[Core] Disaggregated prefilling supports valkey #8724
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…ic to reduce random exit branch
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Add external database valkey operations.
Add valkey in prefill and decode nodes to transfer kv cache. Signed-off-by: Changqi Lu <[email protected]>
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| class ValkeyPipe(TorchDistributedPipe): | ||
| """ | ||
| A pipe that uses the valkey protocol to transfer tensors between ranks. | ||
| """ | ||
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| def __init__(self): | ||
| self.transport_thread: Optional[ThreadPoolExecutor] = None | ||
| self.buffer_size = 0 | ||
| self.buffer_size_lock = threading.Lock() | ||
| self.device = "cpu" | ||
| self.none_tensor = torch.tensor([NONE_INT], device=self.device) | ||
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| self.rcv_metadata_buffer = torch.zeros(self.METADATA_LENGTH, | ||
| dtype=self.METADATA_DTYPE, | ||
| device=self.device) | ||
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| def _send_metadata(self, d_metadata_buffer: torch.Tensor, tensor_key:str = ""): |
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Would be nice if you can move this pipe to a separate file.
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| @abstractmethod | ||
| def send_tensor(self, tensor: Optional[torch.Tensor]) -> None: | ||
| def send_tensor(self, tensor: Optional[torch.Tensor], tensor_key: str = "") -> None: |
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Adding tensor_key is definitely needed for DBs. Would be great if you can make it Optional[str] to force people to generate this metadata if their implementation correctness is based on correct tensor_key .
| elif self.kv_transfer_driver.startswith("valkey"): | ||
| url = self.kv_transfer_driver.split("://")[1] | ||
| ip, port = parse_url(url) | ||
| # TODO add PING command | ||
| self.sender = KVDatabaseTransfer(ip, int(port), self.local_rank, ValkeyPipe()) | ||
| self.recver = KVDatabaseTransfer(ip, int(port), self.local_rank, ValkeyPipe()) | ||
| else: | ||
| raise ValueError("Invalid kv_transfer_driver") |
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lol we definitely need a factory class to build the lookup buffer in the future, but let us keep it as is for now.
| def drop_select(self, input_tokens: torch.Tensor, | ||
| roi: torch.Tensor) -> List[Optional[torch.Tensor]]: | ||
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| if not self.init_valkey: | ||
| ops.valkey_init(self.ip, self.port, True) | ||
| self.init_valkey = True | ||
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| tensor_key = self._encode_tensors(input_tokens, roi) + "/" + str(self.local_rank) | ||
| key_key = tensor_key + "/key" | ||
| val_key = tensor_key + "/value" | ||
| hid_key = tensor_key + "/hidden" | ||
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| key = self.data_pipe.recv_tensor(key_key) | ||
| val = self.data_pipe.recv_tensor(val_key) | ||
| hid = self.data_pipe.recv_tensor(hid_key) | ||
| res = [input_tokens, roi, key, val, hid] | ||
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| return [tensor.to(self.recv_device) for tensor in res] |
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Would be great if you can make sure the valkey entry from the valkey database at prefill instance & decode instance are properly removed after drop_select to avoid OOM. (That's why we call it drop select -- we want to guarantee that the item selected from the lookup buffer will be dropped after drop_select call).
Thanks! |
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m |
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Could you please provide some benchmark tests? |
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support valkey database
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