xref: /freebsd/contrib/llvm-project/llvm/include/llvm/Analysis/InlineModelFeatureMaps.h (revision 700637cbb5e582861067a11aaca4d053546871d2)
1 //===- InlineModelFeatureMaps.h - common model runner defs ------*- C++ -*-===//
2 //
3 // Part of the LLVM Project, under the Apache License v2.0 with LLVM Exceptions.
4 // See https://llvm.org/LICENSE.txt for license information.
5 // SPDX-License-Identifier: Apache-2.0 WITH LLVM-exception
6 //
7 //===----------------------------------------------------------------------===//
8 //
9 
10 #ifndef LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H
11 #define LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H
12 
13 #include "llvm/Analysis/TensorSpec.h"
14 #include "llvm/Support/Compiler.h"
15 
16 #include <array>
17 #include <vector>
18 
19 namespace llvm {
20 
21 // List of cost features. A "cost" feature is a summand of the heuristic-based
22 // inline cost, and we define them separately to preserve the original heuristic
23 // behavior.
24 #define INLINE_COST_FEATURE_ITERATOR(M)                                        \
25   M(int64_t, {1}, sroa_savings,                                                \
26     "Savings from SROA (scalar replacement of aggregates)")                    \
27   M(int64_t, {1}, sroa_losses,                                                 \
28     "Losses from SROA (scalar replacement of aggregates)")                     \
29   M(int64_t, {1}, load_elimination, "Cost of load elimination in the call")    \
30   M(int64_t, {1}, call_penalty,                                                \
31     "Accumulation of penalty applied to call sites when inlining")             \
32   M(int64_t, {1}, call_argument_setup,                                         \
33     "Accumulation of call argument setup costs")                               \
34   M(int64_t, {1}, load_relative_intrinsic,                                     \
35     "Accumulation of costs of loading relative intrinsics")                    \
36   M(int64_t, {1}, lowered_call_arg_setup,                                      \
37     "Accumulation of cost of lowered call argument setups")                    \
38   M(int64_t, {1}, indirect_call_penalty,                                       \
39     "Accumulation of costs for indirect calls")                                \
40   M(int64_t, {1}, jump_table_penalty, "Accumulation of costs for jump tables") \
41   M(int64_t, {1}, case_cluster_penalty,                                        \
42     "Accumulation of costs for case clusters")                                 \
43   M(int64_t, {1}, switch_default_dest_penalty,                                 \
44     "Accumulation of costs for switch default destination")                    \
45   M(int64_t, {1}, switch_penalty,                                              \
46     "Accumulation of costs for switch statements")                             \
47   M(int64_t, {1}, unsimplified_common_instructions,                            \
48     "Costs from unsimplified common instructions")                             \
49   M(int64_t, {1}, num_loops, "Number of loops in the caller")                  \
50   M(int64_t, {1}, dead_blocks, "Number of dead blocks in the caller")          \
51   M(int64_t, {1}, simplified_instructions,                                     \
52     "Number of simplified instructions")                                       \
53   M(int64_t, {1}, constant_args,                                               \
54     "Number of constant arguments in the call site")                           \
55   M(int64_t, {1}, constant_offset_ptr_args,                                    \
56     "Number of constant offset pointer args in the call site")                 \
57   M(int64_t, {1}, callsite_cost, "Estimated cost of the call site")            \
58   M(int64_t, {1}, cold_cc_penalty, "Penalty for a cold calling convention")    \
59   M(int64_t, {1}, last_call_to_static_bonus,                                   \
60     "Bonus for being the last call to static")                                 \
61   M(int64_t, {1}, is_multiple_blocks,                                          \
62     "Boolean; is the Callee multiple blocks")                                  \
63   M(int64_t, {1}, nested_inlines,                                              \
64     "Would the default inliner perfom nested inlining")                        \
65   M(int64_t, {1}, nested_inline_cost_estimate,                                 \
66     "Estimate of the accumulated cost of nested inlines")                      \
67   M(int64_t, {1}, threshold, "Threshold for the heuristic inliner")
68 
69 // clang-format off
70 enum class InlineCostFeatureIndex : size_t {
71 #define POPULATE_INDICES(DTYPE, SHAPE, NAME, DOC) NAME,
72   INLINE_COST_FEATURE_ITERATOR(POPULATE_INDICES)
73 #undef POPULATE_INDICES
74 
75   NumberOfFeatures
76 };
77 // clang-format on
78 
79 using InlineCostFeatures =
80     std::array<int,
81                static_cast<size_t>(InlineCostFeatureIndex::NumberOfFeatures)>;
82 
isHeuristicInlineCostFeature(InlineCostFeatureIndex Feature)83 constexpr bool isHeuristicInlineCostFeature(InlineCostFeatureIndex Feature) {
84   return Feature != InlineCostFeatureIndex::sroa_savings &&
85          Feature != InlineCostFeatureIndex::is_multiple_blocks &&
86          Feature != InlineCostFeatureIndex::dead_blocks &&
87          Feature != InlineCostFeatureIndex::simplified_instructions &&
88          Feature != InlineCostFeatureIndex::constant_args &&
89          Feature != InlineCostFeatureIndex::constant_offset_ptr_args &&
90          Feature != InlineCostFeatureIndex::nested_inlines &&
91          Feature != InlineCostFeatureIndex::nested_inline_cost_estimate &&
92          Feature != InlineCostFeatureIndex::threshold;
93 }
94 
95 // List of features. Each feature is defined through a triple:
96 // - the name of an enum member, which will be the feature index
97 // - a textual name, used for ML model binding (so it needs to match the
98 // names used by the ML model).
99 // - a documentation description. Currently, that is not used anywhere
100 // programmatically, and serves as workaround to inability of inserting comments
101 // in macros.
102 #define INLINE_FEATURE_ITERATOR(M)                                             \
103   M(int64_t, {1}, callee_basic_block_count,                                    \
104     "number of basic blocks of the callee")                                    \
105   M(int64_t, {1}, callsite_height,                                             \
106     "position of the call site in the original call graph - measured from "    \
107     "the farthest SCC")                                                        \
108   M(int64_t, {1}, node_count,                                                  \
109     "total current number of defined functions in the module")                 \
110   M(int64_t, {1}, nr_ctant_params,                                             \
111     "number of parameters in the call site that are constants")                \
112   M(int64_t, {1}, cost_estimate, "total cost estimate (threshold - free)")     \
113   M(int64_t, {1}, edge_count, "total number of calls in the module")           \
114   M(int64_t, {1}, caller_users,                                                \
115     "number of module-internal users of the caller, +1 if the caller is "      \
116     "exposed externally")                                                      \
117   M(int64_t, {1}, caller_conditionally_executed_blocks,                        \
118     "number of blocks reached from a conditional instruction, in the caller")  \
119   M(int64_t, {1}, caller_basic_block_count,                                    \
120     "number of basic blocks in the caller")                                    \
121   M(int64_t, {1}, callee_conditionally_executed_blocks,                        \
122     "number of blocks reached from a conditional instruction, in the callee")  \
123   M(int64_t, {1}, callee_users,                                                \
124     "number of module-internal users of the callee, +1 if the callee is "      \
125     "exposed externally")                                                      \
126   M(int64_t, {1}, is_callee_avail_external,                                    \
127     "Is callee an available-externally linkage type (i.e. could be DCEd if "   \
128     "not "                                                                     \
129     "fully inlined by ElimAvailExtern)")                                       \
130   M(int64_t, {1}, is_caller_avail_external,                                    \
131     "Is caller an available-externally linkage type (i.e. could be DCEd if "   \
132     "not "                                                                     \
133     "fully inlined by ElimAvailExtern)")
134 
135 // Not all features listed in FeatureIndex are used by the ML model.
136 // Specifically, callee_embedding and caller_embedding are used only when the
137 // usage of IR2Vec embeddings is explicitly enabled. Meaning, the size/number of
138 // features is not static. So, we cannot determine number of features based on
139 // the number of elements in this enum.
140 // clang-format off
141 enum class FeatureIndex : size_t {
142 #define POPULATE_INDICES(DTYPE, SHAPE, NAME, COMMENT) NAME,
143 // InlineCost features - these must come first
144   INLINE_COST_FEATURE_ITERATOR(POPULATE_INDICES)
145 
146 // Non-cost features
147   INLINE_FEATURE_ITERATOR(POPULATE_INDICES)
148 #undef POPULATE_INDICES
149 
150 // IR2Vec embeddings
151 // Dimensions of embeddings are not known in the compile time (until vocab is
152 // read). Hence macros cannot be used here.
153   callee_embedding,
154   caller_embedding
155 };
156 // clang-format on
157 
158 constexpr FeatureIndex
inlineCostFeatureToMlFeature(InlineCostFeatureIndex Feature)159 inlineCostFeatureToMlFeature(InlineCostFeatureIndex Feature) {
160   return static_cast<FeatureIndex>(static_cast<size_t>(Feature));
161 }
162 
163 LLVM_ABI extern std::vector<TensorSpec> FeatureMap;
164 
165 LLVM_ABI extern const char *const DecisionName;
166 LLVM_ABI extern const TensorSpec InlineDecisionSpec;
167 LLVM_ABI extern const char *const DefaultDecisionName;
168 LLVM_ABI extern const TensorSpec DefaultDecisionSpec;
169 LLVM_ABI extern const char *const RewardName;
170 
171 using InlineFeatures = std::vector<int64_t>;
172 
173 } // namespace llvm
174 #endif // LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H
175