calc_density(NumCases, Range) = Density :-
Density is (NumCases * 100) // Range.
%-----------------------------------------------------------------------------%
% Find the highest and lowest case values in a list of cases.
:- pred find_first_and_last_case(list(mlds__switch_case)::in,
int::out, int::out) is det.
find_first_and_last_case(Cases, Min, Max) :-
list__foldl2(find_first_and_last_case_2, Cases, 0, Min, 0, Max).
:- pred find_first_and_last_case_2(mlds__switch_case::in,
int::in, int::out, int::in, int::out) is det.
find_first_and_last_case_2(Case, Min0, Min, Max0, Max) :-
Case = CaseConds - _CaseStatement,
list__foldl2(find_first_and_last_case_3, CaseConds,
Min0, Min, Max0, Max).
:- pred find_first_and_last_case_3(mlds__case_match_cond::in,
int::in, int::out, int::in, int::out) is det.
find_first_and_last_case_3(match_value(Rval), Min0, Min, Max0, Max) :-
(
Rval = const(int_const(Val))
->
int__min(Min0, Val, Min),
int__max(Max0, Val, Max)
;
error("find_first_and_last_case_3: non-int case")
).
find_first_and_last_case_3(match_range(MinRval, MaxRval),
Min0, Min, Max0, Max) :-
(
MinRval = const(int_const(Min1)),
MaxRval = const(int_const(Max1))
->
int__min(Min0, Min1, Min),
int__max(Max0, Max1, Max)
;
error("find_first_and_last_case_3: non-int case")
).
%-----------------------------------------------------------------------------%
% Generate code for a switch using a dense jump table.
:- pred generate_dense_switch(list(mlds__switch_case)::in,
mlds__switch_default::in, int::in, int::in, bool::in,
mlds__type::in, mlds__rval::in, mlds__context::in,
mlds__defns::out, mlds__statements::out,
ml_gen_info::in, ml_gen_info::out) is det.
generate_dense_switch(Cases, Default, FirstVal, LastVal, NeedRangeCheck,
_Type, Rval, MLDS_Context, MLDS_Decls, MLDS_Statements) -->
%
% If the case values start at some number other than 0,
% then subtract that number to give us a zero-based index
%
{ FirstVal = 0 ->
Index = Rval
;
Index = binop(-, Rval, const(int_const(FirstVal)))
},
%
% Now generate the jump table
%
ml_gen_new_label(EndLabel),
{ map__init(CaseLabelsMap0) },
generate_cases(Cases, EndLabel, CaseLabelsMap0,
CaseLabelsMap, CasesDecls, CasesCode),
ml_gen_new_label(DefaultLabel),
{ CaseLabels = get_case_labels(FirstVal, LastVal,
CaseLabelsMap, DefaultLabel) },
{ DefaultLabelStatement = mlds__statement(
label(DefaultLabel),
MLDS_Context) },
(
{ Default = default_is_unreachable },
% we still need the label, in case we inserted
% references to it into (unreachable) slots in the
% jump table
{ DefaultStatements = [DefaultLabelStatement] }
;
{ Default = default_do_nothing },
{ DefaultStatements = [DefaultLabelStatement] }
;
{ Default = default_case(DefaultCase) },
{ DefaultStatements = [DefaultLabelStatement, DefaultCase] }
),
{ StartComment = mlds__statement(
atomic(comment("switch (using dense jump table)")),
MLDS_Context) },
{ DoJump = mlds__statement(
computed_goto(Index, CaseLabels),
MLDS_Context) },
{ EndLabelStatement = mlds__statement(
label(EndLabel),
MLDS_Context) },
{ EndComment = mlds__statement(
atomic(comment("End of dense switch")),
MLDS_Context) },
% We may need to check that the value of the variable lies within the
% appropriate range
(
{ NeedRangeCheck = yes }
->
{ Difference is LastVal - FirstVal },
{ InRange = binop(unsigned_le, Index,
const(int_const(Difference))) },
{ Else = yes(mlds__statement(
block([], DefaultStatements),
MLDS_Context)) },
{ SwitchBody = mlds__statement(
block([], [DoJump | CasesCode]),
MLDS_Context) },
{ DoSwitch = mlds__statement(
if_then_else(InRange, SwitchBody, Else),
MLDS_Context) },
{ MLDS_Statements = [StartComment, DoSwitch] ++
[EndLabelStatement, EndComment] }
;
{ MLDS_Statements = [StartComment, DoJump | CasesCode] ++
DefaultStatements ++
[EndLabelStatement, EndComment] }
),
{ MLDS_Decls = CasesDecls }.
:- pred generate_cases(list(mlds__switch_case)::in, mlds__label::in,
case_labels_map::in, case_labels_map::out,
mlds__defns::out, mlds__statements::out,
ml_gen_info::in, ml_gen_info::out) is det.
generate_cases([], _EndLabel, CaseLabelsMap, CaseLabelsMap, [], []) --> [].
generate_cases([Case | Cases], EndLabel, CaseLabelsMap0,
CaseLabelsMap, MLDS_Decls, MLDS_Statements) -->
generate_case(Case, EndLabel, CaseLabelsMap0, CaseLabelsMap1,
CaseDecls, CaseStatements),
generate_cases(Cases, EndLabel,
CaseLabelsMap1, CaseLabelsMap,
MLDS_Decls1, MLDS_Statements1),
{ MLDS_Decls = CaseDecls ++ MLDS_Decls1 },
{ MLDS_Statements = CaseStatements ++ MLDS_Statements1 }.
:- pred generate_case(mlds__switch_case::in, mlds__label::in,
case_labels_map::in, case_labels_map::out,
mlds__defns::out, mlds__statements::out,
ml_gen_info::in, ml_gen_info::out) is det.
% This converts an MLDS switch case into code for a dense switch case,
% by adding a label at the front and a `goto <EndLabel>' at the end.
% It also inserts the label for this case into the CaseLabelsMap.
generate_case(Case, EndLabel, CaseLabelsMap0, CaseLabelsMap,
MLDS_Decls, MLDS_Statements) -->
{ Case = MatchCondition - CaseStatement },
ml_gen_new_label(ThisLabel),
{ insert_cases_into_map(MatchCondition, ThisLabel,
CaseLabelsMap0, CaseLabelsMap) },
{ CaseStatement = mlds__statement(_, MLDS_Context) },
{ LabelComment = mlds__statement(
atomic(comment("case of dense switch")),
MLDS_Context) },
{ LabelCode = mlds__statement(
label(ThisLabel),
MLDS_Context) },
{ JumpComment = mlds__statement(
atomic(comment("branch to end of dense switch")),
MLDS_Context) },
{ JumpCode = mlds__statement(
goto(EndLabel),
MLDS_Context) },
{ MLDS_Decls = [] },
{ MLDS_Statements = [LabelComment, LabelCode, CaseStatement,
JumpComment, JumpCode] }.
%-----------------------------------------------------------------------------%
%
% We build up a map which records which label should be used for
% each case value.
%
:- type case_labels_map == map(int, mlds__label).
:- pred insert_cases_into_map(mlds__case_match_conds::in, mlds__label::in,
case_labels_map::in, case_labels_map::out) is det.
insert_cases_into_map([], _ThisLabel, CaseLabelsMap, CaseLabelsMap).
insert_cases_into_map([Cond|Conds], ThisLabel, CaseLabelsMap0, CaseLabelsMap) :-
insert_case_into_map(Cond, ThisLabel, CaseLabelsMap0, CaseLabelsMap1),
insert_cases_into_map(Conds, ThisLabel, CaseLabelsMap1, CaseLabelsMap).
:- pred insert_case_into_map(mlds__case_match_cond::in, mlds__label::in,
case_labels_map::in, case_labels_map::out) is det.
insert_case_into_map(match_value(Rval), ThisLabel,
CaseLabelsMap0, CaseLabelsMap) :-
( Rval = const(int_const(Val)) ->
map__det_insert(CaseLabelsMap0, Val, ThisLabel, CaseLabelsMap)
;
error("insert_case_into_map: non-int case")
).
insert_case_into_map(match_range(MinRval, MaxRval), ThisLabel,
CaseLabelsMap0, CaseLabelsMap) :-
(
MinRval = const(int_const(Min)),
MaxRval = const(int_const(Max))
->
insert_range_into_map(Min, Max, ThisLabel,
CaseLabelsMap0, CaseLabelsMap)
;
error("insert_case_into_map: non-int case")
).
:- pred insert_range_into_map(int::in, int::in, mlds__label::in,
case_labels_map::in, case_labels_map::out) is det.
insert_range_into_map(Min, Max, ThisLabel, CaseLabelsMap0, CaseLabelsMap) :-
( Min > Max ->
CaseLabelsMap = CaseLabelsMap0
;
map__det_insert(CaseLabelsMap0, Min, ThisLabel,
CaseLabelsMap1),
insert_range_into_map(Min + 1, Max, ThisLabel,
CaseLabelsMap1, CaseLabelsMap)
).
%-----------------------------------------------------------------------------%
% Given the starting and ending case values, the mapping from case values
% to labels, and the default label to use for case values which aren't in
% the map, this function returns the list of labels to use for the case
% values.
:- func get_case_labels(int, int, map(int, mlds__label), mlds__label) =
list(mlds__label).
get_case_labels(ThisVal, LastVal, CaseLabelsMap, DefaultLabel) = CaseLabels :-
( ThisVal > LastVal ->
CaseLabels = []
;
( map__search(CaseLabelsMap, ThisVal, CaseLabel0) ->
CaseLabel = CaseLabel0
;
CaseLabel = DefaultLabel
),
CaseLabels1 = get_case_labels(ThisVal + 1, LastVal,
CaseLabelsMap, DefaultLabel),
CaseLabels = [CaseLabel | CaseLabels1]
).
%-----------------------------------------------------------------------------%
% Convert an int switch to a chain of if-then-elses
% that test each case in turn.
%
:- func ml_switch_to_if_else_chain(mlds__switch_cases, mlds__switch_default,
mlds__rval, mlds__context) = mlds__statement.
ml_switch_to_if_else_chain([], Default, _Rval, MLDS_Context) =
MLDS_Statement :-
(
Default = default_do_nothing,
MLDS_Statement = mlds__statement(block([],[]), MLDS_Context)
;
Default = default_is_unreachable,
MLDS_Statement = mlds__statement(block([],[]), MLDS_Context)
;
Default = default_case(MLDS_Statement)
).
ml_switch_to_if_else_chain([Case | Cases], Default, SwitchRval, MLDS_Context) =
MLDS_Statement :-
Case = MatchConditions - CaseStatement,
(
Cases = [], Default = default_is_unreachable
->
MLDS_Statement = CaseStatement
;
CaseMatchedRval = ml_gen_case_match_conds(MatchConditions,
SwitchRval),
RestStatement = ml_switch_to_if_else_chain(Cases, Default,
SwitchRval, MLDS_Context),
IfStmt = if_then_else(CaseMatchedRval,
CaseStatement, yes(RestStatement)),
MLDS_Statement = mlds__statement(IfStmt, MLDS_Context)
).
% Generate an rval which will be true iff any of the specified
% list of case conditions matches the specified rval
% (which must have integral type).
:- func ml_gen_case_match_conds(mlds__case_match_conds, rval) = rval.
ml_gen_case_match_conds([], _) = const(false).
ml_gen_case_match_conds([Cond], SwitchRval) =
ml_gen_case_match_cond(Cond, SwitchRval).
ml_gen_case_match_conds([Cond1, Cond2 | Conds], SwitchRval) =
binop(or,
ml_gen_case_match_cond(Cond1, SwitchRval),
ml_gen_case_match_conds([Cond2 | Conds], SwitchRval)).
% Generate an rval which will be true iff the specified
% case condition matches the specified rval
% (which must have integral type).
:- func ml_gen_case_match_cond(mlds__case_match_cond, rval) = rval.
ml_gen_case_match_cond(match_value(CaseRval), SwitchRval) =
binop(eq, CaseRval, SwitchRval).
ml_gen_case_match_cond(match_range(MinRval, MaxRval), SwitchRval) =
binop(and, binop(>=, SwitchRval, MinRval),
binop(<=, SwitchRval, MaxRval)).
%-----------------------------------------------------------------------------%
|