%% -*- erlang-indent-level: 2 -*-
%%
%% %CopyrightBegin%
%%
%% Copyright Ericsson AB 2001-2016. All Rights Reserved.
%%
%% Licensed under the Apache License, Version 2.0 (the "License");
%% you may not use this file except in compliance with the License.
%% You may obtain a copy of the License at
%%
%% http://www.apache.org/licenses/LICENSE-2.0
%%
%% Unless required by applicable law or agreed to in writing, software
%% distributed under the License is distributed on an "AS IS" BASIS,
%% WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
%% See the License for the specific language governing permissions and
%% limitations under the License.
%%
%% %CopyrightEnd%
%%
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
%% Copyright (c) 2001 by Erik Johansson. All Rights Reserved
%% ====================================================================
%% Filename : hipe_rtl_mk_switch.erl
%% Module : hipe_rtl_mk_switch
%% Purpose : Implements switching on Erlang values.
%% Notes : Only fixnums are supported well,
%% atoms work with table search,
%% the inline search of atoms might have some bugs.
%% Should be extended to handle bignums and floats.
%%
%% History : * 2001-02-28 Erik Johansson ([email protected]):
%% Created.
%% * 2001-04-01 Erik Trulsson ([email protected]):
%% Stefan Lindström ([email protected]):
%% Added clustering and inlined binary search trees.
%% * 2001-07-30 EJ ([email protected]):
%% Fixed some bugs and started cleanup.
%% ====================================================================
%% Exports :
%% gen_switch_val(I, VarMap, ConstTab, Options)
%% gen_switch_tuple(I, Map, ConstTab, Options)
%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-module(hipe_rtl_mk_switch).
-export([gen_switch_val/4, gen_switch_tuple/4]).
%%-------------------------------------------------------------------------
-include("../main/hipe.hrl").
%%-------------------------------------------------------------------------
-define(MINFORJUMPTABLE,9).
% Minimum number of integers needed to use something else than an inline search.
-define(MINFORINTSEARCHTREE,65). % Must be at least 3
% Minimum number of integer elements needed to use a non-inline binary search.
-define(MININLINEATOMSEARCH,8).
% Minimum number of atoms needed to use an inline binary search instead
% of a fast linear search.
-define(MINFORATOMSEARCHTREE,20). % Must be at least 3
% Minimum number of atoms needed to use a non-inline binary search instead
% of a linear search.
-define(MAXINLINEATOMSEARCH,64). % Must be at least 3
% The cutoff point between inlined and non-inlined binary search for atoms
-define(WORDSIZE, hipe_rtl_arch:word_size()).
-define(MINDENSITY, 0.5).
% Minimum density required to use a jumptable instead of a binary search.
%% The reason why MINFORINTSEARCHTREE and MINFORATOMSEARCHTREE must be
%% at least 3 is that the function tab/5 will enter an infinite loop
%% and hang when faced with a switch of size 1 or 2.
%% Options used by this module:
%%
%% [no_]use_indexing
%% Determines if any indexing be should be done at all. Turned on
%% by default at optimization level o2 and higher.
%%
%% [no_]use_clusters
%% Controls whether we attempt to divide sparse integer switches
%% into smaller dense clusters for which jumptables are practical.
%% Turned off by default since it can increase compilation time
%% considerably and most programs will gain little benefit from it.
%%
%% [no_]use_inline_atom_search
%% Controls whether we use an inline binary search for small number
%% of atoms. Turned off by default since this is currently only
%% supported on SPARC (and not on x86) and probably needs a bit
%% more testing before it can be turned on by default.
gen_switch_val(I, VarMap, ConstTab, Options) ->
case proplists:get_bool(use_indexing, Options) of
false -> gen_slow_switch_val(I, VarMap, ConstTab, Options);
true -> gen_fast_switch_val(I, VarMap, ConstTab, Options)
end.
gen_fast_switch_val(I, VarMap, ConstTab, Options) ->
{Arg, VarMap0} =
hipe_rtl_varmap:icode_var2rtl_var(hipe_icode:switch_val_term(I), VarMap),
IcodeFail = hipe_icode:switch_val_fail_label(I),
{Fail, VarMap1} = hipe_rtl_varmap:icode_label2rtl_label(IcodeFail, VarMap0),
%% Important that the list of cases is sorted when handling integers.
UnsortedCases = hipe_icode:switch_val_cases(I),
Cases = lists:sort(UnsortedCases),
check_duplicates(Cases),
%% This check is currently not really necessary. The checking
%% happens at an earlier phase of the compilation.
{Types, InitCode} = split_types(Cases, Arg),
handle_types(Types, InitCode, VarMap1, ConstTab, Arg, {I, Fail, Options}).
handle_types([{Type,Lbl,Cases}|Types], Code, VarMap, ConstTab, Arg, Info) ->
{Code1,VarMap1,ConstTab1} = gen_fast_switch_on(Type, Cases,
VarMap,
ConstTab, Arg, Info),
handle_types(Types, [Code,Lbl,Code1], VarMap1, ConstTab1, Arg, Info);
handle_types([], Code, VarMap, ConstTab, _, _) ->
{Code, VarMap, ConstTab}.
gen_fast_switch_on(integer, Cases, VarMap, ConstTab, Arg, {I, Fail, Options}) ->
{First,_} = hd(Cases),
Min = hipe_icode:const_value(First),
if length(Cases) < ?MINFORJUMPTABLE ->
gen_small_switch_val(Arg,Cases,Fail,VarMap,ConstTab,Options);
true ->
case proplists:get_bool(use_clusters, Options) of
false ->
M = list_to_tuple(Cases),
D = density(M, 1, tuple_size(M)),
if
D >= ?MINDENSITY ->
gen_jump_table(Arg,Fail,hipe_icode:switch_val_fail_label(I),VarMap,ConstTab,Cases,Min);
true ->
gen_search_switch_val(Arg, Cases, Fail, VarMap, ConstTab, Options)
end;
true ->
MC = minclusters(Cases),
Cl = cluster_split(Cases,MC),
CM = cluster_merge(Cl),
find_cluster(CM,VarMap,ConstTab,Options,Arg,Fail,hipe_icode:switch_val_fail_label(I))
end
end;
gen_fast_switch_on(atom, Cases, VarMap, ConstTab, Arg, {_I, Fail, Options}) ->
case proplists:get_bool(use_inline_atom_search, Options) of
true ->
if
length(Cases) < ?MININLINEATOMSEARCH ->
gen_linear_switch_val(Arg, Cases, Fail, VarMap, ConstTab, Options);
length(Cases) > ?MAXINLINEATOMSEARCH ->
gen_search_switch_val(Arg, Cases, Fail, VarMap, ConstTab, Options);
true ->
gen_atom_switch_val(Arg,Cases,Fail,VarMap,ConstTab,Options)
end;
false ->
if length(Cases) < ?MINFORATOMSEARCHTREE ->
gen_linear_switch_val(Arg, Cases, Fail, VarMap, ConstTab, Options);
true ->
gen_search_switch_val(Arg, Cases, Fail, VarMap, ConstTab, Options)
end
end;
gen_fast_switch_on(_, _, VarMap, ConstTab, _, {I,_Fail,Options}) ->
%% We can only handle smart indexing of integers and atoms
%% TODO: Consider bignum
gen_slow_switch_val(I, VarMap, ConstTab, Options).
%% Split different types into separate switches.
split_types([Case|Cases], Arg) ->
Type1 = casetype(Case),
Types = split(Cases,Type1,[Case],[]),
switch_on_types(Types,[], [], Arg);
split_types([],_) ->
%% Cant happen.
?EXIT({empty_caselist}).
switch_on_types([{Type,Cases}], AccCode, AccCases, _Arg) ->
Lbl = hipe_rtl:mk_new_label(),
I = hipe_rtl:mk_goto(hipe_rtl:label_name(Lbl)),
{[{Type,Lbl,lists:reverse(Cases)} | AccCases], lists:reverse([I|AccCode])};
switch_on_types([{other,Cases} | Rest], AccCode, AccCases, Arg) ->
%% Make sure the general case is handled last.
switch_on_types(Rest ++ [{other,Cases}], AccCode, AccCases, Arg);
switch_on_types([{Type,Cases} | Rest], AccCode, AccCases, Arg) ->
TLab = hipe_rtl:mk_new_label(),
FLab = hipe_rtl:mk_new_label(),
TestCode =
case Type of
integer ->
hipe_tagscheme:test_fixnum(Arg, hipe_rtl:label_name(TLab),
hipe_rtl:label_name(FLab), 0.5);
atom ->
hipe_tagscheme:test_atom(Arg, hipe_rtl:label_name(TLab),
hipe_rtl:label_name(FLab), 0.5);
bignum ->
hipe_tagscheme:test_bignum(Arg, hipe_rtl:label_name(TLab),
hipe_rtl:label_name(FLab), 0.5);
_ -> ?EXIT({ooops, type_not_handled, Type})
end,
switch_on_types(Rest, [[TestCode,FLab] | AccCode],
[{Type,TLab,lists:reverse(Cases)} | AccCases], Arg).
split([Case|Cases], Type, Current, Rest) ->
case casetype(Case) of
Type ->
split(Cases, Type, [Case|Current],Rest);
Other ->
split(Cases, Other, [Case], [{Type,Current}|Rest])
end;
split([], Type, Current, Rest) ->
[{Type, Current} | Rest].
%% Determine what type an entry in the caselist has
casetype({Const,_}) ->
casetype(hipe_icode:const_value(Const));
casetype(A) ->
if
is_integer(A) ->
case hipe_tagscheme:is_fixnum(A) of
true -> integer;
false -> bignum
end;
is_float(A) -> float;
is_atom(A) -> atom;
true -> other
end.
%% check that no duplicate values occur in the case list and also
%% check that all case values have the same type.
check_duplicates([]) -> true;
check_duplicates([_]) -> true;
check_duplicates([{Const1,_},{Const2,L2}|T]) ->
C1 = hipe_icode:const_value(Const1),
C2 = hipe_icode:const_value(Const2),
%% T1 = casetype(C1),
%% T2 = casetype(C2),
if C1 =/= C2 -> %% , T1 =:= T2 ->
check_duplicates([{Const2,L2}|T]);
true ->
?EXIT({bad_values_in_switchval,C1})
end.
%%
%% Determine the optimal way to divide Cases into clusters such that each
%% cluster is dense.
%%
%% See:
%% Producing Good Code for the Case Statement, Robert L. Bernstein
%% Software - Practice and Experience vol 15, 1985, no 10, pp 1021--1024
%% And
%% Correction to "Producing Good Code for the Case Statement"
%% Sampath Kannan and Todd A. Proebsting,
%% Software - Practice and Experience vol 24, 1994, no 2, p 233
%%
%% (The latter is where the algorithm comes from.)
%% This function will return a tuple with the first element being 0
%% The rest of the elements being integers. A value of M at index N
%% (where the first element is considered to have index 0) means that
%% the first N cases can be divided into M (but no fewer) clusters where
%% each cluster is dense.
minclusters(Cases) when is_list(Cases) ->
minclusters(list_to_tuple(Cases));
minclusters(Cases) when is_tuple(Cases) ->
N = tuple_size(Cases),
MinClusters = list_to_tuple([0|n_list(N,inf)]),
i_loop(1,N,MinClusters,Cases).
%% Create a list with N elements initialized to Init
n_list(0,_) -> [];
n_list(N,Init) -> [Init | n_list(N-1,Init)].
%% Do the dirty work of minclusters
i_loop(I,N,MinClusters,_Cases) when I > N ->
MinClusters;
i_loop(I,N,MinClusters,Cases) when I =< N ->
M = j_loop(0, I-1, MinClusters, Cases),
i_loop(I+1, N, M, Cases).
%% More dirty work
j_loop(J,I1,MinClusters,_Cases) when J > I1 ->
MinClusters;
j_loop(J,I1,MinClusters,Cases) when J =< I1 ->
D = density(Cases,J+1,I1+1),
A0 = element(J+1,MinClusters),
A = if
is_number(A0) ->
A0+1;
true ->
A0
end,
B = element(I1+2,MinClusters),
M = if
D >= ?MINDENSITY, A<B ->
setelement(I1+2,MinClusters,A);
true ->
MinClusters
end,
j_loop(J+1,I1,M,Cases).
%% Determine the density of a (subset of a) case list
%% A is a tuple with the cases in order from smallest to largest
%% I is the index of the first element and J of the last
density(A,I,J) ->
{AI,_} = element(I,A),
{AJ,_} = element(J,A),
(J-I+1)/(hipe_icode:const_value(AJ)-hipe_icode:const_value(AI)+1).
%% Split a case list into dense clusters
%% Returns a list of lists of cases.
%%
%% Cases is the case list and Clust is a list describing the optimal
%% clustering as returned by minclusters
%%
%% If the value in the last place in minclusters is M then we can
%% split the case list into M clusters. We then search for the last
%% (== right-most) occurance of the value M-1 in minclusters. That
%% indicates the largest number of cases that can be split into M-1
%% clusters. This means that the cases in between constitute one
%% cluster. Then we recurse on the remainder of the cases.
%%
%% The various calls to lists:reverse are just to ensure that the
%% cases remain in the correct, sorted order.
cluster_split(Cases, Clust) ->
A = tl(tuple_to_list(Clust)),
Max = element(tuple_size(Clust), Clust),
L1 = lists:reverse(Cases),
L2 = lists:reverse(A),
cluster_split(Max, [], [], L1, L2).
cluster_split(0, [], Res, Cases, _Clust) ->
L = lists:reverse(Cases),
{H,_} = hd(L),
{T,_} = hd(Cases),
[{dense,hipe_icode:const_value(H),hipe_icode:const_value(T),L}|Res];
cluster_split(N, [], Res, Cases, [N|_] = Clust) ->
cluster_split(N-1, [], Res, Cases, Clust);
cluster_split(N,Sofar,Res,Cases,[N|Clust]) ->
{H,_} = hd(Sofar),
{T,_} = lists:last(Sofar),
cluster_split(N-1,[],[{dense,hipe_icode:const_value(H),hipe_icode:const_value(T),Sofar}|Res],Cases,[N|Clust]);
cluster_split(N,Sofar,Res,[C|Cases],[_|Clust]) ->
cluster_split(N,[C|Sofar],Res,Cases,Clust).
%%
%% Merge adjacent small clusters into larger sparse clusters
%%
cluster_merge([C]) -> [C];
cluster_merge([{dense,Min,Max,C}|T]) when length(C) >= ?MINFORJUMPTABLE ->
C2 = cluster_merge(T),
[{dense,Min,Max,C}|C2];
cluster_merge([{sparse,Min,_,C},{sparse,_,Max,D}|T]) ->
R = {sparse,Min,Max,C ++ D},
cluster_merge([R|T]);
cluster_merge([{sparse,Min,_,C},{dense,_,Max,D}|T]) when length(D) < ?MINFORJUMPTABLE ->
R = {sparse,Min,Max,C ++ D},
cluster_merge([R|T]);
cluster_merge([{dense,Min,_,C},{dense,_,Max,D}|T]) when length(C) < ?MINFORJUMPTABLE, length(D) < ?MINFORJUMPTABLE ->
R = {sparse,Min,Max,C ++ D},
cluster_merge([R|T]);
cluster_merge([{dense,Min,_,D},{sparse,_,Max,C}|T]) when length(D) < ?MINFORJUMPTABLE ->
R = {sparse,Min,Max,C ++ D},
cluster_merge([R|T]);
cluster_merge([A,{dense,Min,Max,C}|T]) when length(C) >= ?MINFORJUMPTABLE ->
R = cluster_merge([{dense,Min,Max,C}|T]),
[A|R].
%% Generate code to search for the correct cluster
find_cluster([{sparse,_Min,_Max,C}],VarMap,ConstTab,Options,Arg,Fail,_IcodeFail) ->
case length(C) < ?MINFORINTSEARCHTREE of
true ->
gen_small_switch_val(Arg,C,Fail,VarMap,ConstTab,Options);
_ ->
gen_search_switch_val(Arg,C,Fail,VarMap,ConstTab,Options)
end;
find_cluster([{dense,Min,_Max,C}],VarMap,ConstTab,Options,Arg,Fail,IcodeFail) ->
case length(C) < ?MINFORJUMPTABLE of
true ->
gen_small_switch_val(Arg,C,Fail,VarMap,ConstTab,Options);
_ ->
gen_jump_table(Arg,Fail,IcodeFail,VarMap,ConstTab,C,Min)
end;
find_cluster([{Density,Min,Max,C}|T],VarMap,ConstTab,Options,Arg,Fail,IcodeFail) ->
ClustLab = hipe_rtl:mk_new_label(),
NextLab = hipe_rtl:mk_new_label(),
{ClustCode,V1,C1} = find_cluster([{Density,Min,Max,C}],VarMap,ConstTab,Options,Arg,Fail,IcodeFail),
{Rest,V2,C2} = find_cluster(T,V1,C1,Options,Arg,Fail,IcodeFail),
{[
hipe_rtl:mk_branch(Arg, gt, hipe_rtl:mk_imm(hipe_tagscheme:mk_fixnum(Max)),
hipe_rtl:label_name(NextLab),
hipe_rtl:label_name(ClustLab), 0.50),
ClustLab
] ++
ClustCode ++
[NextLab] ++
Rest,
V2,C2}.
%% Generate efficient code for a linear search through the case list.
%% Only works for atoms and integer.
gen_linear_switch_val(Arg,Cases,Fail,VarMap,ConstTab,_Options) ->
{Values,_Labels} = split_cases(Cases),
{LabMap,VarMap1} = lbls_from_cases(Cases,VarMap),
Code = fast_linear_search(Arg,Values,LabMap,Fail),
{Code,VarMap1,ConstTab}.
fast_linear_search(_Arg,[],[],Fail) ->
[hipe_rtl:mk_goto(hipe_rtl:label_name(Fail))];
fast_linear_search(Arg,[Case|Cases],[Label|Labels],Fail) ->
Reg = hipe_rtl:mk_new_reg_gcsafe(),
NextLab = hipe_rtl:mk_new_label(),
C2 = fast_linear_search(Arg,Cases,Labels,Fail),
C1 =
if
is_integer(Case) ->
TVal = hipe_tagscheme:mk_fixnum(Case),
[
hipe_rtl:mk_move(Reg,hipe_rtl:mk_imm(TVal)),
hipe_rtl:mk_branch(Arg,eq,Reg,
Label,
hipe_rtl:label_name(NextLab), 0.5),
NextLab
];
is_atom(Case) ->
[
hipe_rtl:mk_load_atom(Reg,Case),
hipe_rtl:mk_branch(Arg,eq,Reg,
Label,
hipe_rtl:label_name(NextLab), 0.5),
NextLab
];
true -> % This should never happen !
?EXIT({internal_error_in_switch_val,Case})
end,
[C1,C2].
%% Generate code to search through a small cluster of integers using
%% binary search
gen_small_switch_val(Arg,Cases,Fail,VarMap,ConstTab,_Options) ->
{Values,_Labels} = split_cases(Cases),
{LabMap,VarMap1} = lbls_from_cases(Cases,VarMap),
Keys = [hipe_tagscheme:mk_fixnum(X) % Add tags to the values
|| X <- Values],
Code = inline_search(Keys, LabMap, Arg, Fail),
{Code, VarMap1, ConstTab}.
%% Generate code to search through a small cluster of atoms
gen_atom_switch_val(Arg,Cases,Fail,VarMap,ConstTab,_Options) ->
{Values, _Labels} = split_cases(Cases),
{LabMap,VarMap1} = lbls_from_cases(Cases,VarMap),
LMap = [{label,L} || L <- LabMap],
{NewConstTab,Id} = hipe_consttab:insert_sorted_block(ConstTab, Values),
{NewConstTab2,LabId} =
hipe_consttab:insert_sorted_block(NewConstTab, word, LMap, Values),
Code = inline_atom_search(0, length(Cases)-1, Id, LabId, Arg, Fail, LabMap),
{Code, VarMap1, NewConstTab2}.
%% calculate the middle position of a list (+ 1 because of 1-indexing of lists)
get_middle(List) ->
N = length(List),
N div 2 + 1.
%% get element [N1, N2] from a list
get_cases(_, 0, 0) ->
[];
get_cases([H|T], 0, N) ->
[H | get_cases(T, 0, N - 1)];
get_cases([_|T], N1, N2) ->
get_cases(T, N1 - 1, N2 - 1).
%% inline_search/4 creates RTL code for a inlined binary search.
%% It requires two sorted tables - one with the keys to search
%% through and one with the corresponding labels to jump to.
%%
%% Input:
%% KeyList - A list of keys to search through.
%% LableList - A list of labels to jump to.
%% KeyReg - A register containing the key to search for.
%% Default - A label to jump to if the key is not found.
%%
inline_search([], _LabelList, _KeyReg, _Default) -> [];
inline_search(KeyList, LabelList, KeyReg, Default) ->
%% Create some registers and labels that we need.
Reg = hipe_rtl:mk_new_reg_gcsafe(),
Lab1 = hipe_rtl:mk_new_label(),
Lab2 = hipe_rtl:mk_new_label(),
Lab3 = hipe_rtl:mk_new_label(),
Length = length(KeyList),
if
Length >= 3 ->
%% Get middle element and keys/labels before that and after
Middle_pos = get_middle(KeyList),
Middle_key = lists:nth(Middle_pos, KeyList),
Keys_beginning = get_cases(KeyList, 0, Middle_pos - 1),
Labels_beginning = get_cases(LabelList, 0, Middle_pos - 1),
Keys_ending = get_cases(KeyList, Middle_pos, Length),
Labels_ending = get_cases(LabelList, Middle_pos, Length),
%% Create the code.
%% Get the label and build it up properly
Middle_label = lists:nth(Middle_pos, LabelList),
A = [hipe_rtl:mk_move(Reg, hipe_rtl:mk_imm(Middle_key)),
hipe_rtl:mk_branch(KeyReg, lt, Reg,
hipe_rtl:label_name(Lab2),
hipe_rtl:label_name(Lab1), 0.5),
Lab1,
hipe_rtl:mk_branch(KeyReg, gt, Reg,
hipe_rtl:label_name(Lab3),
Middle_label , 0.5),
Lab2],
%% build search tree for keys less than the middle element
B = inline_search(Keys_beginning, Labels_beginning, KeyReg, Default),
%% ...and for keys bigger than the middle element
D = inline_search(Keys_ending, Labels_ending, KeyReg, Default),
%% append the code and return it
A ++ B ++ [Lab3] ++ D;
Length =:= 2 ->
%% get the first and second elements and theirs labels
Key_first = hd(KeyList),
First_label = hd(LabelList),
%% Key_second = hipe_tagscheme:mk_fixnum(lists:nth(2, KeyList)),
Key_second = lists:nth(2, KeyList),
Second_label = lists:nth(2, LabelList),
NewLab = hipe_rtl:mk_new_label(),
%% compare them
A = [hipe_rtl:mk_move(Reg,hipe_rtl:mk_imm(Key_first)),
hipe_rtl:mk_branch(KeyReg, eq, Reg,
First_label,
hipe_rtl:label_name(NewLab) , 0.5),
NewLab],
B = [hipe_rtl:mk_move(Reg,hipe_rtl:mk_imm(Key_second)),
hipe_rtl:mk_branch(KeyReg, eq, Reg,
Second_label,
hipe_rtl:label_name(Default) , 0.5)],
A ++ B;
Length =:= 1 ->
Key = hd(KeyList),
Label = hd(LabelList),
[hipe_rtl:mk_move(Reg,hipe_rtl:mk_imm(Key)),
hipe_rtl:mk_branch(KeyReg, eq, Reg,
Label,
hipe_rtl:label_name(Default) , 0.5)]
end.
inline_atom_search(Start, End, Block, LBlock, KeyReg, Default, Labels) ->
Reg = hipe_rtl:mk_new_reg_gcsafe(),
Length = (End - Start) + 1,
if
Length >= 3 ->
Lab1 = hipe_rtl:mk_new_label(),
Lab2 = hipe_rtl:mk_new_label(),
Lab3 = hipe_rtl:mk_new_label(),
Lab4 = hipe_rtl:mk_new_label(),
Mid = ((End-Start) div 2)+Start,
End1 = Mid-1,
Start1 = Mid+1,
A = [
hipe_rtl:mk_load_word_index(Reg,Block,Mid),
hipe_rtl:mk_branch(KeyReg, lt, Reg,
hipe_rtl:label_name(Lab2),
hipe_rtl:label_name(Lab1), 0.5),
Lab1,
hipe_rtl:mk_branch(KeyReg, gt, Reg,
hipe_rtl:label_name(Lab3),
hipe_rtl:label_name(Lab4), 0.5),
Lab4,
hipe_rtl:mk_goto_index(LBlock, Mid, Labels),
Lab2
],
B = [inline_atom_search(Start,End1,Block,LBlock,KeyReg,Default,Labels)],
C = [inline_atom_search(Start1,End,Block,LBlock,KeyReg,Default,Labels)],
A ++ B ++ [Lab3] ++ C;
Length =:= 2 ->
L1 = hipe_rtl:mk_new_label(),
L2 = hipe_rtl:mk_new_label(),
L3 = hipe_rtl:mk_new_label(),
[
hipe_rtl:mk_load_word_index(Reg,Block,Start),
hipe_rtl:mk_branch(KeyReg,eq,Reg,
hipe_rtl:label_name(L1),
hipe_rtl:label_name(L2), 0.5),
L1,
hipe_rtl:mk_goto_index(LBlock,Start,Labels),
L2,
hipe_rtl:mk_load_word_index(Reg,Block,End),
hipe_rtl:mk_branch(KeyReg,eq,Reg,
hipe_rtl:label_name(L3),
hipe_rtl:label_name(Default), 0.5),
L3,
hipe_rtl:mk_goto_index(LBlock, End, Labels)
];
Length =:= 1 ->
NewLab = hipe_rtl:mk_new_label(),
[
hipe_rtl:mk_load_word_index(Reg,Block,Start),
hipe_rtl:mk_branch(KeyReg, eq, Reg,
hipe_rtl:label_name(NewLab),
hipe_rtl:label_name(Default), 0.9),
NewLab,
hipe_rtl:mk_goto_index(LBlock, Start, Labels)
]
end.
%% Create a jumptable
gen_jump_table(Arg,Fail,IcodeFail,VarMap,ConstTab,Cases,Min) ->
%% Map is a rtl mapping of Dense
{Max,DenseTbl} = dense_interval(Cases,Min,IcodeFail),
{Map,VarMap2} = lbls_from_cases(DenseTbl,VarMap),
%% Make some labels and registers that we need.
BelowLab = hipe_rtl:mk_new_label(),
UntaggedR = hipe_rtl:mk_new_reg_gcsafe(),
StartR = hipe_rtl:mk_new_reg_gcsafe(),
%% Generate the code to do the switch...
{[
%% Untag the index.
hipe_tagscheme:untag_fixnum(UntaggedR, Arg)|
%% Check that the index is within Min and Max.
case Min of
0 -> %% First element is 0 this is simple.
[hipe_rtl:mk_branch(UntaggedR, gtu, hipe_rtl:mk_imm(Max),
hipe_rtl:label_name(Fail),
hipe_rtl:label_name(BelowLab), 0.01),
BelowLab,
%% StartR contains the index into the jumptable
hipe_rtl:mk_switch(UntaggedR, Map)];
_ -> %% First element is not 0
[hipe_rtl:mk_alu(StartR, UntaggedR, sub,
hipe_rtl:mk_imm(Min)),
hipe_rtl:mk_branch(StartR, gtu, hipe_rtl:mk_imm(Max-Min),
hipe_rtl:label_name(Fail),
hipe_rtl:label_name(BelowLab), 0.01),
BelowLab,
%% StartR contains the index into the jumptable
hipe_rtl:mk_switch(StartR, Map)]
end],
VarMap2,
ConstTab}.
%% Generate the jumptable for Cases while filling in unused positions
%% with the fail label
dense_interval(Cases, Min, IcodeFail) ->
dense_interval(Cases, Min, IcodeFail, 0, 0).
dense_interval([Pair = {Const,_}|Rest], Pos, Fail, Range, NoEntries) ->
Val = hipe_icode:const_value(Const),
if
Pos < Val ->
{Max, Res} =
dense_interval([Pair|Rest], Pos+1, Fail, Range+1, NoEntries),
{Max,[{hipe_icode:mk_const(Pos), Fail}|Res]};
true ->
{Max, Res} = dense_interval(Rest, Pos+1, Fail, Range+1, NoEntries+1),
{Max, [Pair | Res]}
end;
dense_interval([], Max, _, _, _) ->
{Max-1, []}.
%%-------------------------------------------------------------------------
%% switch_val without jumptable
%%
gen_slow_switch_val(I, VarMap, ConstTab, Options) ->
Is = rewrite_switch_val(I),
?IF_DEBUG_LEVEL(3,?msg("Switch: ~w\n", [Is]), no_debug),
hipe_icode2rtl:translate_instrs(Is, VarMap, ConstTab, Options).
rewrite_switch_val(I) ->
Var = hipe_icode:switch_val_term(I),
Fail = hipe_icode:switch_val_fail_label(I),
Cases = hipe_icode:switch_val_cases(I),
rewrite_switch_val_cases(Cases, Fail, Var).
rewrite_switch_val_cases([{C,L}|Cases], Fail, Arg) ->
Tmp = hipe_icode:mk_new_var(),
NextLab = hipe_icode:mk_new_label(),
[hipe_icode:mk_move(Tmp, C),
hipe_icode:mk_if(op_exact_eqeq_2, [Arg, Tmp], L,
hipe_icode:label_name(NextLab)),
NextLab |
rewrite_switch_val_cases(Cases, Fail, Arg)];
rewrite_switch_val_cases([], Fail, _Arg) ->
[hipe_icode:mk_goto(Fail)].
%%-------------------------------------------------------------------------
%% switch_val with binary search jumptable
%%
gen_search_switch_val(Arg, Cases, Default, VarMap, ConstTab, _Options) ->
ValTableR = hipe_rtl:mk_new_reg_gcsafe(),
{Values,_Labels} = split_cases(Cases),
{NewConstTab,Id} = hipe_consttab:insert_sorted_block(ConstTab, Values),
{LabMap,VarMap1} = lbls_from_cases(Cases,VarMap),
Code =
[hipe_rtl:mk_load_address(ValTableR, Id, constant)|
tab(Values,LabMap,Arg,ValTableR,Default)],
{Code, VarMap1, NewConstTab}.
%%-------------------------------------------------------------------------
%%
%% tab/5 creates RTL code for a binary search.
%% It requires two sorted tables one with the keys to search
%% through and one with the corresponding labels to jump to.
%%
%% The implementation is derived from John Bentlys
%% Programming Pearls.
%%
%% Input:
%% KeyList - A list of keys to search through.
%% (Just used to calculate the number of elements.)
%% LableList - A list of labels to jump to.
%% KeyReg - A register containing the key to search for.
%% TablePntrReg - A register containing a pointer to the
%% tables with keys
%% Default - A lable to jump to if the key is not found.
%%
%% Example:
%% KeyTbl: < a, b, d, f, h, i, z >
%% Lbls: < 5, 3, 2, 4, 1, 7, 6 >
%% Default: 8
%% KeyReg: v37
%% TablePntrReg: r41
%%
%% should give code like:
%% r41 <- KeyTbl
%% r42 <- 0
%% r43 <- [r41+16]
%% if (r43 gt v37) then L17 (0.50) else L16
%% L16:
%% r42 <- 16
%% goto L17
%% L17:
%% r46 <- r42 add 16
%% r45 <- [r41+r46]
%% if (r45 gt v37) then L21 (0.50) else L20
%% L20:
%% r42 <- r46
%% goto L21
%% L21:
%% r48 <- r42 add 8
%% r47 <- [r41+r48]
%% if (r47 gt v37) then L23 (0.50) else L22
%% L22:
%% r42 <- r48
%% goto L23
%% L23:
%% r50 <- r42 add 4
%% r49 <- [r41+r50]
%% if (r49 gt v37) then L25 (0.50) else L24
%% L24:
%% r42 <- r42 add 4
%% goto L25
%% L25:
%% if (r42 gt 28) then L6 (0.50) else L18
%% L18:
%% r44 <- [r41+r42]
%% if (r44 eq v37) then L19 (0.90) else L8
%% L19:
%% r42 <- r42 sra 2
%% switch (r42) <L5, L3, L2, L4, L1,
%% L7, L6>
%%
%% The search is done like a rolled out binary search,
%% but instead of starting in the middle we start at
%% the power of two closest above the middle.
%%
%% We let IndexReg point to the lower bound of our
%% search, and then we speculatively look at a
%% position at IndexReg + I where I is a power of 2.
%%
%% Example: Looking for 'h' in
%% KeyTbl: < a, b, d, f, h, i, z >
%%
%% We start with IndexReg=0 and I=4
%% < a, b, d, f, h, i, z >
%% ^ ^
%% IndexReg + I
%%
%% 'f' < 'h' so we add I to IndexReg and divide I with 2
%% IndexReg=4 and I=2
%% < a, b, d, f, h, i, z >
%% ^ ^
%% IndexReg + I
%%
%% 'i' > 'h' so we keep IndexReg and divide I with 2
%% IndexReg=4 and I=1
%% < a, b, d, f, h, i, z >
%% ^ ^
%% IndexReg+ I
%% Now we have found 'h' so we add I to IndexReg -> 5
%% And we can load switch to the label at position 5 in
%% the label table.
%%
%% Now since the wordsize is 4 all numbers above are
%% Multiples of 4.
tab(KeyList, LabelList, KeyReg, TablePntrReg, Default) ->
%% Calculate the size of the table:
%% the number of keys * wordsize
LastOffset = (length(KeyList)-1)*?WORDSIZE,
%% Calculate the power of two closest to the size of the table.
Pow2 = 1 bsl trunc(math:log(LastOffset) / math:log(2)),
%% Create some registers and lables that we need
IndexReg = hipe_rtl:mk_new_reg_gcsafe(),
Temp = hipe_rtl:mk_new_reg_gcsafe(),
Temp2 = hipe_rtl:mk_new_reg_gcsafe(),
Lab1 = hipe_rtl:mk_new_label(),
Lab2 = hipe_rtl:mk_new_label(),
Lab3 = hipe_rtl:mk_new_label(),
Lab4 = hipe_rtl:mk_new_label(),
%% Calculate the position to start looking at
Init = (LastOffset)-Pow2,
%% Create the code
[
hipe_rtl:mk_move(IndexReg,hipe_rtl:mk_imm(0)),
hipe_rtl:mk_load(Temp,TablePntrReg,hipe_rtl:mk_imm(Init)),
hipe_rtl:mk_branch(Temp, geu, KeyReg,
hipe_rtl:label_name(Lab2),
hipe_rtl:label_name(Lab1), 0.5),
Lab1,
hipe_rtl:mk_alu(IndexReg, IndexReg, add, hipe_rtl:mk_imm(Init+?WORDSIZE)),
hipe_rtl:mk_goto(hipe_rtl:label_name(Lab2)),
Lab2] ++
step(Pow2 div 2, TablePntrReg, IndexReg, KeyReg) ++
[hipe_rtl:mk_branch(IndexReg, gt, hipe_rtl:mk_imm(LastOffset),
hipe_rtl:label_name(Default),
hipe_rtl:label_name(Lab3), 0.5),
Lab3,
hipe_rtl:mk_load(Temp2,TablePntrReg,IndexReg),
hipe_rtl:mk_branch(Temp2, eq, KeyReg,
hipe_rtl:label_name(Lab4),
hipe_rtl:label_name(Default), 0.9),
Lab4,
hipe_rtl:mk_alu(IndexReg, IndexReg, sra,
hipe_rtl:mk_imm(hipe_rtl_arch:log2_word_size())),
hipe_rtl:mk_sorted_switch(IndexReg, LabelList, KeyList)
].
step(I,TablePntrReg,IndexReg,KeyReg) ->
Temp = hipe_rtl:mk_new_reg_gcsafe(),
TempIndex = hipe_rtl:mk_new_reg_gcsafe(),
Lab1 = hipe_rtl:mk_new_label(),
Lab2 = hipe_rtl:mk_new_label(),
[hipe_rtl:mk_alu(TempIndex, IndexReg, add, hipe_rtl:mk_imm(I)),
hipe_rtl:mk_load(Temp,TablePntrReg,TempIndex),
hipe_rtl:mk_branch(Temp, gtu, KeyReg,
hipe_rtl:label_name(Lab2),
hipe_rtl:label_name(Lab1) , 0.5),
Lab1] ++
case ?WORDSIZE of
I -> %% Recursive base case
[hipe_rtl:mk_alu(IndexReg, IndexReg, add, hipe_rtl:mk_imm(I)),
hipe_rtl:mk_goto(hipe_rtl:label_name(Lab2)),
Lab2
];
_ -> %% Recursion case
[hipe_rtl:mk_move(IndexReg, TempIndex),
hipe_rtl:mk_goto(hipe_rtl:label_name(Lab2)),
Lab2
| step(I div 2, TablePntrReg, IndexReg, KeyReg)
]
end.
%%-------------------------------------------------------------------------
lbls_from_cases([{_,L}|Rest], VarMap) ->
{Map,VarMap1} = lbls_from_cases(Rest, VarMap),
{RtlL, VarMap2} = hipe_rtl_varmap:icode_label2rtl_label(L,VarMap1),
%% {[{label,hipe_rtl:label_name(RtlL)}|Map],VarMap2};
{[hipe_rtl:label_name(RtlL)|Map],VarMap2};
lbls_from_cases([], VarMap) ->
{[], VarMap}.
%%-------------------------------------------------------------------------
split_cases(L) ->
split_cases(L, [], []).
split_cases([], Vs, Ls) -> {lists:reverse(Vs),lists:reverse(Ls)};
split_cases([{V,L}|Rest], Vs, Ls) ->
split_cases(Rest, [hipe_icode:const_value(V)|Vs], [L|Ls]).
%%-------------------------------------------------------------------------
%%
%% {switch_tuple_arity,X,Fail,N,[{A1,L1},...,{AN,LN}]}
%%
%% if not boxed(X) goto Fail
%% Hdr := *boxed_val(X)
%% switch_int(Hdr,Fail,[{H(A1),L1},...,{H(AN),LN}])
%% where H(Ai) = make_arityval(Ai)
%%
%%-------------------------------------------------------------------------
gen_switch_tuple(I, Map, ConstTab, _Options) ->
Var = hipe_icode:switch_tuple_arity_term(I),
{X, Map1} = hipe_rtl_varmap:icode_var2rtl_var(Var, Map),
Fail0 = hipe_icode:switch_tuple_arity_fail_label(I),
{Fail1, Map2} = hipe_rtl_varmap:icode_label2rtl_label(Fail0, Map1),
FailLab = hipe_rtl:label_name(Fail1),
{Cases, Map3} =
lists:foldr(fun({A,L}, {Rest,M}) ->
{L1,M1} = hipe_rtl_varmap:icode_label2rtl_label(L, M),
L2 = hipe_rtl:label_name(L1),
A1 = hipe_icode:const_value(A),
H1 = hipe_tagscheme:mk_arityval(A1),
{[{H1,L2}|Rest], M1} end,
{[], Map2},
hipe_icode:switch_tuple_arity_cases(I)),
Hdr = hipe_rtl:mk_new_reg_gcsafe(),
IsBoxedLab = hipe_rtl:mk_new_label(),
{[hipe_tagscheme:test_is_boxed(X, hipe_rtl:label_name(IsBoxedLab),
FailLab, 0.9),
IsBoxedLab,
hipe_tagscheme:get_header(Hdr, X) |
gen_switch_int(Hdr, FailLab, Cases)],
Map3, ConstTab}.
%%
%% RTL-level switch-on-int
%%
gen_switch_int(X, FailLab, [{C,L}|Rest]) ->
NextLab = hipe_rtl:mk_new_label(),
[hipe_rtl:mk_branch(X, eq, hipe_rtl:mk_imm(C), L,
hipe_rtl:label_name(NextLab), 0.5),
NextLab |
gen_switch_int(X, FailLab, Rest)];
gen_switch_int(_, FailLab, []) ->
[hipe_rtl:mk_goto(FailLab)].
