Disp.A：Display Active GPU 初始化状态；Memory-Usage 显存使用率；Volatile GPU-Util GPU 使用率；ECC...
nvidia-smi --query-gpu=utilization.gpu 查询 GPU 的利用率。 输出格式控制 nvidia-smi --format=csv 将输出格式化为 CSV 格式,方便导入到电子表格或其他数据分析工具中。 nvidia-smi --format=csv,noheader 输出 CSV 格式的数据,不包含列头。 高级功能 nvidia-smi -l 5 设置刷新频率为每 5 秒一次,持续输出...
watch -n 1 nvidia-smi 另外建议你不要光看Utilization，要看Power 功耗。仅仅是Utilization高的话不能...
gpu}%") print(f"UtilizationRates Memory: {info.memory}%") 输出结果: 代码语言:python 代码运行次数:0 复制Cloud Studio 代码运行 UtilizationRates Gpu: 1% UtilizationRates Memory: 17% 获取编码利用率信息 代码语言:python 代码运行次数:0 复制Cloud Studio 代码运行 info = nvmlDeviceGetEncoderUtilization(...
$ nvidia-smi--query-gpu=timestamp,name,pci.bus_id,driver_version,pstate,pcie.link.gen.max,pcie.link.gen.current,temperature.gpu,utilization.gpu,utilization.memory,memory.total,memory.free,memory.used--format=csv-l5 When adding additional parameters to a query, ensure that no spaces are added...
NVML and nvidia-smi are oneinthe same (nvidia-smi uses NVML library to get it’sinfo). Since NVML is based on discrete GPU driver architecture, it isn’t supported on Jetsonwhichuses integrated GPU driver. If you want to check GPU utilization, please use tegrastats. ...
UTILIZATION, ECC, TEMPERATURE, POWER, CLOCK, COMPUTE, PIDS, PERFORMANCE, SUPPORTED_CLOCKS, PAGE_RETIREMENT, ACCOUNTING, ENCODER_STATS, SUPPORTED_GPU_TARGET_TEMP, VOLTAGE, FBC_STATS ROW_REMAPPER, RESET_STATUS Flags can be combined with comma e.g. ECC,POWER. ...
{ Total: '256 MiB', Used: '1 MiB', Free: '255 MiB' }, 'Compute Mode': 'Default', Utilization: { Gpu: '36 %', Memory: '18 %', Encoder: '0 %', Decoder: '0 %' }, 'Encoder Stats': { 'Active Sessions': '0', 'Average FPS': '0', 'Average Latency': '0' }, 'FBC...
Error: Command failed: nvidia-smi -i 0 --query-gpu=name,memory.used,memory.total,temperature.gpu,utilization.gpu,utilization.memory,clocks.current.graphics,clocks.current.memory --format=csv,noheader 'nvidia-smi' n�o � reconhecido como um comando interno ou externo, um programa oper�vel...
"""Gets GPU usage information and processes using the nvidia-smi command.""" try: # Run the nvidia-smi command to get GPU information result = subprocess.run( ['nvidia-smi', '--query-gpu=timestamp,name,index,utilization.gpu,utilization.memory,memory.total,memory.free,memory.used', '--fo...