scx_lavd::cpu_order

Struct EnergyModelOptimizer

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struct EnergyModelOptimizer<'a> {
    em: &'a EnergyModel,
    cpus_topological_order: Vec<usize>,
    pd_cpu_order: BTreeMap<usize, RefCell<Vec<usize>>>,
    tot_perf: usize,
    pdss_infos: RefCell<BTreeMap<usize, RefCell<HashSet<PDSetInfo<'a>>>>>,
    perf_pdsi: RefCell<BTreeMap<usize, PDSetInfo<'a>>>,
    perf_cpu_order: RefCell<BTreeMap<usize, PerfCpuOrder>>,
}

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§em: &'a EnergyModel§cpus_topological_order: Vec<usize>§pd_cpu_order: BTreeMap<usize, RefCell<Vec<usize>>>§tot_perf: usize§pdss_infos: RefCell<BTreeMap<usize, RefCell<HashSet<PDSetInfo<'a>>>>>§perf_pdsi: RefCell<BTreeMap<usize, PDSetInfo<'a>>>§perf_cpu_order: RefCell<BTreeMap<usize, PerfCpuOrder>>

Implementations§

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impl<'a> EnergyModelOptimizer<'a>

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fn new(em: &'a EnergyModel, cpus_pf: &'a Vec<CpuId>) -> EnergyModelOptimizer<'a>

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fn get_perf_cpu_order_table( em: &'a EnergyModel, cpus_pf: &'a Vec<CpuId>, ) -> BTreeMap<usize, PerfCpuOrder>

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fn get_fake_perf_cpu_order_table( cpus_pf: &'a Vec<CpuId>, cpus_ps: &'a Vec<CpuId>, ) -> BTreeMap<usize, PerfCpuOrder>

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fn fake_pco( tot_perf: usize, cpuids: &'a Vec<CpuId>, powersave: bool, ) -> PerfCpuOrder

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fn gen_perf_cpu_order_table(&'a self)

Generate the performance versus CPU preference order table based on the system’s CPU topology and energy model. The table consists of the following information (PerfCpuOrder):

  • PerfCpuOrder::perf_cap: The upper bound of the performance capacity covered by this tuple.

  • PerfCpuOrder::cpus_perf: Primary CPUs to be used is ordered by preference.

  • PerfCpuOrder::cpus_ovrflw: When the system load goes beyond @perf_cap, the list of CPUs to be used is ordered by preference.

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fn assign_cpu_vids(&'a self)

Generate a CPU order table for each performance range.

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fn sort_cpus_by_topological_order(&'a self, cpus: &Vec<usize>) -> Vec<usize>

Sort the CPU IDs by topological order (@self.cpus_topological_order).

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fn gen_perf_pds_table(&'a self)

Generate a table of performance vs. performance domain sets (@self.perf_pdss) from all the possible performance domain & state combinations (@self.pdss_infos).

An example result is as follows: PERF: [, 300] pd:id: 0 – cpu_vid: 0 pd:id: 0 – cpu_vid: 1 PERF: [, 1138] pd:id: 0 – cpu_vid: 0 pd:id: 0 – cpu_vid: 1 pd:id: 1 – cpu_vid: 0 pd:id: 1 – cpu_vid: 1 PERF: [, 3386] pd:id: 1 – cpu_vid: 0 pd:id: 1 – cpu_vid: 1 pd:id: 1 – cpu_vid: 2 pd:id: 2 – cpu_vid: 0 pd:id: 2 – cpu_vid: 1 PERF: [, 3977] pd:id: 0 – cpu_vid: 0 pd:id: 1 – cpu_vid: 0 pd:id: 1 – cpu_vid: 1 pd:id: 1 – cpu_vid: 2 pd:id: 2 – cpu_vid: 0 pd:id: 2 – cpu_vid: 1 PERF: [, 4508] pd:id: 0 – cpu_vid: 0 pd:id: 0 – cpu_vid: 1 pd:id: 1 – cpu_vid: 0 pd:id: 1 – cpu_vid: 1 pd:id: 1 – cpu_vid: 2 pd:id: 2 – cpu_vid: 0 pd:id: 2 – cpu_vid: 1 PERF: [, 5627] pd:id: 0 – cpu_vid: 0 pd:id: 0 – cpu_vid: 1 pd:id: 1 – cpu_vid: 0 pd:id: 1 – cpu_vid: 1 pd:id: 1 – cpu_vid: 2 pd:id: 2 – cpu_vid: 0 pd:id: 2 – cpu_vid: 1 pd:id: 3 – cpu_vid: 0

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fn find_perf_pds_for( &'a self, util: f32, base: Option<&PDSetInfo<'a>>, ) -> Option<PDSetInfo<'a>>

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fn gen_all_pds_combinations(&'a self)

Generate all possible performance domain & state combinations, @self.pdss_infos. Each combination represents a set of performance domains (and their corresponding performance states) that achieve the requested performance with minimal power consumption.

We assume a ‘reasonable load balancer,’ so the CPU utilization of all the involved CPUs is similar.

An example result is as follows:

PERF: [_, 5135]
    perf: 5135 -- power: 5475348
        pd:id: 0 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 2
        pd:id: 2 -- cpu_vid: 0
        pd:id: 2 -- cpu_vid: 1
        pd:id: 3 -- cpu_vid: 0
PERF: [_, 5187]
    perf: 5187 -- power: 4844969
        pd:id: 0 -- cpu_vid: 0
        pd:id: 0 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 2
        pd:id: 2 -- cpu_vid: 0
        pd:id: 2 -- cpu_vid: 1
        pd:id: 3 -- cpu_vid: 0
PERF: [_, 5195]
    perf: 5195 -- power: 5924606
        pd:id: 1 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 2
        pd:id: 2 -- cpu_vid: 0
        pd:id: 2 -- cpu_vid: 1
        pd:id: 3 -- cpu_vid: 0
PERF: [_, 5217]
    perf: 5217 -- power: 4894911
        pd:id: 0 -- cpu_vid: 0
        pd:id: 0 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 2
        pd:id: 2 -- cpu_vid: 0
        pd:id: 2 -- cpu_vid: 1
        pd:id: 3 -- cpu_vid: 0
PERF: [_, 5225]
    perf: 5225 -- power: 5665770
        pd:id: 0 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 2
        pd:id: 2 -- cpu_vid: 0
        pd:id: 2 -- cpu_vid: 1
        pd:id: 3 -- cpu_vid: 0
PERF: [_, 5316]
    perf: 5316 -- power: 5860568
        pd:id: 0 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 0
        pd:id: 1 -- cpu_vid: 1
        pd:id: 1 -- cpu_vid: 2
        pd:id: 2 -- cpu_vid: 0
        pd:id: 2 -- cpu_vid: 1
        pd:id: 3 -- cpu_vid: 0
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fn gen_perf_cpuset_table_range(&'a self, low: isize, high: isize)

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fn gen_pds_combinations(&'a self, util: f32) -> Vec<PDSetInfo<'a>>

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fn insert_pds_combinations(&self, new_pdsi_vec: &Vec<PDSetInfo<'a>>) -> bool

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fn gen_pds_set(&self, util: f32) -> Vec<PDS<'_>>

Get a vector of (performance domain, performance state) to achieve the given CPU utilization, @util.

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fn expand_pds_set(&self, pds_set: &mut Vec<PDS<'_>>)

Expand a PDS vector such that a performance domain with X CPUs has N elements in the vector. This is purely for generating combinations easy.

Trait Implementations§

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impl<'a> Debug for EnergyModelOptimizer<'a>

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