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b7372420bc
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68123809bb
@ -1,5 +1,6 @@
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import socket
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import socket
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import json
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import json
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from variables import actions
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class ClusterCommunicationModule():
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class ClusterCommunicationModule():
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def __init__(self, host, port, node_manager):
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def __init__(self, host, port, node_manager):
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@ -1,8 +1,8 @@
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import threading
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import threading
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from src.communication import ServiceExplorationModule, ClusterCommunicationModule
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from src.communication import ServiceExplorationModule, ClusterCommunicationModule
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import torch
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import time
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import time
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class NodeManager():
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class NodeManager():
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def __init__(self, host, port):
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def __init__(self, host, port):
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self.status = 'none'
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self.status = 'none'
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@ -10,8 +10,8 @@ class NodeManager():
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{'explanation': 'Add another node into our cluster', 'function': 'add_node'},
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{'explanation': 'Add another node into our cluster', 'function': 'add_node'},
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{'explanation': 'Exit', 'function': 'exit'},
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{'explanation': 'Exit', 'function': 'exit'},
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]
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]
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self.get_GPU_info()
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self.GPU = 'RTX 4090'
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print(f"You have {self.GPU} * {self.GPU_num}")
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self.GPU_num = 1
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# start Cluster Communication Module
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# start Cluster Communication Module
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# let the nodes in the cluster can communicate
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# let the nodes in the cluster can communicate
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@ -23,14 +23,6 @@ class NodeManager():
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time.sleep(2)
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time.sleep(2)
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def get_GPU_info(self):
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self.GPU_num = torch.cuda.device_count()
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assert self.GPU_num > 0, "Your computer doesn't have GPU resource"
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self.GPU = torch.cuda.get_device_name(0)
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for i in range(self.GPU_num):
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assert torch.cuda.get_device_name(i) == self.GPU, "Please provide same type of GPUs."
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def start_service(self):
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def start_service(self):
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communication_thread = threading.Thread(target=self.cluster_communication_module.listen)
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communication_thread = threading.Thread(target=self.cluster_communication_module.listen)
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communication_thread.daemon = True
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communication_thread.daemon = True
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