199 lines
6.1 KiB
Python
199 lines
6.1 KiB
Python
# 优化模块
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# 第一步: 常量传播
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def constant_propagation(quads):
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#print("Running Constant Propagation")
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value_map = {}
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optimized = []
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for quad in quads:
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op, arg1, arg2, dest = quad
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if op == '=' and arg1.isdigit():
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# 常量赋值：如 (=, 32, _, _v0)
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value_map[dest] = arg1
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elif op == '=':
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# 变量赋值：如 (=, _v0, _, age)
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if arg1 in value_map:
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new_quad = ('=', value_map[arg1], '_', dest)
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optimized.append(new_quad)
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value_map[dest] = value_map[arg1]
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else:
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optimized.append(quad)
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# 如果 dest 不再被使用，可以考虑删除该赋值
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else:
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# 替换操作数中的变量为已知常量
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new_arg1 = value_map.get(arg1, arg1)
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new_arg2 = value_map.get(arg2, arg2) if arg2 != '_' else '_'
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optimized.append((op, new_arg1, new_arg2, dest))
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return optimized
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# 第二步: 公共子表达式消除
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def common_subexpression_elimination(quads):
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#print("Running Common Subexpression Elimination")
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expr_map = {}
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optimized = []
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temp_counter = 0
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for quad in quads:
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op, arg1, arg2, dest = quad
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if op in ['+', '-', '*', '/']:
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expr_key = f"{arg1} {op} {arg2}"
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if expr_key in expr_map:
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# 复用已有结果
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reused_var = expr_map[expr_key]
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optimized.append(('=', reused_var, '_', dest))
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else:
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# 新表达式
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temp_var = f"_t{temp_counter}"
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temp_counter += 1
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expr_map[expr_key] = temp_var
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optimized.append((op, arg1, arg2, temp_var))
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optimized.append(('=', temp_var, '_', dest))
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else:
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optimized.append(quad)
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return optimized
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# 第三步: 死代码消除
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def dead_code_elimination(quads):
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#print("Running Dead Code Elimination")
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used_vars = set()
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optimized = []
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# 第一遍找出所有被使用的变量
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for quad in quads:
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op, arg1, arg2, dest = quad
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if arg1 != '_' and not arg1.isdigit():
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used_vars.add(arg1)
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if arg2 != '_' and not arg2.isdigit():
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used_vars.add(arg2)
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# 第二遍删除未使用变量的赋值语句
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for quad in quads:
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op, arg1, arg2, dest = quad
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if op == '=' and dest.startswith('_v') and dest not in used_vars:
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continue # 跳过无用的赋值语句
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optimized.append(quad)
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return optimized
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# 第四步: 控制流优化
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def control_flow_simplification(quads):
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# print("Running Control Flow Simplification")
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optimized = []
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for quad in quads:
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op, arg1, arg2, dest = quad
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if op == 'if' and arg2 == 'goto':
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if arg1.isdigit():
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if arg1 == '1':
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optimized.append(('goto', '_', '_', dest))
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elif arg1 == '0':
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continue # 恒假，跳过该条件跳转
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else:
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optimized.append(quad)
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else:
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optimized.append(quad)
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return optimized
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# 第五步: 寄存器重用
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def register_reuse(quads):
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#print("Running Register Reuse (Improved)")
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# 计算活跃变量信息
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live_info = compute_live_vars(quads)
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optimized = []
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available_temps = [] # 可用于复用的临时变量池
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for i, quad in enumerate(quads):
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op, arg1, arg2, dest = quad
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current_live = live_info[i]
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if op == '=':
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# 查看当前 dest 是否会被后续使用
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is_dest_used_later = dest in current_live
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# 如果 dest 不再使用，可以加入可用池
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if not is_dest_used_later and dest.startswith('_'):
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available_temps.append(dest)
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# 尝试复用已死的临时变量
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reused = False
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for var in list(available_temps):
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if var not in [arg1, arg2] and var not in current_live:
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# 安全复用
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optimized.append(('=', arg1, arg2, var))
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available_temps.remove(var)
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if var != dest:
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available_temps.append(dest) # 原 dest 现在可回收
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reused = True
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break
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if not reused:
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optimized.append(quad)
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if dest.startswith('_') and dest not in current_live:
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available_temps.append(dest)
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else:
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optimized.append(quad)
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return optimized
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def compute_live_vars(quads):
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"""
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活跃变量分析：从后往前推导每个 quad 之后仍会使用的变量
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"""
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live_vars = set()
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live_info = []
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for quad in reversed(quads):
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op, arg1, arg2, dest = quad
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# 先移除 dest 的影响（因为 dest 被重新定义）
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if dest in live_vars:
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live_vars.remove(dest)
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# 如果操作数是变量，则加入活跃集合
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if arg1 != '_' and not arg1.isdigit():
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live_vars.add(arg1)
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if arg2 != '_' and not arg2.isdigit():
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live_vars.add(arg2)
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# 把当前活跃变量集合复制一份保存下来
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live_info.append(live_vars.copy())
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# 从后往前遍历，所以需要反转结果
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live_info.reverse()
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return live_info
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# 优化器整合
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def optimize(quads):
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passes = [
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("Constant Propagation", constant_propagation),
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("Common Subexpression Elimination", common_subexpression_elimination),
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("Dead Code Elimination", dead_code_elimination),
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("Control Flow Simplification", control_flow_simplification),
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("Register Reuse", register_reuse),
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]
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for name, opt_func in passes:
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# print(f"Running optimization pass: {name}")
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quads = opt_func(quads)
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return quads
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def output_ir_str(quads):
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lines = []
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for i, quad in enumerate(quads):
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op, arg1, arg2, dest = quad
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quad = f"({op}, {arg1}, {arg2}, {dest})"
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lines.append(f"{i} {quad}")
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return "\n".join(lines)
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