Kirill
02c9843e1b
- Implemented runtime-only adaptive quality controller to optimize simulation performance based on CPU time. - Added adaptive quality thresholds and recovery cycles to dynamically adjust simulation fidelity. - Introduced single-step solving method for civilization transitions to improve performance under high loads. - Updated benchmark scripts to include speed parameter for testing various simulation speeds. - Added tests for adaptive quality adjustments and their effects on civilization flow calculations. - Documented results of optimization attempts and their impact on performance metrics.
68 lines
3.3 KiB
GDScript
68 lines
3.3 KiB
GDScript
extends SceneTree
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## Full-cycle throughput benchmark; diagnostic input is never modified.
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const E = preload("res://world/owniverse/math/exact.gd")
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func _initialize():
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call_deferred("run")
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func restore_json_integers(value):
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# JSON parses ordinary integer tokens as float. Large integers are $exact.
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if value is float and value == floorf(value) and absf(value) <= 9007199254740991:
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return int(value)
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if value is Dictionary:
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for key in value: value[key] = restore_json_integers(value[key])
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elif value is Array:
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for i in value.size(): value[i] = restore_json_integers(value[i])
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return value
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func run():
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var args = OS.get_cmdline_user_args()
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if args.is_empty():
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print("Usage: --script tests/benchmark_civilization_flows.gd -- /path/to/save.adventure.json [delta_seconds] [profile] [cycles=100] [speed=1..6]")
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quit(1)
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return
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var data = JSON.parse_string(FileAccess.get_file_as_string(args[0]))
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if not data is Dictionary or data.get("format_version") != 6:
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push_error("Expected diagnostic JSON format 6")
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quit(1)
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return
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var initial: Dictionary = E.decode(restore_json_integers(data)).state
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var validation: String = root.get_node("SaveManager").validate_data(E.decode(restore_json_integers(data)))
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print("Save validation: ", "OK" if validation.is_empty() else validation)
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var delta: float = args[1].to_float() if args.size() > 1 else 1.0 / 60.0
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if not is_finite(delta) or delta <= 0:
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quit(1)
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return
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var selected_speed: int = 6
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for arg in args:
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if arg.begins_with("speed="):
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selected_speed = clampi(arg.trim_prefix("speed=").to_int(), 1, root.get_node("Global").SPEED_LIMIT)
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for speed in [selected_speed]:
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var world = load("res://world/owniverse/owniverse.gd").new()
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world.catalog.load_definitions(root.get_node("Global").OwniverseEntities)
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world.state = initial.duplicate(true)
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world.speed = speed
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world.profile_enabled = args.has("profile")
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var elapsed: Array = []
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var cycles: int = 100
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for arg in args:
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if arg.begins_with("cycles="): cycles = maxi(1, arg.trim_prefix("cycles=").to_int())
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var initial_clock: Variant = world.state.time.datetime
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for cycle in cycles:
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var start: int = Time.get_ticks_usec()
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world.evolute(delta)
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elapsed.append((Time.get_ticks_usec() - start) / 1000.0)
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print("Speed %d, %d complete %.3f-second steps" % [speed, cycles, delta])
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print("Min/max ms: ", elapsed.min(), "/", elapsed.max())
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print("Game years applied: ", E.fixed(E.subtract(world.state.time.datetime, initial_clock)))
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var total_ms: float = 0.0
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for sample in elapsed: total_ms += sample
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var throughput: float = float(cycles) * delta / (total_ms / 1000.0)
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print("Mean complete cycle ms: ", total_ms / cycles)
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print("Full cycles/s: ", float(cycles) * 1000.0 / total_ms)
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print("Simulation throughput: %.3f real-time seconds processed per CPU second; needs >= 1.0 to keep up" % throughput)
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if world.profile_enabled: print("CPU profile (usec, calls): ", world.profile)
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for entity in world.catalog.entities.values(): entity.free()
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world.free()
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quit()
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