services/surfaceflinger/Scheduler/VSyncPredictor.cpp - android_frameworks_native - Gitiles

 /*
  * Copyright 2019 The Android Open Source Project
  *
  * Licensed under the Apache License, Version 2.0 (the "License");
  * you may not use this file except in compliance with the License.
  * You may obtain a copy of the License at
  *
  *      http://www.apache.org/licenses/LICENSE-2.0
  *
  * Unless required by applicable law or agreed to in writing, software
  * distributed under the License is distributed on an "AS IS" BASIS,
  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  * See the License for the specific language governing permissions and
  * limitations under the License.
  */

 #define ATRACE_TAG ATRACE_TAG_GRAPHICS
 //#define LOG_NDEBUG 0
 #include "VSyncPredictor.h"
 #include <android-base/logging.h>
 #include <cutils/compiler.h>
 #include <utils/Log.h>
 #include <utils/Trace.h>
 #include <algorithm>
 #include <chrono>
 #include <sstream>
 #include "SchedulerUtils.h"

 namespace android::scheduler {
 static auto constexpr kNeedsSamplesTag = "SamplesRequested";
 static auto constexpr kMaxPercent = 100u;

 VSyncPredictor::~VSyncPredictor() = default;

 VSyncPredictor::VSyncPredictor(nsecs_t idealPeriod, size_t historySize,
                                size_t minimumSamplesForPrediction, uint32_t outlierTolerancePercent)
       : kHistorySize(historySize),
         kMinimumSamplesForPrediction(minimumSamplesForPrediction),
         kOutlierTolerancePercent(std::min(outlierTolerancePercent, kMaxPercent)),
         mIdealPeriod(idealPeriod) {
     mRateMap[mIdealPeriod] = {idealPeriod, 0};
 }

 inline size_t VSyncPredictor::next(int i) const {
     return (i + 1) % timestamps.size();
 }

 bool VSyncPredictor::validate(nsecs_t timestamp) const {
     if (lastTimestampIndex < 0 || timestamps.empty()) {
         return true;
     }

     auto const aValidTimestamp = timestamps[lastTimestampIndex];
     auto const percent = (timestamp - aValidTimestamp) % mIdealPeriod * kMaxPercent / mIdealPeriod;
     return percent < kOutlierTolerancePercent || percent > (kMaxPercent - kOutlierTolerancePercent);
 }

 nsecs_t VSyncPredictor::currentPeriod() const {
     std::lock_guard<std::mutex> lk(mMutex);
     return std::get<0>(mRateMap.find(mIdealPeriod)->second);
 }

 void VSyncPredictor::addVsyncTimestamp(nsecs_t timestamp) {
     std::lock_guard<std::mutex> lk(mMutex);

     if (!validate(timestamp)) {
         ALOGW("timestamp was too far off the last known timestamp");
         return;
     }

     if (timestamps.size() != kHistorySize) {
         timestamps.push_back(timestamp);
         lastTimestampIndex = next(lastTimestampIndex);
     } else {
         lastTimestampIndex = next(lastTimestampIndex);
         timestamps[lastTimestampIndex] = timestamp;
     }

     if (timestamps.size() < kMinimumSamplesForPrediction) {
         mRateMap[mIdealPeriod] = {mIdealPeriod, 0};
         return;
     }

     // This is a 'simple linear regression' calculation of Y over X, with Y being the
     // vsync timestamps, and X being the ordinal of vsync count.
     // The calculated slope is the vsync period.
     // Formula for reference:
     // Sigma_i: means sum over all timestamps.
     // mean(variable): statistical mean of variable.
     // X: snapped ordinal of the timestamp
     // Y: vsync timestamp
     //
     //         Sigma_i( (X_i - mean(X)) * (Y_i - mean(Y) )
     // slope = -------------------------------------------
     //         Sigma_i ( X_i - mean(X) ) ^ 2
     //
     // intercept = mean(Y) - slope * mean(X)
     //
     std::vector<nsecs_t> vsyncTS(timestamps.size());
     std::vector<nsecs_t> ordinals(timestamps.size());

     // normalizing to the oldest timestamp cuts down on error in calculating the intercept.
     auto const oldest_ts = *std::min_element(timestamps.begin(), timestamps.end());
     auto it = mRateMap.find(mIdealPeriod);
     auto const currentPeriod = std::get<0>(it->second);
     // TODO (b/144707443): its important that there's some precision in the mean of the ordinals
     //                     for the intercept calculation, so scale the ordinals by 10 to continue
     //                     fixed point calculation. Explore expanding
     //                     scheduler::utils::calculate_mean to have a fixed point fractional part.
     static constexpr int kScalingFactor = 10;

     for (auto i = 0u; i < timestamps.size(); i++) {
         vsyncTS[i] = timestamps[i] - oldest_ts;
         ordinals[i] = ((vsyncTS[i] + (currentPeriod / 2)) / currentPeriod) * kScalingFactor;
     }

     auto meanTS = scheduler::calculate_mean(vsyncTS);
     auto meanOrdinal = scheduler::calculate_mean(ordinals);
     for (auto i = 0; i < vsyncTS.size(); i++) {
         vsyncTS[i] -= meanTS;
         ordinals[i] -= meanOrdinal;
     }

     auto top = 0ll;
     auto bottom = 0ll;
     for (auto i = 0; i < vsyncTS.size(); i++) {
         top += vsyncTS[i] * ordinals[i];
         bottom += ordinals[i] * ordinals[i];
     }

     if (CC_UNLIKELY(bottom == 0)) {
         it->second = {mIdealPeriod, 0};
         return;
     }

     nsecs_t const anticipatedPeriod = top / bottom * kScalingFactor;
     nsecs_t const intercept = meanTS - (anticipatedPeriod * meanOrdinal / kScalingFactor);

     it->second = {anticipatedPeriod, intercept};

     ALOGV("model update ts: %" PRId64 " slope: %" PRId64 " intercept: %" PRId64, timestamp,
           anticipatedPeriod, intercept);
 }

 nsecs_t VSyncPredictor::nextAnticipatedVSyncTimeFrom(nsecs_t timePoint) const {
     std::lock_guard<std::mutex> lk(mMutex);

     auto const [slope, intercept] = getVSyncPredictionModel(lk);

     if (timestamps.empty()) {
         auto const knownTimestamp = mKnownTimestamp ? *mKnownTimestamp : timePoint;
         auto const numPeriodsOut = ((timePoint - knownTimestamp) / mIdealPeriod) + 1;
         return knownTimestamp + numPeriodsOut * mIdealPeriod;
     }

     auto const oldest = *std::min_element(timestamps.begin(), timestamps.end());

     // See b/145667109, the ordinal calculation must take into account the intercept.
     auto const zeroPoint = oldest + intercept;
     auto const ordinalRequest = (timePoint - zeroPoint + slope) / slope;
     auto const prediction = (ordinalRequest * slope) + intercept + oldest;

     auto const printer = [&, slope = slope, intercept = intercept] {
         std::stringstream str;
         str << "prediction made from: " << timePoint << "prediction: " << prediction << " (+"
             << prediction - timePoint << ") slope: " << slope << " intercept: " << intercept
             << "oldestTS: " << oldest << " ordinal: " << ordinalRequest;
         return str.str();
     };

     ALOGV("%s", printer().c_str());
     LOG_ALWAYS_FATAL_IF(prediction < timePoint, "VSyncPredictor: model miscalculation: %s",
                         printer().c_str());

     return prediction;
 }

 std::tuple<nsecs_t, nsecs_t> VSyncPredictor::getVSyncPredictionModel() const {
     std::lock_guard<std::mutex> lk(mMutex);
     return VSyncPredictor::getVSyncPredictionModel(lk);
 }

 std::tuple<nsecs_t, nsecs_t> VSyncPredictor::getVSyncPredictionModel(
         std::lock_guard<std::mutex> const&) const {
     return mRateMap.find(mIdealPeriod)->second;
 }

 void VSyncPredictor::setPeriod(nsecs_t period) {
     ATRACE_CALL();

     std::lock_guard<std::mutex> lk(mMutex);
     static constexpr size_t kSizeLimit = 30;
     if (CC_UNLIKELY(mRateMap.size() == kSizeLimit)) {
         mRateMap.erase(mRateMap.begin());
     }

     mIdealPeriod = period;
     if (mRateMap.find(period) == mRateMap.end()) {
         mRateMap[mIdealPeriod] = {period, 0};
     }

     if (!timestamps.empty()) {
         mKnownTimestamp = *std::max_element(timestamps.begin(), timestamps.end());
         timestamps.clear();
         lastTimestampIndex = 0;
     }
 }

 bool VSyncPredictor::needsMoreSamples(nsecs_t now) const {
     using namespace std::literals::chrono_literals;
     std::lock_guard<std::mutex> lk(mMutex);
     bool needsMoreSamples = true;
     if (timestamps.size() >= kMinimumSamplesForPrediction) {
         nsecs_t constexpr aLongTime =
                 std::chrono::duration_cast<std::chrono::nanoseconds>(500ms).count();
         if (!(lastTimestampIndex < 0 || timestamps.empty())) {
             auto const lastTimestamp = timestamps[lastTimestampIndex];
             needsMoreSamples = !((lastTimestamp + aLongTime) > now);
         }
     }

     ATRACE_INT(kNeedsSamplesTag, needsMoreSamples);
     return needsMoreSamples;
 }

 } // namespace android::scheduler
	/*
	* Copyright 2019 The Android Open Source Project
	*
	* Licensed under the Apache License, Version 2.0 (the "License");
	* you may not use this file except in compliance with the License.
	* You may obtain a copy of the License at
	*
	* http://www.apache.org/licenses/LICENSE-2.0
	*
	* Unless required by applicable law or agreed to in writing, software
	* distributed under the License is distributed on an "AS IS" BASIS,
	* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	* See the License for the specific language governing permissions and
	* limitations under the License.
	*/

	#define ATRACE_TAG ATRACE_TAG_GRAPHICS
	//#define LOG_NDEBUG 0
	#include "VSyncPredictor.h"
	#include <android-base/logging.h>
	#include <cutils/compiler.h>
	#include <utils/Log.h>
	#include <utils/Trace.h>
	#include <algorithm>
	#include <chrono>
	#include <sstream>
	#include "SchedulerUtils.h"

	namespace android::scheduler {
	static auto constexpr kNeedsSamplesTag = "SamplesRequested";
	static auto constexpr kMaxPercent = 100u;

	VSyncPredictor::~VSyncPredictor() = default;

	VSyncPredictor::VSyncPredictor(nsecs_t idealPeriod, size_t historySize,
	size_t minimumSamplesForPrediction, uint32_t outlierTolerancePercent)
	: kHistorySize(historySize),
	kMinimumSamplesForPrediction(minimumSamplesForPrediction),
	kOutlierTolerancePercent(std::min(outlierTolerancePercent, kMaxPercent)),
	mIdealPeriod(idealPeriod) {
	mRateMap[mIdealPeriod] = {idealPeriod, 0};
	}

	inline size_t VSyncPredictor::next(int i) const {
	return (i + 1) % timestamps.size();
	}

	bool VSyncPredictor::validate(nsecs_t timestamp) const {
	if (lastTimestampIndex < 0 \|\| timestamps.empty()) {
	return true;
	}

	auto const aValidTimestamp = timestamps[lastTimestampIndex];
	auto const percent = (timestamp - aValidTimestamp) % mIdealPeriod * kMaxPercent / mIdealPeriod;
	return percent < kOutlierTolerancePercent \|\| percent > (kMaxPercent - kOutlierTolerancePercent);
	}

	nsecs_t VSyncPredictor::currentPeriod() const {
	std::lock_guard<std::mutex> lk(mMutex);
	return std::get<0>(mRateMap.find(mIdealPeriod)->second);
	}

	void VSyncPredictor::addVsyncTimestamp(nsecs_t timestamp) {
	std::lock_guard<std::mutex> lk(mMutex);

	if (!validate(timestamp)) {
	ALOGW("timestamp was too far off the last known timestamp");
	return;
	}

	if (timestamps.size() != kHistorySize) {
	timestamps.push_back(timestamp);
	lastTimestampIndex = next(lastTimestampIndex);
	} else {
	lastTimestampIndex = next(lastTimestampIndex);
	timestamps[lastTimestampIndex] = timestamp;
	}

	if (timestamps.size() < kMinimumSamplesForPrediction) {
	mRateMap[mIdealPeriod] = {mIdealPeriod, 0};
	return;
	}

	// This is a 'simple linear regression' calculation of Y over X, with Y being the
	// vsync timestamps, and X being the ordinal of vsync count.
	// The calculated slope is the vsync period.
	// Formula for reference:
	// Sigma_i: means sum over all timestamps.
	// mean(variable): statistical mean of variable.
	// X: snapped ordinal of the timestamp
	// Y: vsync timestamp
	//
	// Sigma_i( (X_i - mean(X)) * (Y_i - mean(Y) )
	// slope = -------------------------------------------
	// Sigma_i ( X_i - mean(X) ) ^ 2
	//
	// intercept = mean(Y) - slope * mean(X)
	//
	std::vector<nsecs_t> vsyncTS(timestamps.size());
	std::vector<nsecs_t> ordinals(timestamps.size());

	// normalizing to the oldest timestamp cuts down on error in calculating the intercept.
	auto const oldest_ts = *std::min_element(timestamps.begin(), timestamps.end());
	auto it = mRateMap.find(mIdealPeriod);
	auto const currentPeriod = std::get<0>(it->second);
	// TODO (b/144707443): its important that there's some precision in the mean of the ordinals
	// for the intercept calculation, so scale the ordinals by 10 to continue
	// fixed point calculation. Explore expanding
	// scheduler::utils::calculate_mean to have a fixed point fractional part.
	static constexpr int kScalingFactor = 10;

	for (auto i = 0u; i < timestamps.size(); i++) {
	vsyncTS[i] = timestamps[i] - oldest_ts;
	ordinals[i] = ((vsyncTS[i] + (currentPeriod / 2)) / currentPeriod) * kScalingFactor;
	}

	auto meanTS = scheduler::calculate_mean(vsyncTS);
	auto meanOrdinal = scheduler::calculate_mean(ordinals);
	for (auto i = 0; i < vsyncTS.size(); i++) {
	vsyncTS[i] -= meanTS;
	ordinals[i] -= meanOrdinal;
	}

	auto top = 0ll;
	auto bottom = 0ll;
	for (auto i = 0; i < vsyncTS.size(); i++) {
	top += vsyncTS[i] * ordinals[i];
	bottom += ordinals[i] * ordinals[i];
	}

	if (CC_UNLIKELY(bottom == 0)) {
	it->second = {mIdealPeriod, 0};
	return;
	}

	nsecs_t const anticipatedPeriod = top / bottom * kScalingFactor;
	nsecs_t const intercept = meanTS - (anticipatedPeriod * meanOrdinal / kScalingFactor);

	it->second = {anticipatedPeriod, intercept};

	ALOGV("model update ts: %" PRId64 " slope: %" PRId64 " intercept: %" PRId64, timestamp,
	anticipatedPeriod, intercept);
	}

	nsecs_t VSyncPredictor::nextAnticipatedVSyncTimeFrom(nsecs_t timePoint) const {
	std::lock_guard<std::mutex> lk(mMutex);

	auto const [slope, intercept] = getVSyncPredictionModel(lk);

	if (timestamps.empty()) {
	auto const knownTimestamp = mKnownTimestamp ? *mKnownTimestamp : timePoint;
	auto const numPeriodsOut = ((timePoint - knownTimestamp) / mIdealPeriod) + 1;
	return knownTimestamp + numPeriodsOut * mIdealPeriod;
	}

	auto const oldest = *std::min_element(timestamps.begin(), timestamps.end());

	// See b/145667109, the ordinal calculation must take into account the intercept.
	auto const zeroPoint = oldest + intercept;
	auto const ordinalRequest = (timePoint - zeroPoint + slope) / slope;
	auto const prediction = (ordinalRequest * slope) + intercept + oldest;

	auto const printer = [&, slope = slope, intercept = intercept] {
	std::stringstream str;
	str << "prediction made from: " << timePoint << "prediction: " << prediction << " (+"
	<< prediction - timePoint << ") slope: " << slope << " intercept: " << intercept
	<< "oldestTS: " << oldest << " ordinal: " << ordinalRequest;
	return str.str();
	};

	ALOGV("%s", printer().c_str());
	LOG_ALWAYS_FATAL_IF(prediction < timePoint, "VSyncPredictor: model miscalculation: %s",
	printer().c_str());

	return prediction;
	}

	std::tuple<nsecs_t, nsecs_t> VSyncPredictor::getVSyncPredictionModel() const {
	std::lock_guard<std::mutex> lk(mMutex);
	return VSyncPredictor::getVSyncPredictionModel(lk);
	}

	std::tuple<nsecs_t, nsecs_t> VSyncPredictor::getVSyncPredictionModel(
	std::lock_guard<std::mutex> const&) const {
	return mRateMap.find(mIdealPeriod)->second;
	}

	void VSyncPredictor::setPeriod(nsecs_t period) {
	ATRACE_CALL();

	std::lock_guard<std::mutex> lk(mMutex);
	static constexpr size_t kSizeLimit = 30;
	if (CC_UNLIKELY(mRateMap.size() == kSizeLimit)) {
	mRateMap.erase(mRateMap.begin());
	}

	mIdealPeriod = period;
	if (mRateMap.find(period) == mRateMap.end()) {
	mRateMap[mIdealPeriod] = {period, 0};
	}

	if (!timestamps.empty()) {
	mKnownTimestamp = *std::max_element(timestamps.begin(), timestamps.end());
	timestamps.clear();
	lastTimestampIndex = 0;
	}
	}

	bool VSyncPredictor::needsMoreSamples(nsecs_t now) const {
	using namespace std::literals::chrono_literals;
	std::lock_guard<std::mutex> lk(mMutex);
	bool needsMoreSamples = true;
	if (timestamps.size() >= kMinimumSamplesForPrediction) {
	nsecs_t constexpr aLongTime =
	std::chrono::duration_cast<std::chrono::nanoseconds>(500ms).count();
	if (!(lastTimestampIndex < 0 \|\| timestamps.empty())) {
	auto const lastTimestamp = timestamps[lastTimestampIndex];
	needsMoreSamples = !((lastTimestamp + aLongTime) > now);
	}
	}

	ATRACE_INT(kNeedsSamplesTag, needsMoreSamples);
	return needsMoreSamples;
	}

	} // namespace android::scheduler