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  1. docs/metrics/prometheus/list.md

    | `minio_node_cpu_avg_system`          | CPU system time.                           |
    | `minio_node_cpu_avg_system_avg`      | CPU system time (avg).                     |
    | `minio_node_cpu_avg_system_max`      | CPU system time (max).                     |
    | `minio_node_cpu_avg_idle`            | CPU idle time.                             |
    Registered: Sun Nov 03 19:28:11 UTC 2024
    - Last Modified: Mon Jul 29 18:48:51 UTC 2024
    - 43.3K bytes
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  2. cmd/metrics-resource.go

    		cpuUser:           "CPU user time",
    		cpuSystem:         "CPU system time",
    		cpuIdle:           "CPU idle time",
    		cpuIOWait:         "CPU ioWait time",
    		cpuSteal:          "CPU steal time",
    		cpuNice:           "CPU nice time",
    		cpuLoad1:          "CPU load average 1min",
    		cpuLoad5:          "CPU load average 5min",
    		cpuLoad15:         "CPU load average 15min",
    Registered: Sun Nov 03 19:28:11 UTC 2024
    - Last Modified: Wed Jul 24 23:30:33 UTC 2024
    - 17.2K bytes
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  3. README.md

    A smaller CPU-only package is also available:
    
    ```
    $ pip install tensorflow-cpu
    ```
    
    To update TensorFlow to the latest version, add `--upgrade` flag to the above
    commands.
    
    *Nightly binaries are available for testing using the
    [tf-nightly](https://pypi.python.org/pypi/tf-nightly) and
    [tf-nightly-cpu](https://pypi.python.org/pypi/tf-nightly-cpu) packages on PyPi.*
    
    Registered: Tue Nov 05 12:39:12 UTC 2024
    - Last Modified: Thu Oct 05 15:00:10 UTC 2023
    - 11.9K bytes
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  4. cmd/update.go

    			cpuMap[cpus[i].PhysicalID] = struct{}{}
    			coreMap[cpus[i].CoreID] = struct{}{}
    		}
    		cpu := cpus[0]
    		uaAppend(" CPU ", fmt.Sprintf("(total_cpus:%d, total_cores:%d; vendor:%s; family:%s; model:%s; stepping:%d; model_name:%s)",
    			len(cpuMap), len(coreMap), cpu.VendorID, cpu.Family, cpu.Model, cpu.Stepping, cpu.ModelName))
    	}
    	uaAppend(")", "")
    
    	return strings.Join(userAgentParts, "")
    }
    
    Registered: Sun Nov 03 19:28:11 UTC 2024
    - Last Modified: Fri May 24 23:05:23 UTC 2024
    - 18.7K bytes
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  5. docs/zh/docs/deployment/concepts.md

    ## 资源利用率
    
    您的服务器是一个**资源**,您可以通过您的程序消耗或**利用**CPU 上的计算时间以及可用的 RAM 内存。
    
    您想要消耗/利用多少系统资源? 您可能很容易认为“不多”,但实际上,您可能希望在不崩溃的情况下**尽可能多地消耗**。
    
    如果您支付了 3 台服务器的费用,但只使用了它们的一点点 RAM 和 CPU,那么您可能**浪费金钱** 💸,并且可能 **浪费服务器电力** 🌎,等等。
    
    在这种情况下,最好只拥有 2 台服务器并使用更高比例的资源(CPU、内存、磁盘、网络带宽等)。
    
    另一方面,如果您有 2 台服务器,并且正在使用 **100% 的 CPU 和 RAM**,则在某些时候,一个进程会要求更多内存,并且服务器将不得不使用磁盘作为“内存” (这可能会慢数千倍),甚至**崩溃**。 或者一个进程可能需要执行一些计算,并且必须等到 CPU 再次空闲。
    
    Registered: Sun Nov 03 07:19:11 UTC 2024
    - Last Modified: Tue Aug 06 04:48:30 UTC 2024
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  6. common-protos/k8s.io/api/autoscaling/v2beta2/generated.proto

    // ContainerResourceMetricSource indicates how to scale on a resource metric known to
    // Kubernetes, as specified in requests and limits, describing each pod in the
    // current scale target (e.g. CPU or memory).  The values will be averaged
    // together before being compared to the target.  Such metrics are built in to
    // Kubernetes, and have special scaling options on top of those available to
    Registered: Wed Nov 06 22:53:10 UTC 2024
    - Last Modified: Mon Mar 11 18:43:24 UTC 2024
    - 21K bytes
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  7. common-protos/k8s.io/api/autoscaling/v1/generated.proto

      optional int32 desiredReplicas = 4;
    
      // currentCPUUtilizationPercentage is the current average CPU utilization over all pods, represented as a percentage of requested CPU,
      // e.g. 70 means that an average pod is using now 70% of its requested CPU.
      // +optional
      optional int32 currentCPUUtilizationPercentage = 5;
    }
    
    // MetricSpec specifies how to scale based on a single metric
    Registered: Wed Nov 06 22:53:10 UTC 2024
    - Last Modified: Mon Mar 11 18:43:24 UTC 2024
    - 22K bytes
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  8. docs/pt/docs/deployment/concepts.md

    Nesse caso, seria melhor ter apenas 2 servidores e usar uma porcentagem maior de seus recursos (CPU, memória, disco, largura de banda de rede, etc).
    
    Registered: Sun Nov 03 07:19:11 UTC 2024
    - Last Modified: Fri Oct 04 11:04:50 UTC 2024
    - 19.7K bytes
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  9. docs/de/docs/deployment/concepts.md

    In diesem Fall könnte es besser sein, nur zwei Server zu haben und einen höheren Prozentsatz von deren Ressourcen zu nutzen (CPU, Arbeitsspeicher, Festplatte, Netzwerkbandbreite, usw.).
    
    Registered: Sun Nov 03 07:19:11 UTC 2024
    - Last Modified: Tue Aug 06 04:48:30 UTC 2024
    - 20.6K bytes
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  10. docs/en/docs/deployment/concepts.md

    In that case, it could be better to have only 2 servers and use a higher percentage of their resources (CPU, memory, disk, network bandwidth, etc).
    
    Registered: Sun Nov 03 07:19:11 UTC 2024
    - Last Modified: Wed Sep 18 16:09:57 UTC 2024
    - 17.8K bytes
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