The function introduced here calculates a P-state range derived from
the statistics computed in the previous patch which will be used to
drive the HWP P-state range or (if HWP is not available) as basis for
some additional kernel-side frequency selection mechanism which will
choose a single P-state from the range. This is meant to provide a
variably low-pass filtering effect that will damp oscillations below a
frequency threshold that can be specified by device drivers via PM QoS
in order to achieve energy-efficient behavior in cases where the
system has an IO bottleneck.
Signed-off-by: Francisco Jerez <currojerez@xxxxxxxxxx>
---
drivers/cpufreq/intel_pstate.c | 157 +++++++++++++++++++++++++++++++++
1 file changed, 157 insertions(+)
diff --git a/drivers/cpufreq/intel_pstate.c b/drivers/cpufreq/intel_pstate.c
index 12ee350db2a9..cecadfec8bc1 100644
--- a/drivers/cpufreq/intel_pstate.c
+++ b/drivers/cpufreq/intel_pstate.c
@@ -207,17 +207,34 @@ struct vlp_status_sample {
int32_t realtime_avg;
};
+/**
+ * VLP controller state used for the estimation of the target P-state
+ * range, computed by get_vlp_target_range() from the heuristic status
+ * information defined above in struct vlp_status_sample.
+ */
+struct vlp_target_range {
+ unsigned int value[2];
+ int32_t p_base;
+};
+
/**
* struct vlp_data - VLP controller parameters and state.
* @sample_interval_ns: Update interval in ns.
* @sample_frequency_hz: Reciprocal of the update interval in Hz.
+ * @gain*: Response factor of the controller relative to each
+ * one of its linear input variables as fixed-point
+ * fraction.
*/
struct vlp_data {
s64 sample_interval_ns;
int32_t sample_frequency_hz;
+ int32_t gain_aggr;
+ int32_t gain_rt;
+ int32_t gain;
struct vlp_input_stats stats;
struct vlp_status_sample status;
+ struct vlp_target_range target;
};
/**
@@ -323,12 +340,18 @@ static struct cpudata **all_cpu_data;
/**
* struct vlp_params - VLP controller static configuration
* @sample_interval_ms: Update interval in ms.
+ * @setpoint_*_pml: Target CPU utilization at which the controller is
+ * expected to leave the current P-state untouched,
+ * as an integer per mille.
* @avg*_hz: Exponential averaging frequencies of the various
* low-pass filters as an integer in Hz.
*/
struct vlp_params {
int sample_interval_ms;
+ int setpoint_0_pml;
+ int setpoint_aggr_pml;
int avg_hz;
+ int realtime_gain_pml;
int debug;
};
@@ -362,7 +385,10 @@ struct pstate_funcs {
static struct pstate_funcs pstate_funcs __read_mostly;
static struct vlp_params vlp_params __read_mostly = {
.sample_interval_ms = 10,
+ .setpoint_0_pml = 900,
+ .setpoint_aggr_pml = 1500,
.avg_hz = 2,
+ .realtime_gain_pml = 12000,
.debug = 0,
};
@@ -1873,6 +1899,11 @@ static void intel_pstate_reset_vlp(struct cpudata *cpu)
vlp->sample_interval_ns = vlp_params.sample_interval_ms * NSEC_PER_MSEC;
vlp->sample_frequency_hz = max(1u, (uint32_t)MSEC_PER_SEC /
vlp_params.sample_interval_ms);
+ vlp->gain_rt = div_fp(cpu->pstate.max_pstate *
+ vlp_params.realtime_gain_pml, 1000);
+ vlp->gain_aggr = max(1, div_fp(1000, vlp_params.setpoint_aggr_pml));
+ vlp->gain = max(1, div_fp(1000, vlp_params.setpoint_0_pml));
+ vlp->target.p_base = 0;
vlp->stats.last_response_frequency_hz = vlp_params.avg_hz;
}
@@ -1996,6 +2027,132 @@ static const struct vlp_status_sample *get_vlp_status_sample(
return last_status;
}
+/**
+ * Calculate the target P-state range for the next update period.
+ * Uses a variably low-pass-filtering controller intended to improve
+ * energy efficiency when a CPU response frequency target is specified
+ * via PM QoS (e.g. under IO-bound conditions).
+ */
+static const struct vlp_target_range *get_vlp_target_range(struct cpudata *cpu)
+{
+ struct vlp_data *vlp = &cpu->vlp;
+ struct vlp_target_range *last_target = &vlp->target;
+
+ /*
+ * P-state limits in fixed-point as allowed by the policy.
+ */
+ const int32_t p0 = int_tofp(max(cpu->pstate.min_pstate,
+ cpu->min_perf_ratio));
+ const int32_t p1 = int_tofp(cpu->max_perf_ratio);
+
+ /*
+ * Observed average P-state during the sampling period. The
+ * conservative path (po_cons) uses the TSC increment as
+ * denominator which will give the minimum (arguably most
+ * energy-efficient) P-state able to accomplish the observed
+ * amount of work during the sampling period.
+ *
+ * The downside of that somewhat optimistic estimate is that
+ * it can give a biased result for intermittent
+ * latency-sensitive workloads, which may have to be completed
+ * in a short window of time for the system to achieve maximum
+ * performance, even if the average CPU utilization is low.
+ * For that reason the aggressive path (po_aggr) uses the
+ * MPERF increment as denominator, which is approximately
+ * optimal under the pessimistic assumption that the CPU work
+ * cannot be parallelized with any other dependent IO work
+ * that subsequently keeps the CPU idle (partly in C1+
+ * states).
+ */
+ const int32_t po_cons =
+ div_fp((cpu->sample.aperf << cpu->aperf_mperf_shift)
+ * cpu->pstate.max_pstate_physical,
+ cpu->sample.tsc);
+ const int32_t po_aggr =
+ div_fp((cpu->sample.aperf << cpu->aperf_mperf_shift)
+ * cpu->pstate.max_pstate_physical,
+ (cpu->sample.mperf << cpu->aperf_mperf_shift));
+
+ const struct vlp_status_sample *status =
+ get_vlp_status_sample(cpu, po_cons);
+
+ /* Calculate the target P-state. */
+ const int32_t p_tgt_cons = mul_fp(vlp->gain, po_cons);
+ const int32_t p_tgt_aggr = mul_fp(vlp->gain_aggr, po_aggr);
+ const int32_t p_tgt = max(p0, min(p1, max(p_tgt_cons, p_tgt_aggr)));
+
+ /* Calculate the realtime P-state target lower bound. */
+ const int32_t pm = int_tofp(cpu->pstate.max_pstate);
+ const int32_t p_tgt_rt = min(pm, mul_fp(vlp->gain_rt,
+ status->realtime_avg));
+
+ /*
+ * Low-pass filter the P-state estimate above by exponential
+ * averaging. For an oscillating workload (e.g. submitting
+ * work repeatedly to a device like a soundcard or GPU) this
+ * will approximate the minimum P-state that would be able to
+ * accomplish the observed amount of work during the averaging
+ * period, which is also the optimally energy-efficient one,
+ * under the assumptions that:
+ *
+ * - The power curve of the system is convex throughout the
+ * range of P-states allowed by the policy. I.e. energy
+ * efficiency is steadily decreasing with frequency past p0
+ * (which is typically close to the maximum-efficiency
+ * ratio). In practice for the lower range of P-states
+ * this may only be approximately true due to the
+ * interaction between different components of the system.
+ *
+ * - Parallelism constraints of the workload don't prevent it
+ * from achieving the same throughput at the lower P-state.
+ * This will happen in cases where the application is
+ * designed in a way that doesn't allow for dependent CPU
+ * and IO jobs to be pipelined, leading to alternating full
+ * and zero utilization of the CPU and IO device. This
+ * will give an average IO device utilization lower than
+ * 100% regardless of the CPU frequency, which should
+ * prevent the device driver from requesting a response
+ * frequency bound, so the filtered P-state calculated
+ * below won't have an influence on the controller
+ * response.
+ *
+ * - The period of the oscillating workload is significantly
+ * shorter than the time constant of the exponential
+ * average (1s / last_response_frequency_hz). Otherwise for
+ * more slowly oscillating workloads the controller
+ * response will roughly follow the oscillation, leading to
+ * decreased energy efficiency.
+ *
+ * - The behavior of the workload doesn't change
+ * qualitatively during the next update interval. This is
+ * only true in the steady state, and could possibly lead
+ * to a transitory period in which the controller response
+ * deviates from the most energy-efficient ratio until the
+ * workload reaches a steady state again.
+ */
+ const int32_t alpha = get_last_sample_avg_weight(
+ cpu, vlp->stats.last_response_frequency_hz);
+
+ last_target->p_base = p_tgt + mul_fp(alpha,
+ last_target->p_base - p_tgt);
+
+ /*
+ * Use the low-pass-filtered controller response for better
+ * energy efficiency unless we have reasons to believe that
+ * some of the optimality assumptions discussed above may not
+ * hold.
+ */
+ if ((status->value & VLP_BOTTLENECK_IO)) {
+ last_target->value[0] = rnd_fp(p0);
+ last_target->value[1] = rnd_fp(last_target->p_base);
+ } else {
+ last_target->value[0] = rnd_fp(p_tgt_rt);
+ last_target->value[1] = rnd_fp(p1);
+ }
+
+ return last_target;
+}
+
/**
* Collect some scheduling and PM statistics in response to an
* update_state() call.
--
2.22.1
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