add files

.gitignore

@@ -1,3 +1,17 @@
+# Custom
+
+status.xml
+
+
+
+# IDEA
+
+*.iml
+.idea/
+
+
+
+
 # Byte-compiled / optimized / DLL files
 __pycache__/
 *.py[cod]

yao-agent.py

@@ -0,0 +1,73 @@
+import os
+import time
+import subprocess
+import json
+from xml.dom.minidom import parse
+import xml.dom.minidom
+from kafka import KafkaProducer
+
+
+ClientID = os.getenv('ClientID', 1)
+KafkaBrokers = os.getenv('KafkaBrokers', 'localhost:9092').split(',')
+
+
+def main():
+	interval = 10
+	while True:
+		try:
+			status, msg_gpu = execute(['nvidia-smi', '-q', '-x', '-f', 'status.xml'])
+			if not status:
+				print("execute failed, ", msg_gpu)
+				continue
+			report_msg()
+			time.sleep(interval)
+		except Exception as e:
+			print(e)
+			time.sleep(interval)
+
+
+def execute(cmd):
+	try:
+		result = subprocess.run(cmd, stdout=subprocess.PIPE, stderr=subprocess.PIPE)
+		if result.returncode == 0:
+			return True, result.stdout.decode('utf-8').rstrip('\n')
+		return False, result.stderr.decode('utf-8').rstrip('\n')
+	except Exception as e:
+		return False, e
+
+
+def report_msg():
+	DOMTree = xml.dom.minidom.parse("status.xml")
+	collection = DOMTree.documentElement
+	gpus = collection.getElementsByTagName("gpu")
+	stats = []
+	for gpu in gpus:
+		stat = {
+			'uuid': gpu.getElementsByTagName('uuid')[0].childNodes[0].data,
+			'product_name': gpu.getElementsByTagName('product_name')[0].childNodes[0].data,
+			'fan_speed': gpu.getElementsByTagName('fan_speed')[0].childNodes[0].data,
+			'performance_state': gpu.getElementsByTagName('performance_state')[0].childNodes[0].data,
+			'memory_total': gpu.getElementsByTagName('fb_memory_usage')[0].getElementsByTagName('total')[0].childNodes[0].data,
+			'memory_free': gpu.getElementsByTagName('fb_memory_usage')[0].getElementsByTagName('free')[0].childNodes[0].data,
+			'memory_used': gpu.getElementsByTagName('fb_memory_usage')[0].getElementsByTagName('used')[0].childNodes[0].data,
+			'utilization_gpu': gpu.getElementsByTagName('utilization')[0].getElementsByTagName('gpu_util')[0].childNodes[0].data,
+			'utilization_mem': gpu.getElementsByTagName('utilization')[0].getElementsByTagName('memory_util')[0].childNodes[0].data,
+			'temperature_gpu': gpu.getElementsByTagName('temperature')[0].getElementsByTagName('gpu_temp')[0].childNodes[0].data,
+			'power_draw': gpu.getElementsByTagName('power_readings')[0].getElementsByTagName('power_draw')[0].childNodes[0].data
+		}
+		stats.append(stat)
+
+	post_fields = {'id': ClientID, 'status': stats}
+	data = json.dumps(post_fields)
+
+	producer = KafkaProducer(bootstrap_servers=KafkaBrokers)
+	future = producer.send('yao', value=data.encode(), partition=0)
+	result = future.get(timeout=10)
+	print(result)
+
+
+if __name__ == '__main__':
+	os.environ["TZ"] = 'Asia/Shanghai'
+	if hasattr(time, 'tzset'):
+		time.tzset()
+	main()