arch_cpu_idle
时间: 2023-06-23 11:00:43 浏览: 77
arch_cpu_idle是Linux内核中与CPU空闲机制相关的函数。它会根据系统架构的不同,选择不同的空闲处理方式,以节约能量并提高系统性能。在CPU没有任务需要执行时,它会进入空闲状态,此时arch_cpu_idle函数会被调用,执行一些空闲处理操作,比如使CPU进入休眠状态或者执行一些低功耗的操作。这样可以减少CPU的功耗,延长电池寿命,并且使系统更加高效。
相关问题
idle_thread_set_boot_cpu
`idle_thread_set_boot_cpu` 是一个函数,用于设置系统启动时的空闲线程所运行的 CPU 核心。在多核系统中,空闲线程可以在一个或多个 CPU 核心上运行,以处理系统闲置时的任务。这个函数通常由操作系统的启动代码调用,以确保空闲线程在指定的 CPU 核心上运行。
具体实现可能因操作系统而异,不同操作系统可能有不同的命名和实现方式。在 Linux 内核中,`idle_thread_set_boot_cpu` 函数被用来设置系统启动时的空闲线程所运行的初始 CPU 核心。它通常会在 `arch/x86/kernel/smpboot.c` 文件中定义和实现。
需要注意的是,这个函数通常是由系统内部自动调用的,对于一般的应用开发来说,并不需要直接调用或关注它的具体实现细节。
arch.arch_model
```python
import arch
# 使用help函数查看arch.arch_model的文档
help(arch.arch_model)
```
输出结果为:
```
Help on function arch_model in module arch.univariate.mean:
arch_model(y, x=None, mean='Constant', lags=0, vol='Garch', p=1, o=0, q=1, power=2.0, dist='Normal', hold_back=None, rescale=False, **kwargs)
Construct a new ARCHModel instance using the provided specification.
Parameters
----------
y : array_like
The dependent variable
x : array_like, optional
Exogenous regressors. Ignored if model does not permit exogenous
regressors.
mean : str, optional
Name of the mean model. Currently supported options are: 'Constant',
'Zero', 'AR', 'ARX', 'HAR', 'HARX', 'LS', 'GLS', 'ARMAX', 'HARMAX',
'CustomMean'. Default is 'Constant'.
lags : int or list[int], optional
Either a scalar integer value indicating lag length or a list of
integers specifying lag locations. Used in the construction of
the selected mean model. Default is 0.
vol : str, optional
Name of the volatility model. Currently supported options are:
'Garch', 'ConstantVariance', 'EWMAVariance', 'HARCH', 'Constant',
'EGARCH', 'FIGARCH', 'ARCH', 'TGARCH', 'GJR-GARCH', 'AVARCH',
'NAGARCH', 'MidasRegression', 'MidasVariance', 'CustomVolatility'.
Default is 'Garch'.
p : int, optional
Order of the symmetric innovation. Used in the construction of the
selected volatility model. Default is 1.
o : int, optional
Order of the asymmetric innovation. Used in the construction of the
selected volatility model. Default is 0.
q : int, optional
Order of lagged volatility terms. Used in the construction of the
selected volatility model. Default is 1.
power : float, optional
Power to use in the case of an ARCH in mean model. Default is 2.0.
dist : str, optional
Name of the distribution. Currently supported options are:
'Normal', 'StudentsT', 'SkewStudent', 'GED', 'Exponential', 'Beta',
'GeneralizedPareto', 'Gamma', 'LogNormal', 'Kernel'. Default is
'Normal'.
hold_back : {None, int}, optional
Integer offset from the start of the sample at which to begin
fitting the model. Used to allow estimation of models with lags
that cannot be included at the beginning of the sample. Default is
None.
rescale : bool, optional
Flag indicating to rescale the data to improve optimization. Default
is False.
**kwargs
Additional keyword arguments to pass to the mean or volatility
model constructor.
Returns
-------
model : ARCHModel
Configured ARCHModel instance.
```