Lines Matching refs:energy
9 the impact of its decisions on the energy consumed by CPUs. EAS relies on an
10 Energy Model (EM) of the CPUs to select an energy efficient CPU for each task,
20 because this is where the potential for saving energy through scheduling is
25 please refer to its documentation (see Documentation/power/energy-model.rst).
32 - energy = [joule] (resource like a battery on powered devices)
33 - power = energy/time = [joule/second] = [watt]
35 The goal of EAS is to minimize energy, while still getting the job done. That
44 energy [J]
50 scheduler. This alternative considers two objectives: energy-efficiency and
54 implications of its decisions rather than blindly applying energy-saving
62 that is predicted to yield the best energy consumption without harming the
65 and their respective energy costs.
79 energy trade-offs. The capacity of CPUs is provided via arch-specific code
84 per 'performance domain' in the system (see Documentation/power/energy-model.rst
132 platform and the PELT signals to choose an energy-efficient target CPU during
138 save energy compared to leaving it on prev_cpu, i.e. the CPU where the task ran
142 energy consumed by the system if the waking task was migrated. compute_energy()
145 which computes the expected energy consumption of each performance domain for
148 An example of energy-optimized task placement decision is detailed below.
186 CPU1 and CPU3. Then it will estimate the energy of the system if P was
187 placed on either of them, and check if that would save some energy
246 From these calculations, the Case 1 has the lowest total energy. So CPU 1
247 is be the best candidate from an energy-efficiency standpoint.
251 necessarily more energy-efficient than big CPUs. For some systems, the high OPPs
252 of the little CPUs can be less energy-efficient than the lowest OPPs of the
255 of executing on the big side in order to save energy, even though it would fit
258 And even in the case where all OPPs of the big CPUs are less energy-efficient
260 specific conditions, save energy. Indeed, placing a task on a little CPU can
265 which will keep running at a lower OPP. So, when considering the total energy
284 much that can be done by the scheduler to save energy without severly harming
289 the most energy efficient CPUs of the system more than the others if that can be
291 it from breaking the energy-efficient task placement found by EAS. It is safe to
346 energy. So, your platform must provide power cost tables to the EM framework in
348 independent EM framework in Documentation/power/energy-model.rst.
353 EAS uses the EM to make a forecasting decision on energy usage and thus it is
365 The energy-aware wake-up algorithm has a complexity of:
394 in order to estimate their energy consumption. To do so, it is assumed that OPPs
403 frequency requests and energy predictions.
424 multithreaded hardware to save energy. EAS considers threads as independent
425 CPUs, which can actually be counter-productive for both performance and energy.