Skip to content

vllm.v1.worker.ubatching

_CURRENT_CONTEXTS module-attribute 

_CURRENT_CONTEXTS: list[Optional[UBatchContext]] = [
    None,
    None,
]

_THREAD_ID_TO_CONTEXT module-attribute 

_THREAD_ID_TO_CONTEXT: dict = {}

dbo_maybe_run_recv_hook module-attribute 

dbo_maybe_run_recv_hook = _register_ubatch_function(
    maybe_run_recv_hook
)

dbo_switch_to_comm module-attribute 

dbo_switch_to_comm = _register_ubatch_function(
    switch_to_comm
)

dbo_switch_to_comm_sync module-attribute 

dbo_switch_to_comm_sync = _register_ubatch_function(
    switch_to_comm_sync
)

dbo_switch_to_compute module-attribute 

dbo_switch_to_compute = _register_ubatch_function(
    switch_to_compute
)

dbo_switch_to_compute_sync module-attribute 

dbo_switch_to_compute_sync = _register_ubatch_function(
    switch_to_compute_sync
)

dbo_yield module-attribute 

dbo_yield = _register_ubatch_function(yield_)

dbo_yield_and_switch_from_comm_to_compute module-attribute 

dbo_yield_and_switch_from_comm_to_compute = (
    _register_ubatch_function(
        yield_and_switch_from_comm_to_compute
    )
)

dbo_yield_and_switch_from_compute_to_comm module-attribute 

dbo_yield_and_switch_from_compute_to_comm = (
    _register_ubatch_function(
        yield_and_switch_from_compute_to_comm
    )
)

UBatchContext

Context manager for micro-batching synchronization using threading events.

Source code in vllm/v1/worker/ubatching.py 
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
class UBatchContext:
    """
    Context manager for micro-batching synchronization using threading events.
    """

    def __init__(
        self,
        id: int,
        comm_stream: torch.cuda.Stream,
        compute_stream: torch.cuda.Stream,
        forward_context: ForwardContext,
        ready_barrier: threading.Barrier,
        cpu_wait_event: threading.Event,
        cpu_signal_event: threading.Event,
        gpu_comm_done_event: torch.cuda.Event,
        gpu_compute_done_event: torch.cuda.Event,
        schedule: str = "default",
    ):
        self.id = id
        self.comm_stream = comm_stream
        self.compute_stream = compute_stream
        self.forward_context = forward_context
        self.ready_barrier = ready_barrier
        self.cpu_wait_event = cpu_wait_event
        self.cpu_signal_event = cpu_signal_event
        self.current_stream = compute_stream
        self.gpu_comm_done_event = gpu_comm_done_event
        self.gpu_compute_done_event = gpu_compute_done_event
        self.schedule = schedule
        self.recv_hook = None

    def __enter__(self):
        global _CURRENT_CONTEXTS, _THREAD_ID_TO_CONTEXT
        _THREAD_ID_TO_CONTEXT[threading.get_ident()] = self.id
        _CURRENT_CONTEXTS[self.id] = self
        self.ready_barrier.wait()

        self.cpu_wait_event.wait()
        self.cpu_wait_event.clear()
        self._restore_context()
        # Assume we want to start on the compute stream
        self.update_stream(self.compute_stream)
        return self

    def __exit__(self, exc_type, exc_val, exc_tb):
        global _CURRENT_CONTEXTS, _THREAD_ID_TO_CONTEXT
        _CURRENT_CONTEXTS[self.id] = None
        del _THREAD_ID_TO_CONTEXT[threading.get_ident()]
        self.maybe_run_recv_hook()
        self.cpu_signal_event.set()
        self.cpu_wait_event.clear()
        return False

    def _restore_context(self):
        forward_context._forward_context = self.forward_context

    def update_stream(self, stream):
        self.current_stream = stream
        if current_stream() != self.current_stream:
            torch.cuda.set_stream(self.current_stream)

    def _signal_comm_done(self):
        self.gpu_comm_done_event.record(self.comm_stream)

    def _signal_compute_done(self):
        self.gpu_compute_done_event.record(self.compute_stream)

    def _wait_compute_done(self):
        self.comm_stream.wait_event(self.gpu_compute_done_event)

    def _wait_comm_done(self):
        self.compute_stream.wait_event(self.gpu_comm_done_event)

    def _cpu_yield(self):
        # It is critical for correctness that only one thread is running
        # at a time. These asserts just make sure that this is the only
        # thread running before waking the other one up and going to sleep
        assert forward_context._forward_context == self.forward_context
        assert current_stream() == self.current_stream
        assert not self.cpu_wait_event.is_set()

        self.cpu_signal_event.set()
        self.cpu_wait_event.wait()
        self.cpu_wait_event.clear()
        self._restore_context()

    def switch_to_comm(self):
        self.update_stream(self.comm_stream)

    def switch_to_compute(self):
        self.update_stream(self.compute_stream)

    def switch_to_comm_sync(self):
        self._signal_compute_done()
        self.update_stream(self.comm_stream)
        self._wait_compute_done()

    def switch_to_compute_sync(self):
        self._signal_comm_done()
        self.update_stream(self.compute_stream)
        self._wait_comm_done()

    def maybe_run_recv_hook(self):
        if self.recv_hook is not None:
            self.recv_hook()
            self.recv_hook = None

    def yield_(self):
        self.current_stream = current_stream()
        self._cpu_yield()
        self.update_stream(self.current_stream)

    def yield_and_switch_from_compute_to_comm(self):
        assert current_stream() == self.compute_stream
        self._signal_compute_done()
        self._cpu_yield()
        assert self.current_stream == self.compute_stream
        self.update_stream(self.comm_stream)
        self._wait_compute_done()

    def yield_and_switch_from_comm_to_compute(self):
        assert current_stream() == self.comm_stream
        self._signal_comm_done()
        self._cpu_yield()
        assert self.current_stream == self.comm_stream
        self.update_stream(self.compute_stream)
        self._wait_comm_done()

comm_stream instance-attribute 

comm_stream = comm_stream

compute_stream instance-attribute 

compute_stream = compute_stream

cpu_signal_event instance-attribute 

cpu_signal_event = cpu_signal_event

cpu_wait_event instance-attribute 

cpu_wait_event = cpu_wait_event

current_stream instance-attribute 

current_stream = compute_stream

forward_context instance-attribute 

forward_context = forward_context

gpu_comm_done_event instance-attribute 

gpu_comm_done_event = gpu_comm_done_event

gpu_compute_done_event instance-attribute 

gpu_compute_done_event = gpu_compute_done_event

id instance-attribute 

id = id

ready_barrier instance-attribute 

ready_barrier = ready_barrier

recv_hook instance-attribute 

recv_hook = None

schedule instance-attribute 

schedule = schedule

__enter__ 

__enter__()
Source code in vllm/v1/worker/ubatching.py 
47
48
49
50
51
52
53
54
55
56
57
58
def __enter__(self):
    global _CURRENT_CONTEXTS, _THREAD_ID_TO_CONTEXT
    _THREAD_ID_TO_CONTEXT[threading.get_ident()] = self.id
    _CURRENT_CONTEXTS[self.id] = self
    self.ready_barrier.wait()

    self.cpu_wait_event.wait()
    self.cpu_wait_event.clear()
    self._restore_context()
    # Assume we want to start on the compute stream
    self.update_stream(self.compute_stream)
    return self

__exit__ 

__exit__(exc_type, exc_val, exc_tb)
Source code in vllm/v1/worker/ubatching.py 
60
61
62
63
64
65
66
67
def __exit__(self, exc_type, exc_val, exc_tb):
    global _CURRENT_CONTEXTS, _THREAD_ID_TO_CONTEXT
    _CURRENT_CONTEXTS[self.id] = None
    del _THREAD_ID_TO_CONTEXT[threading.get_ident()]
    self.maybe_run_recv_hook()
    self.cpu_signal_event.set()
    self.cpu_wait_event.clear()
    return False

__init__ 

__init__(
    id: int,
    comm_stream: Stream,
    compute_stream: Stream,
    forward_context: ForwardContext,
    ready_barrier: Barrier,
    cpu_wait_event: Event,
    cpu_signal_event: Event,
    gpu_comm_done_event: Event,
    gpu_compute_done_event: Event,
    schedule: str = "default",
)
Source code in vllm/v1/worker/ubatching.py 
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
def __init__(
    self,
    id: int,
    comm_stream: torch.cuda.Stream,
    compute_stream: torch.cuda.Stream,
    forward_context: ForwardContext,
    ready_barrier: threading.Barrier,
    cpu_wait_event: threading.Event,
    cpu_signal_event: threading.Event,
    gpu_comm_done_event: torch.cuda.Event,
    gpu_compute_done_event: torch.cuda.Event,
    schedule: str = "default",
):
    self.id = id
    self.comm_stream = comm_stream
    self.compute_stream = compute_stream
    self.forward_context = forward_context
    self.ready_barrier = ready_barrier
    self.cpu_wait_event = cpu_wait_event
    self.cpu_signal_event = cpu_signal_event
    self.current_stream = compute_stream
    self.gpu_comm_done_event = gpu_comm_done_event
    self.gpu_compute_done_event = gpu_compute_done_event
    self.schedule = schedule
    self.recv_hook = None

_cpu_yield 

_cpu_yield()
Source code in vllm/v1/worker/ubatching.py 
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
def _cpu_yield(self):
    # It is critical for correctness that only one thread is running
    # at a time. These asserts just make sure that this is the only
    # thread running before waking the other one up and going to sleep
    assert forward_context._forward_context == self.forward_context
    assert current_stream() == self.current_stream
    assert not self.cpu_wait_event.is_set()

    self.cpu_signal_event.set()
    self.cpu_wait_event.wait()
    self.cpu_wait_event.clear()
    self._restore_context()

_restore_context 

_restore_context()
Source code in vllm/v1/worker/ubatching.py 
69
70
def _restore_context(self):
    forward_context._forward_context = self.forward_context

_signal_comm_done 

_signal_comm_done()
Source code in vllm/v1/worker/ubatching.py 
77
78
def _signal_comm_done(self):
    self.gpu_comm_done_event.record(self.comm_stream)

_signal_compute_done 

_signal_compute_done()
Source code in vllm/v1/worker/ubatching.py 
80
81
def _signal_compute_done(self):
    self.gpu_compute_done_event.record(self.compute_stream)

_wait_comm_done 

_wait_comm_done()
Source code in vllm/v1/worker/ubatching.py 
86
87
def _wait_comm_done(self):
    self.compute_stream.wait_event(self.gpu_comm_done_event)

_wait_compute_done 

_wait_compute_done()
Source code in vllm/v1/worker/ubatching.py 
83
84
def _wait_compute_done(self):
    self.comm_stream.wait_event(self.gpu_compute_done_event)

maybe_run_recv_hook 

maybe_run_recv_hook()
Source code in vllm/v1/worker/ubatching.py 
118
119
120
121
def maybe_run_recv_hook(self):
    if self.recv_hook is not None:
        self.recv_hook()
        self.recv_hook = None

switch_to_comm 

switch_to_comm()
Source code in vllm/v1/worker/ubatching.py 
102
103
def switch_to_comm(self):
    self.update_stream(self.comm_stream)

switch_to_comm_sync 

switch_to_comm_sync()
Source code in vllm/v1/worker/ubatching.py 
108
109
110
111
def switch_to_comm_sync(self):
    self._signal_compute_done()
    self.update_stream(self.comm_stream)
    self._wait_compute_done()

switch_to_compute 

switch_to_compute()
Source code in vllm/v1/worker/ubatching.py 
105
106
def switch_to_compute(self):
    self.update_stream(self.compute_stream)

switch_to_compute_sync 

switch_to_compute_sync()
Source code in vllm/v1/worker/ubatching.py 
113
114
115
116
def switch_to_compute_sync(self):
    self._signal_comm_done()
    self.update_stream(self.compute_stream)
    self._wait_comm_done()

update_stream 

update_stream(stream)
Source code in vllm/v1/worker/ubatching.py 
72
73
74
75
def update_stream(self, stream):
    self.current_stream = stream
    if current_stream() != self.current_stream:
        torch.cuda.set_stream(self.current_stream)

yield_ 

yield_()
Source code in vllm/v1/worker/ubatching.py 
123
124
125
126
def yield_(self):
    self.current_stream = current_stream()
    self._cpu_yield()
    self.update_stream(self.current_stream)

yield_and_switch_from_comm_to_compute 

yield_and_switch_from_comm_to_compute()
Source code in vllm/v1/worker/ubatching.py 
136
137
138
139
140
141
142
def yield_and_switch_from_comm_to_compute(self):
    assert current_stream() == self.comm_stream
    self._signal_comm_done()
    self._cpu_yield()
    assert self.current_stream == self.comm_stream
    self.update_stream(self.compute_stream)
    self._wait_comm_done()

yield_and_switch_from_compute_to_comm 

yield_and_switch_from_compute_to_comm()
Source code in vllm/v1/worker/ubatching.py 
128
129
130
131
132
133
134
def yield_and_switch_from_compute_to_comm(self):
    assert current_stream() == self.compute_stream
    self._signal_compute_done()
    self._cpu_yield()
    assert self.current_stream == self.compute_stream
    self.update_stream(self.comm_stream)
    self._wait_compute_done()

_register_ubatch_function 

_register_ubatch_function(func)
Source code in vllm/v1/worker/ubatching.py 
155
156
157
158
159
160
161
162
def _register_ubatch_function(func):
    def wrapper(*args, **kwargs):
        if len(_THREAD_ID_TO_CONTEXT) > 0:
            ctx_idx = _THREAD_ID_TO_CONTEXT[threading.get_ident()]
            ctx = _CURRENT_CONTEXTS[ctx_idx]
            func(ctx, *args, **kwargs)

    return wrapper

dbo_current_ubatch_id 

dbo_current_ubatch_id() -> int
Source code in vllm/v1/worker/ubatching.py 
149
150
151
152
def dbo_current_ubatch_id() -> int:
    if len(_THREAD_ID_TO_CONTEXT) == 0:
        return 0
    return _THREAD_ID_TO_CONTEXT[threading.get_ident()]

dbo_enabled 

dbo_enabled() -> bool
Source code in vllm/v1/worker/ubatching.py 
145
146
def dbo_enabled() -> bool:
    return len(_THREAD_ID_TO_CONTEXT) > 0

dbo_register_recv_hook 

dbo_register_recv_hook(recv_hook)
Source code in vllm/v1/worker/ubatching.py 
181
182
183
184
185
def dbo_register_recv_hook(recv_hook):
    if len(_THREAD_ID_TO_CONTEXT) > 0:
        ctx_idx = _THREAD_ID_TO_CONTEXT[threading.get_ident()]
        next_ctx = _CURRENT_CONTEXTS[(ctx_idx + 1) % 2]
        next_ctx.recv_hook = recv_hook

make_ubatch_contexts 

make_ubatch_contexts(
    num_micro_batches: int,
    compute_stream: Stream,
    comm_stream: Stream,
    forward_contexts: list[ForwardContext],
    ready_barrier: Barrier,
    schedule: str = "default",
) -> list[UBatchContext]
Source code in vllm/v1/worker/ubatching.py 
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
def make_ubatch_contexts(
    num_micro_batches: int,
    compute_stream: torch.cuda.Stream,
    comm_stream: torch.cuda.Stream,
    forward_contexts: list[ForwardContext],
    ready_barrier: threading.Barrier,
    schedule: str = "default",
) -> list[UBatchContext]:
    assert num_micro_batches == 2, "only been tested with 2 micro-batches"
    """
    Create a context manager for micro-batching synchronization.
    """
    cpu_events = [threading.Event() for _ in range(num_micro_batches)]
    gpu_comm_done_events = [torch.cuda.Event() for _ in range(num_micro_batches)]
    gpu_compute_done_events = [torch.cuda.Event() for _ in range(num_micro_batches)]

    assert len(forward_contexts) == 2

    ctxs = []
    for i in range(num_micro_batches):
        ctx = UBatchContext(
            id=i,
            compute_stream=compute_stream,
            comm_stream=comm_stream,
            forward_context=forward_contexts[i],
            ready_barrier=ready_barrier,
            cpu_wait_event=cpu_events[i],
            cpu_signal_event=cpu_events[(i + 1) % num_micro_batches],
            gpu_comm_done_event=gpu_comm_done_events[i],
            gpu_compute_done_event=gpu_compute_done_events[i],
            schedule=schedule,
        )
        ctxs.append(ctx)

    return ctxs