Spaces:
Running
Running
Update implementation for 1F1B overlapping.
Browse files- README.md +1 -1
- main.py +2 -1
- src/execution_model.py +78 -16
- src/strategies.py +20 -22
- src/visualizer.py +15 -1
README.md
CHANGED
@@ -52,7 +52,7 @@ uv run python main.py strategy=zb1p num_devices=4 num_stages=4 num_batches=8
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Running for 1F1B-batch-overlap strategy:
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```
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uv run python main.py strategy=1f1b_overlap num_devices=4 num_stages=4 num_batches=8
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```
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Running for 1F1B-batch-overlap strategy:
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+
```bash
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uv run python main.py strategy=1f1b_overlap num_devices=4 num_stages=4 num_batches=8
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```
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main.py
CHANGED
@@ -105,7 +105,8 @@ def run_1f1b_overlap(cfg: DictConfig) -> None:
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)
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schedule = generate_1f1b_overlap_schedule(schedule_config)
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schedule.execute()
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-
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if __name__ == "__main__":
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)
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schedule = generate_1f1b_overlap_schedule(schedule_config)
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schedule.execute()
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schedule.show()
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# visualize_pipeline_parallelism_dash(schedule, port=cfg.visualization_port)
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if __name__ == "__main__":
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src/execution_model.py
CHANGED
@@ -13,7 +13,52 @@ class Operation:
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self.start_time = None
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self.end_time = None
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class DeviceQueue:
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def __init__(self, stages: List[int], device_id: int):
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@@ -45,6 +90,7 @@ class ScheduleConfig:
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self.p2p_latency = p2p_latency
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self.placement_strategy = placement_strategy
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self.split_backward = split_backward
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# Initialize default operation times
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if self.split_backward:
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@@ -104,9 +150,20 @@ class ScheduleConfig:
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raise ValueError(f"Invalid placement strategy: {self.placement_strategy}")
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def get_op_time(self, op_type: str, stage_id: int):
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if op_type not in self.op_times:
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raise ValueError(f"Invalid operation type: {op_type}")
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-
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times = self.op_times[op_type]
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if isinstance(times, dict):
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# If we have stage-specific times, use those
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@@ -121,9 +178,9 @@ class ScheduleConfig:
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class Schedule:
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def __init__(self, config: ScheduleConfig):
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self.ops = {} # (batch_id, stage_id, op_type) -> Operation
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self.
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for dev_id in range(config.num_devices):
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self.
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self.config = config
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self.init_operations()
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@@ -142,7 +199,7 @@ class Schedule:
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def get_op(self, batch_id: int, stage_id: int, op_type: str):
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return self.ops[(batch_id, stage_id, op_type)]
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-
def get_dependencies(self, op: Operation):
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deps = []
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if op.op_type == "forward":
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if op.stage_id > 0:
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@@ -179,9 +236,10 @@ class Schedule:
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)
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)
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-
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-
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-
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return deps
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def show(self):
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@@ -192,12 +250,12 @@ class Schedule:
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print("\n=== DEVICE QUEUES ===")
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for dev_id in range(self.config.num_devices):
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-
print(f"\nDEVICE {dev_id} (Stages: {self.
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print("-" * 80)
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print(f"{'Batch':^6} | {'Stage':^6} | {'Type':^10} | {'Start':^10} | {'End':^10} | {'Duration':^10}")
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print("-" * 80)
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-
for op in self.
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op_type = op.op_type
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start = f"{op.start_time:.2f}" if op.start_time is not None else "N/A"
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end = f"{op.end_time:.2f}" if op.end_time is not None else "N/A"
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@@ -207,7 +265,7 @@ class Schedule:
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duration = f"{op.end_time - op.start_time:.2f}"
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print(f"{op.batch_id:^6} | {op.stage_id:^6} | {op_type:^10} | {start:^10} | {end:^10} | {duration:^10}")
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-
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# Find the total execution time (if timing info is available)
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if all(op.end_time is not None for op in self.ops.values()):
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total_time = max(op.end_time for op in self.ops.values())
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@@ -215,22 +273,26 @@ class Schedule:
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def execute(self):
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def execute_op(op: Operation):
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deps = self.get_dependencies(op)
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if len(deps) == 0:
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-
op.
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else:
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for dep, gap in deps:
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if dep.end_time is None or dep.start_time is None:
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execute_op(dep)
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op.
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op.
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op.op_type, op.stage_id
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)
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op_num = len(self.
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for i in range(op_num):
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for dev_id in range(self.config.num_devices):
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-
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execute_op(op)
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for op in self.ops.values():
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self.start_time = None
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self.end_time = None
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def set_end_time(self, end_time: float):
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self.end_time = end_time
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def set_start_time(self, start_time: float):
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self.start_time = start_time
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def __repr__(self) -> str:
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return f"Operation(batch_id={self.batch_id}, stage_id={self.stage_id}, op_type={self.op_type})"
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class OverlappedOperation:
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"""Represents multiple operations that are overlapped/executed concurrently."""
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def __init__(self, operations: List[Operation]):
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self.operations = operations
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self.device_id = operations[0].device_id
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# Validate all operations are on the same device
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for op in operations:
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assert op.device_id == self.device_id, "All operations must be on the same device"
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# Create a combined op_type (e.g., "overlapped_forward_backward")
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self.op_type = "overlapped_" + "_".join([op.op_type for op in operations])
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# Use the batch_id and stage_id of the first operation for identification
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# (though we'll track all operations internally)
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self.batch_id = operations[0].batch_id
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self.stage_id = operations[0].stage_id
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# Initialize timing information
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self.start_time = None
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self.end_time = None
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def set_end_time(self, end_time: float):
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self.end_time = end_time
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for op in self.operations:
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op.set_end_time(end_time)
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def set_start_time(self, start_time: float):
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self.start_time = start_time
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for op in self.operations:
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op.set_start_time(start_time)
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def __repr__(self) -> str:
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op_str = ", ".join([f"({op.batch_id},{op.stage_id},{op.op_type})" for op in self.operations])
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return f"OverlappedOperation([{op_str}])"
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class DeviceQueue:
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def __init__(self, stages: List[int], device_id: int):
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self.p2p_latency = p2p_latency
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self.placement_strategy = placement_strategy
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self.split_backward = split_backward
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self.overlapped_op_times = {}
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# Initialize default operation times
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if self.split_backward:
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raise ValueError(f"Invalid placement strategy: {self.placement_strategy}")
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def get_op_time(self, op_type: str, stage_id: int):
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# For overlapped operations, extract the original operation types
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if op_type.startswith("overlapped_"):
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op_parts = op_type.split("_")[1:]
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if len(op_parts) >= 2:
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op_type1, op_type2 = op_parts[0], op_parts[1]
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# Check if we have a specific time for this combination
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if (op_type1, op_type2) in self.overlapped_op_times:
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return self.overlapped_op_times[(op_type1, op_type2)]
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# Otherwise, use the sum of individual times
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return (self.get_op_time(op_type1, stage_id) +
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self.get_op_time(op_type2, stage_id))
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if op_type not in self.op_times:
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raise ValueError(f"Invalid operation type: {op_type}")
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times = self.op_times[op_type]
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if isinstance(times, dict):
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# If we have stage-specific times, use those
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class Schedule:
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def __init__(self, config: ScheduleConfig):
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self.ops = {} # (batch_id, stage_id, op_type) -> Operation
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self.device_queues: List[DeviceQueue] = []
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for dev_id in range(config.num_devices):
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self.device_queues.append(DeviceQueue(config.device_to_stages[dev_id], dev_id))
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self.config = config
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self.init_operations()
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def get_op(self, batch_id: int, stage_id: int, op_type: str):
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return self.ops[(batch_id, stage_id, op_type)]
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def get_dependencies(self, op: Operation, include_device_dependency=True):
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deps = []
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if op.op_type == "forward":
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if op.stage_id > 0:
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)
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)
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if include_device_dependency:
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device_index = self.device_queues[op.device_id].ops.index(op)
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if device_index > 0:
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deps.append((self.device_queues[op.device_id].ops[device_index - 1], 0.0))
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return deps
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def show(self):
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print("\n=== DEVICE QUEUES ===")
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for dev_id in range(self.config.num_devices):
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print(f"\nDEVICE {dev_id} (Stages: {self.device_queues[dev_id].stages}):")
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print("-" * 80)
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print(f"{'Batch':^6} | {'Stage':^6} | {'Type':^10} | {'Start':^10} | {'End':^10} | {'Duration':^10}")
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print("-" * 80)
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for op in self.device_queues[dev_id].ops:
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op_type = op.op_type
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start = f"{op.start_time:.2f}" if op.start_time is not None else "N/A"
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end = f"{op.end_time:.2f}" if op.end_time is not None else "N/A"
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duration = f"{op.end_time - op.start_time:.2f}"
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print(f"{op.batch_id:^6} | {op.stage_id:^6} | {op_type:^10} | {start:^10} | {end:^10} | {duration:^10}")
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+
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# Find the total execution time (if timing info is available)
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if all(op.end_time is not None for op in self.ops.values()):
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total_time = max(op.end_time for op in self.ops.values())
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def execute(self):
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def execute_op(op: Operation):
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if op.end_time is not None:
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return
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deps = self.get_dependencies(op)
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if len(deps) == 0:
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op.set_start_time(0.0)
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else:
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for dep, gap in deps:
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if dep.end_time is None or dep.start_time is None:
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execute_op(dep)
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op.set_start_time(max(dep.end_time + gap for dep, gap in deps))
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op.set_end_time(op.start_time + self.config.get_op_time(
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op.op_type, op.stage_id
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))
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+
op_num = len(self.device_queues[0].ops)
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for i in range(op_num):
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for dev_id in range(self.config.num_devices):
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if len(self.device_queues[dev_id].ops) <= i:
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continue
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op = self.device_queues[dev_id].ops[i]
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execute_op(op)
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for op in self.ops.values():
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src/strategies.py
CHANGED
@@ -1,5 +1,5 @@
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from collections import defaultdict
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-
from src.execution_model import Schedule, ScheduleConfig
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def generate_1f1b_schedule(config: ScheduleConfig):
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@@ -14,23 +14,23 @@ def generate_1f1b_schedule(config: ScheduleConfig):
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steady_batches = config.num_batches - warmup_batches
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for _ in range(warmup_batches):
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schedule.
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schedule.get_op(fwd_batch_id, i, "forward")
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)
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fwd_batch_id += 1
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for _ in range(steady_batches):
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-
schedule.
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schedule.get_op(fwd_batch_id, i, "forward")
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)
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fwd_batch_id += 1
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-
schedule.
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schedule.get_op(bwd_batch_id, i, "backward")
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)
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bwd_batch_id += 1
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for _ in range(cooldown_batches):
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-
schedule.
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schedule.get_op(bwd_batch_id, i, "backward")
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)
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bwd_batch_id += 1
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@@ -53,20 +53,20 @@ def generate_zero_bubble_1p_schedule(config: ScheduleConfig):
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steady_batches = total_batches - warmup_batches
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for _ in range(warmup_batches):
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-
schedule.
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schedule.get_op(fwd_batch_id, i, "forward")
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)
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fwd_batch_id += 1
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for _ in range(steady_batches):
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-
schedule.
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schedule.get_op(fwd_batch_id, i, "forward")
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)
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-
schedule.
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schedule.get_op(bwd_d_batch_id, i, "backward_D")
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)
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if fwd_batch_id - bwd_w_batch_id >= config.num_devices - 1:
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-
schedule.
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schedule.get_op(bwd_w_batch_id, i, "backward_W")
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)
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bwd_w_batch_id += 1
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@@ -74,11 +74,11 @@ def generate_zero_bubble_1p_schedule(config: ScheduleConfig):
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fwd_batch_id += 1
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for _ in range(cooldown_batches):
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-
schedule.
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schedule.get_op(bwd_d_batch_id, i, "backward_D")
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)
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-
schedule.
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schedule.get_op(bwd_w_batch_id, i, "backward_W")
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)
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@@ -86,7 +86,7 @@ def generate_zero_bubble_1p_schedule(config: ScheduleConfig):
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bwd_d_batch_id += 1
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while bwd_w_batch_id < total_batches:
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-
schedule.
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schedule.get_op(bwd_w_batch_id, i, "backward_W")
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)
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bwd_w_batch_id += 1
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@@ -106,23 +106,21 @@ def generate_1f1b_overlap_schedule(config: ScheduleConfig):
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steady_batches = config.num_batches - warmup_batches
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for _ in range(warmup_batches):
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-
schedule.
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schedule.get_op(fwd_batch_id, i, "forward")
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)
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fwd_batch_id += 1
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for _ in range(steady_batches):
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-
schedule.
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-
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-
)
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fwd_batch_id += 1
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-
schedule.dev_queues[i].add_operation(
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schedule.get_op(bwd_batch_id, i, "backward")
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-
)
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bwd_batch_id += 1
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for _ in range(cooldown_batches):
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-
schedule.
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schedule.get_op(bwd_batch_id, i, "backward")
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)
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bwd_batch_id += 1
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@@ -264,7 +262,7 @@ def generate_1f1b_interleave_schedule(config: ScheduleConfig):
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cur_stage_microbatch_id[i] = 0
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cur_stage_microbatch_id[-i] = 0
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for order_item in order:
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-
stage_id = schedule.
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if order_item > 0:
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op_type = "forward"
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@@ -276,7 +274,7 @@ def generate_1f1b_interleave_schedule(config: ScheduleConfig):
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cur_stage_microbatch_id[order_item] = cur_stage_microbatch_id[order_item] + 1
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else:
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raise ValueError(f"Invalid order item: {order_item}")
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-
schedule.
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schedule.get_op(micro_batch_id, stage_id, op_type)
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)
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return schedule
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from collections import defaultdict
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+
from src.execution_model import OverlappedOperation, Schedule, ScheduleConfig
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def generate_1f1b_schedule(config: ScheduleConfig):
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|
14 |
steady_batches = config.num_batches - warmup_batches
|
15 |
|
16 |
for _ in range(warmup_batches):
|
17 |
+
schedule.device_queues[i].add_operation(
|
18 |
schedule.get_op(fwd_batch_id, i, "forward")
|
19 |
)
|
20 |
fwd_batch_id += 1
|
21 |
|
22 |
for _ in range(steady_batches):
|
23 |
+
schedule.device_queues[i].add_operation(
|
24 |
schedule.get_op(fwd_batch_id, i, "forward")
|
25 |
)
|
26 |
fwd_batch_id += 1
|
27 |
+
schedule.device_queues[i].add_operation(
|
28 |
schedule.get_op(bwd_batch_id, i, "backward")
|
29 |
)
|
30 |
bwd_batch_id += 1
|
31 |
|
32 |
for _ in range(cooldown_batches):
|
33 |
+
schedule.device_queues[i].add_operation(
|
34 |
schedule.get_op(bwd_batch_id, i, "backward")
|
35 |
)
|
36 |
bwd_batch_id += 1
|
|
|
53 |
steady_batches = total_batches - warmup_batches
|
54 |
|
55 |
for _ in range(warmup_batches):
|
56 |
+
schedule.device_queues[i].add_operation(
|
57 |
schedule.get_op(fwd_batch_id, i, "forward")
|
58 |
)
|
59 |
fwd_batch_id += 1
|
60 |
|
61 |
for _ in range(steady_batches):
|
62 |
+
schedule.device_queues[i].add_operation(
|
63 |
schedule.get_op(fwd_batch_id, i, "forward")
|
64 |
)
|
65 |
+
schedule.device_queues[i].add_operation(
|
66 |
schedule.get_op(bwd_d_batch_id, i, "backward_D")
|
67 |
)
|
68 |
if fwd_batch_id - bwd_w_batch_id >= config.num_devices - 1:
|
69 |
+
schedule.device_queues[i].add_operation(
|
70 |
schedule.get_op(bwd_w_batch_id, i, "backward_W")
|
71 |
)
|
72 |
bwd_w_batch_id += 1
|
|
|
74 |
fwd_batch_id += 1
|
75 |
|
76 |
for _ in range(cooldown_batches):
|
77 |
+
schedule.device_queues[i].add_operation(
|
78 |
schedule.get_op(bwd_d_batch_id, i, "backward_D")
|
79 |
)
|
80 |
|
81 |
+
schedule.device_queues[i].add_operation(
|
82 |
schedule.get_op(bwd_w_batch_id, i, "backward_W")
|
83 |
)
|
84 |
|
|
|
86 |
bwd_d_batch_id += 1
|
87 |
|
88 |
while bwd_w_batch_id < total_batches:
|
89 |
+
schedule.device_queues[i].add_operation(
|
90 |
schedule.get_op(bwd_w_batch_id, i, "backward_W")
|
91 |
)
|
92 |
bwd_w_batch_id += 1
|
|
|
106 |
steady_batches = config.num_batches - warmup_batches
|
107 |
|
108 |
for _ in range(warmup_batches):
|
109 |
+
schedule.device_queues[i].add_operation(
|
110 |
schedule.get_op(fwd_batch_id, i, "forward")
|
111 |
)
|
112 |
fwd_batch_id += 1
|
113 |
|
114 |
for _ in range(steady_batches):
|
115 |
+
fwd_op = schedule.get_op(fwd_batch_id, i, "forward")
|
116 |
+
bwd_op = schedule.get_op(bwd_batch_id, i, "backward")
|
117 |
+
schedule.device_queues[i].add_operation(OverlappedOperation([fwd_op, bwd_op]))
|
118 |
+
|
119 |
fwd_batch_id += 1
|
|
|
|
|
|
|
120 |
bwd_batch_id += 1
|
121 |
|
122 |
for _ in range(cooldown_batches):
|
123 |
+
schedule.device_queues[i].add_operation(
|
124 |
schedule.get_op(bwd_batch_id, i, "backward")
|
125 |
)
|
126 |
bwd_batch_id += 1
|
|
|
262 |
cur_stage_microbatch_id[i] = 0
|
263 |
cur_stage_microbatch_id[-i] = 0
|
264 |
for order_item in order:
|
265 |
+
stage_id = schedule.device_queues[device_id].stages[abs(order_item)-1]
|
266 |
|
267 |
if order_item > 0:
|
268 |
op_type = "forward"
|
|
|
274 |
cur_stage_microbatch_id[order_item] = cur_stage_microbatch_id[order_item] + 1
|
275 |
else:
|
276 |
raise ValueError(f"Invalid order item: {order_item}")
|
277 |
+
schedule.device_queues[device_id].add_operation(
|
278 |
schedule.get_op(micro_batch_id, stage_id, op_type)
|
279 |
)
|
280 |
return schedule
|
src/visualizer.py
CHANGED
@@ -5,6 +5,8 @@ import plotly.graph_objects as go
|
|
5 |
from typing import List, Dict
|
6 |
from tqdm import tqdm
|
7 |
from functools import lru_cache
|
|
|
|
|
8 |
|
9 |
from src.execution_model import Schedule
|
10 |
|
@@ -26,7 +28,7 @@ def convert_schedule_to_visualization_format(schedule: Schedule):
|
|
26 |
visualization_data = {}
|
27 |
|
28 |
# Organize operations by device
|
29 |
-
for device_id, device_queue in enumerate(schedule.
|
30 |
visualization_data[device_id] = []
|
31 |
|
32 |
for op in device_queue.ops:
|
@@ -494,6 +496,7 @@ def visualize_pipeline_parallelism_dash(
|
|
494 |
debug: bool = False,
|
495 |
enable_caching: bool = True,
|
496 |
schedule_type="1f1b",
|
|
|
497 |
):
|
498 |
"""
|
499 |
Launch a Dash app to visualize the pipeline schedule interactively.
|
@@ -504,9 +507,20 @@ def visualize_pipeline_parallelism_dash(
|
|
504 |
debug: Whether to run the Dash app in debug mode
|
505 |
enable_caching: Whether to cache schedule data and figures
|
506 |
schedule_type: Type of schedule ("1f1b", "zb1p", or custom description)
|
|
|
507 |
"""
|
508 |
app = create_dash_app(
|
509 |
schedule, schedule_type=schedule_type, enable_caching=enable_caching
|
510 |
)
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
511 |
print(f"Starting Dash app on http://localhost:{port}/")
|
512 |
app.run_server(debug=debug, port=port)
|
|
|
5 |
from typing import List, Dict
|
6 |
from tqdm import tqdm
|
7 |
from functools import lru_cache
|
8 |
+
import webbrowser
|
9 |
+
from threading import Timer
|
10 |
|
11 |
from src.execution_model import Schedule
|
12 |
|
|
|
28 |
visualization_data = {}
|
29 |
|
30 |
# Organize operations by device
|
31 |
+
for device_id, device_queue in enumerate(schedule.device_queues):
|
32 |
visualization_data[device_id] = []
|
33 |
|
34 |
for op in device_queue.ops:
|
|
|
496 |
debug: bool = False,
|
497 |
enable_caching: bool = True,
|
498 |
schedule_type="1f1b",
|
499 |
+
open_browser: bool = True,
|
500 |
):
|
501 |
"""
|
502 |
Launch a Dash app to visualize the pipeline schedule interactively.
|
|
|
507 |
debug: Whether to run the Dash app in debug mode
|
508 |
enable_caching: Whether to cache schedule data and figures
|
509 |
schedule_type: Type of schedule ("1f1b", "zb1p", or custom description)
|
510 |
+
open_browser: Whether to automatically open a browser window
|
511 |
"""
|
512 |
app = create_dash_app(
|
513 |
schedule, schedule_type=schedule_type, enable_caching=enable_caching
|
514 |
)
|
515 |
+
|
516 |
+
# Define function to open browser after a short delay
|
517 |
+
def open_browser_tab():
|
518 |
+
webbrowser.open_new_tab(f"http://localhost:{port}/")
|
519 |
+
|
520 |
+
# Open browser automatically if requested
|
521 |
+
if open_browser:
|
522 |
+
# Use a timer to open the browser after the server has started
|
523 |
+
Timer(1.0, open_browser_tab).start()
|
524 |
+
|
525 |
print(f"Starting Dash app on http://localhost:{port}/")
|
526 |
app.run_server(debug=debug, port=port)
|