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 15#include <array> 16#include <vector> 17 18namespace llvm { 19 20// List of cost features. A "cost" feature is a summand of the heuristic-based 21// inline cost, and we define them separately to preserve the original heuristic 22// behavior. 23#define INLINE_COST_FEATURE_ITERATOR(M) \ 24 M(int64_t, {1}, sroa_savings, \ 25 "Savings from SROA (scalar replacement of aggregates)") \ 26 M(int64_t, {1}, sroa_losses, \ 27 "Losses from SROA (scalar replacement of aggregates)") \ 28 M(int64_t, {1}, load_elimination, "Cost of load elimination in the call") \ 29 M(int64_t, {1}, call_penalty, \ 30 "Accumulation of penalty applied to call sites when inlining") \ 31 M(int64_t, {1}, call_argument_setup, \ 32 "Accumulation of call argument setup costs") \ 33 M(int64_t, {1}, load_relative_intrinsic, \ 34 "Accumulation of costs of loading relative intrinsics") \ 35 M(int64_t, {1}, lowered_call_arg_setup, \ 36 "Accumulation of cost of lowered call argument setups") \ 37 M(int64_t, {1}, indirect_call_penalty, \ 38 "Accumulation of costs for indirect calls") \ 39 M(int64_t, {1}, jump_table_penalty, "Accumulation of costs for jump tables") \ 40 M(int64_t, {1}, case_cluster_penalty, \ 41 "Accumulation of costs for case clusters") \ 42 M(int64_t, {1}, switch_penalty, \ 43 "Accumulation of costs for switch statements") \ 44 M(int64_t, {1}, unsimplified_common_instructions, \ 45 "Costs from unsimplified common instructions") \ 46 M(int64_t, {1}, num_loops, "Number of loops in the caller") \ 47 M(int64_t, {1}, dead_blocks, "Number of dead blocks in the caller") \ 48 M(int64_t, {1}, simplified_instructions, \ 49 "Number of simplified instructions") \ 50 M(int64_t, {1}, constant_args, \ 51 "Number of constant arguments in the call site") \ 52 M(int64_t, {1}, constant_offset_ptr_args, \ 53 "Number of constant offset pointer args in the call site") \ 54 M(int64_t, {1}, callsite_cost, "Estimated cost of the call site") \ 55 M(int64_t, {1}, cold_cc_penalty, "Penalty for a cold calling convention") \ 56 M(int64_t, {1}, last_call_to_static_bonus, \ 57 "Bonus for being the last call to static") \ 58 M(int64_t, {1}, is_multiple_blocks, \ 59 "Boolean; is the Callee multiple blocks") \ 60 M(int64_t, {1}, nested_inlines, \ 61 "Would the default inliner perfom nested inlining") \ 62 M(int64_t, {1}, nested_inline_cost_estimate, \ 63 "Estimate of the accumulated cost of nested inlines") \ 64 M(int64_t, {1}, threshold, "Threshold for the heuristic inliner") 65 66// clang-format off 67enum class InlineCostFeatureIndex : size_t { 68#define POPULATE_INDICES(DTYPE, SHAPE, NAME, DOC) NAME, 69 INLINE_COST_FEATURE_ITERATOR(POPULATE_INDICES) 70#undef POPULATE_INDICES 71 72 NumberOfFeatures 73}; 74// clang-format on 75 76using InlineCostFeatures = 77 std::array<int, 78 static_cast<size_t>(InlineCostFeatureIndex::NumberOfFeatures)>; 79 80constexpr bool isHeuristicInlineCostFeature(InlineCostFeatureIndex Feature) { 81 return Feature != InlineCostFeatureIndex::sroa_savings && 82 Feature != InlineCostFeatureIndex::is_multiple_blocks && 83 Feature != InlineCostFeatureIndex::dead_blocks && 84 Feature != InlineCostFeatureIndex::simplified_instructions && 85 Feature != InlineCostFeatureIndex::constant_args && 86 Feature != InlineCostFeatureIndex::constant_offset_ptr_args && 87 Feature != InlineCostFeatureIndex::nested_inlines && 88 Feature != InlineCostFeatureIndex::nested_inline_cost_estimate && 89 Feature != InlineCostFeatureIndex::threshold; 90} 91 92// List of features. Each feature is defined through a triple: 93// - the name of an enum member, which will be the feature index 94// - a textual name, used for ML model binding (so it needs to match the 95// names used by the ML model). 96// - a documentation description. Currently, that is not used anywhere 97// programmatically, and serves as workaround to inability of inserting comments 98// in macros. 99#define INLINE_FEATURE_ITERATOR(M) \ 100 M(int64_t, {1}, callee_basic_block_count, \ 101 "number of basic blocks of the callee") \ 102 M(int64_t, {1}, callsite_height, \ 103 "position of the call site in the original call graph - measured from " \ 104 "the farthest SCC") \ 105 M(int64_t, {1}, node_count, \ 106 "total current number of defined functions in the module") \ 107 M(int64_t, {1}, nr_ctant_params, \ 108 "number of parameters in the call site that are constants") \ 109 M(int64_t, {1}, cost_estimate, "total cost estimate (threshold - free)") \ 110 M(int64_t, {1}, edge_count, "total number of calls in the module") \ 111 M(int64_t, {1}, caller_users, \ 112 "number of module-internal users of the caller, +1 if the caller is " \ 113 "exposed externally") \ 114 M(int64_t, {1}, caller_conditionally_executed_blocks, \ 115 "number of blocks reached from a conditional instruction, in the caller") \ 116 M(int64_t, {1}, caller_basic_block_count, \ 117 "number of basic blocks in the caller") \ 118 M(int64_t, {1}, callee_conditionally_executed_blocks, \ 119 "number of blocks reached from a conditional instruction, in the callee") \ 120 M(int64_t, {1}, callee_users, \ 121 "number of module-internal users of the callee, +1 if the callee is " \ 122 "exposed externally") 123 124// clang-format off 125enum class FeatureIndex : size_t { 126#define POPULATE_INDICES(DTYPE, SHAPE, NAME, COMMENT) NAME, 127// InlineCost features - these must come first 128 INLINE_COST_FEATURE_ITERATOR(POPULATE_INDICES) 129 130// Non-cost features 131 INLINE_FEATURE_ITERATOR(POPULATE_INDICES) 132#undef POPULATE_INDICES 133 134 NumberOfFeatures 135}; 136// clang-format on 137 138constexpr FeatureIndex 139inlineCostFeatureToMlFeature(InlineCostFeatureIndex Feature) { 140 return static_cast<FeatureIndex>(static_cast<size_t>(Feature)); 141} 142 143constexpr size_t NumberOfFeatures = 144 static_cast<size_t>(FeatureIndex::NumberOfFeatures); 145 146extern const std::vector<TensorSpec> FeatureMap; 147 148extern const char *const DecisionName; 149extern const TensorSpec InlineDecisionSpec; 150extern const char *const DefaultDecisionName; 151extern const TensorSpec DefaultDecisionSpec; 152extern const char *const RewardName; 153 154using InlineFeatures = std::vector<int64_t>; 155 156} // namespace llvm 157#endif // LLVM_ANALYSIS_INLINEMODELFEATUREMAPS_H 158