| `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.                             |

		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",

    /**
     * Data transfer object representing process CPU statistics.
     */
    public static class ProcessCpuObj {
        /**
         * Default constructor.
         */
        public ProcessCpuObj() {
            // Default constructor
        }

        /** CPU usage percentage for the process. */
        public short percent;
        /** Total CPU time used by the process in milliseconds. */

A smaller CPU-only TensorFlow package is also available:

```
 pip install tensorflow-cpu
```

To update TensorFlow to the latest version, add the `--upgrade` flag to the
commands above.

*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.*

你的伺服器（群）是可以被「消耗／利用」的「資源」，你的程式會使用 CPU 的計算時間，以及可用的 RAM 記憶體。

你想要消耗／利用多少系統資源？直覺上可能會想「不要太多」，但實際上，你大概會希望在「不當機」的前提下「盡可能用多一點」。

如果你花錢租了 3 台伺服器，卻只用了它們少量的 RAM 與 CPU，那你可能是在「浪費金錢」💸、也「浪費伺服器電力」🌎 等。

在那種情況下，可能更好的是只用 2 台伺服器，並以更高的比例使用它們的資源（CPU、記憶體、磁碟、網路頻寬等）。

另一方面，如果你有 2 台伺服器，且你使用了它們「100% 的 CPU 與 RAM」，某個時刻一個行程會要求更多記憶體，伺服器就得用磁碟當作「記憶體」（這可能慢上數千倍），甚至「當機」。或是某個行程需要做計算時，必須等到 CPU 再度空閒。

    }

    /**
     * Gets the current system CPU usage percentage.
     *
     * @return The system CPU usage percentage.
     */
    public short currentSystemCpuPercent() {
        return getSystemCpuPercent();
    }

    /**
     * Gets the search engine CPU usage percentage.
     *
     * @return The search engine CPU usage percentage.
     */

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).

```bash
tensorflow/tools/ci_build/ci_build.sh CPU tensorflow/tools/ci_build/ci_sanity.sh
```

This will catch most license, Python coding style and BUILD file issues that
may exist in your changes.

#### Running unit tests

There are two ways to run TensorFlow unit tests.

1.  Using tools and libraries installed directly on your system.

    Refer to the

			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, "")
}

issues with Docker 1.9.1 can be found below.
  * CPU hardcapping will be enabled by default for containers with CPU limit set,
if supported by the kernel. You should either adjust your CPU limit, or set CPU
request only, if you want to avoid hardcapping. If the kernel does not support
CPU Quota, NodeStatus will contain a warning indicating that CPU Limits cannot
be enforced.