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368 lines
14 KiB
368 lines
14 KiB
/*
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* Copyright 2019 The Android Open Source Project
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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// TODO(b/129481165): remove the #pragma below and fix conversion issues
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#pragma clang diagnostic push
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#pragma clang diagnostic ignored "-Wextra"
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#define ATRACE_TAG ATRACE_TAG_GRAPHICS
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//#define LOG_NDEBUG 0
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#include "VSyncPredictor.h"
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#include <android-base/logging.h>
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#include <android-base/stringprintf.h>
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#include <cutils/compiler.h>
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#include <cutils/properties.h>
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#include <utils/Log.h>
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#include <utils/Trace.h>
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#include <algorithm>
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#include <chrono>
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#include <sstream>
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#include "RefreshRateConfigs.h"
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#undef LOG_TAG
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#define LOG_TAG "VSyncPredictor"
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namespace android::scheduler {
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using base::StringAppendF;
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static auto constexpr kMaxPercent = 100u;
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VSyncPredictor::~VSyncPredictor() = default;
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VSyncPredictor::VSyncPredictor(nsecs_t idealPeriod, size_t historySize,
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size_t minimumSamplesForPrediction, uint32_t outlierTolerancePercent)
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: mTraceOn(property_get_bool("debug.sf.vsp_trace", true)),
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kHistorySize(historySize),
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kMinimumSamplesForPrediction(minimumSamplesForPrediction),
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kOutlierTolerancePercent(std::min(outlierTolerancePercent, kMaxPercent)),
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mIdealPeriod(idealPeriod) {
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resetModel();
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}
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inline void VSyncPredictor::traceInt64If(const char* name, int64_t value) const {
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if (CC_UNLIKELY(mTraceOn)) {
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ATRACE_INT64(name, value);
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}
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}
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inline size_t VSyncPredictor::next(size_t i) const {
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return (i + 1) % mTimestamps.size();
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}
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bool VSyncPredictor::validate(nsecs_t timestamp) const {
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if (mLastTimestampIndex < 0 || mTimestamps.empty()) {
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return true;
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}
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auto const aValidTimestamp = mTimestamps[mLastTimestampIndex];
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auto const percent = (timestamp - aValidTimestamp) % mIdealPeriod * kMaxPercent / mIdealPeriod;
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if (percent >= kOutlierTolerancePercent &&
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percent <= (kMaxPercent - kOutlierTolerancePercent)) {
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return false;
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}
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const auto iter = std::min_element(mTimestamps.begin(), mTimestamps.end(),
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[timestamp](nsecs_t a, nsecs_t b) {
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return std::abs(timestamp - a) < std::abs(timestamp - b);
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});
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const auto distancePercent = std::abs(*iter - timestamp) * kMaxPercent / mIdealPeriod;
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if (distancePercent < kOutlierTolerancePercent) {
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// duplicate timestamp
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return false;
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}
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return true;
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}
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nsecs_t VSyncPredictor::currentPeriod() const {
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std::lock_guard lock(mMutex);
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return mRateMap.find(mIdealPeriod)->second.slope;
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}
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bool VSyncPredictor::addVsyncTimestamp(nsecs_t timestamp) {
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std::lock_guard lock(mMutex);
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if (!validate(timestamp)) {
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// VSR could elect to ignore the incongruent timestamp or resetModel(). If ts is ignored,
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// don't insert this ts into mTimestamps ringbuffer. If we are still
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// in the learning phase we should just clear all timestamps and start
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// over.
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if (mTimestamps.size() < kMinimumSamplesForPrediction) {
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// Add the timestamp to mTimestamps before clearing it so we could
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// update mKnownTimestamp based on the new timestamp.
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mTimestamps.push_back(timestamp);
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clearTimestamps();
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} else if (!mTimestamps.empty()) {
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mKnownTimestamp =
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std::max(timestamp, *std::max_element(mTimestamps.begin(), mTimestamps.end()));
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} else {
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mKnownTimestamp = timestamp;
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}
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return false;
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}
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if (mTimestamps.size() != kHistorySize) {
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mTimestamps.push_back(timestamp);
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mLastTimestampIndex = next(mLastTimestampIndex);
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} else {
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mLastTimestampIndex = next(mLastTimestampIndex);
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mTimestamps[mLastTimestampIndex] = timestamp;
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}
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if (mTimestamps.size() < kMinimumSamplesForPrediction) {
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mRateMap[mIdealPeriod] = {mIdealPeriod, 0};
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return true;
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}
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// This is a 'simple linear regression' calculation of Y over X, with Y being the
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// vsync timestamps, and X being the ordinal of vsync count.
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// The calculated slope is the vsync period.
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// Formula for reference:
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// Sigma_i: means sum over all timestamps.
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// mean(variable): statistical mean of variable.
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// X: snapped ordinal of the timestamp
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// Y: vsync timestamp
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//
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// Sigma_i( (X_i - mean(X)) * (Y_i - mean(Y) )
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// slope = -------------------------------------------
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// Sigma_i ( X_i - mean(X) ) ^ 2
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//
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// intercept = mean(Y) - slope * mean(X)
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//
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std::vector<nsecs_t> vsyncTS(mTimestamps.size());
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std::vector<nsecs_t> ordinals(mTimestamps.size());
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// normalizing to the oldest timestamp cuts down on error in calculating the intercept.
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auto const oldest_ts = *std::min_element(mTimestamps.begin(), mTimestamps.end());
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auto it = mRateMap.find(mIdealPeriod);
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auto const currentPeriod = it->second.slope;
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// TODO (b/144707443): its important that there's some precision in the mean of the ordinals
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// for the intercept calculation, so scale the ordinals by 1000 to continue
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// fixed point calculation. Explore expanding
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// scheduler::utils::calculate_mean to have a fixed point fractional part.
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static constexpr int64_t kScalingFactor = 1000;
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for (auto i = 0u; i < mTimestamps.size(); i++) {
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traceInt64If("VSP-ts", mTimestamps[i]);
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vsyncTS[i] = mTimestamps[i] - oldest_ts;
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ordinals[i] = ((vsyncTS[i] + (currentPeriod / 2)) / currentPeriod) * kScalingFactor;
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}
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auto meanTS = scheduler::calculate_mean(vsyncTS);
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auto meanOrdinal = scheduler::calculate_mean(ordinals);
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for (size_t i = 0; i < vsyncTS.size(); i++) {
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vsyncTS[i] -= meanTS;
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ordinals[i] -= meanOrdinal;
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}
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auto top = 0ll;
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auto bottom = 0ll;
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for (size_t i = 0; i < vsyncTS.size(); i++) {
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top += vsyncTS[i] * ordinals[i];
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bottom += ordinals[i] * ordinals[i];
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}
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if (CC_UNLIKELY(bottom == 0)) {
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it->second = {mIdealPeriod, 0};
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clearTimestamps();
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return false;
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}
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nsecs_t const anticipatedPeriod = top * kScalingFactor / bottom;
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nsecs_t const intercept = meanTS - (anticipatedPeriod * meanOrdinal / kScalingFactor);
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auto const percent = std::abs(anticipatedPeriod - mIdealPeriod) * kMaxPercent / mIdealPeriod;
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if (percent >= kOutlierTolerancePercent) {
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it->second = {mIdealPeriod, 0};
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clearTimestamps();
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return false;
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}
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traceInt64If("VSP-period", anticipatedPeriod);
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traceInt64If("VSP-intercept", intercept);
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it->second = {anticipatedPeriod, intercept};
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ALOGV("model update ts: %" PRId64 " slope: %" PRId64 " intercept: %" PRId64, timestamp,
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anticipatedPeriod, intercept);
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return true;
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}
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nsecs_t VSyncPredictor::nextAnticipatedVSyncTimeFromLocked(nsecs_t timePoint) const {
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auto const [slope, intercept] = getVSyncPredictionModelLocked();
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if (mTimestamps.empty()) {
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traceInt64If("VSP-mode", 1);
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auto const knownTimestamp = mKnownTimestamp ? *mKnownTimestamp : timePoint;
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auto const numPeriodsOut = ((timePoint - knownTimestamp) / mIdealPeriod) + 1;
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return knownTimestamp + numPeriodsOut * mIdealPeriod;
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}
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auto const oldest = *std::min_element(mTimestamps.begin(), mTimestamps.end());
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// See b/145667109, the ordinal calculation must take into account the intercept.
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auto const zeroPoint = oldest + intercept;
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auto const ordinalRequest = (timePoint - zeroPoint + slope) / slope;
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auto const prediction = (ordinalRequest * slope) + intercept + oldest;
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traceInt64If("VSP-mode", 0);
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traceInt64If("VSP-timePoint", timePoint);
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traceInt64If("VSP-prediction", prediction);
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auto const printer = [&, slope = slope, intercept = intercept] {
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std::stringstream str;
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str << "prediction made from: " << timePoint << "prediction: " << prediction << " (+"
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<< prediction - timePoint << ") slope: " << slope << " intercept: " << intercept
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<< "oldestTS: " << oldest << " ordinal: " << ordinalRequest;
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return str.str();
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};
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ALOGV("%s", printer().c_str());
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LOG_ALWAYS_FATAL_IF(prediction < timePoint, "VSyncPredictor: model miscalculation: %s",
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printer().c_str());
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return prediction;
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}
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nsecs_t VSyncPredictor::nextAnticipatedVSyncTimeFrom(nsecs_t timePoint) const {
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std::lock_guard lock(mMutex);
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return nextAnticipatedVSyncTimeFromLocked(timePoint);
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}
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/*
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* Returns whether a given vsync timestamp is in phase with a frame rate.
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* If the frame rate is not a divider of the refresh rate, it is always considered in phase.
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* For example, if the vsync timestamps are (16.6,33.3,50.0,66.6):
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* isVSyncInPhase(16.6, 30) = true
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* isVSyncInPhase(33.3, 30) = false
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* isVSyncInPhase(50.0, 30) = true
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*/
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bool VSyncPredictor::isVSyncInPhase(nsecs_t timePoint, Fps frameRate) const {
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struct VsyncError {
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nsecs_t vsyncTimestamp;
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float error;
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bool operator<(const VsyncError& other) const { return error < other.error; }
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};
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std::lock_guard lock(mMutex);
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const auto divider =
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RefreshRateConfigs::getFrameRateDivider(Fps::fromPeriodNsecs(mIdealPeriod), frameRate);
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if (divider <= 1 || timePoint == 0) {
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return true;
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}
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const nsecs_t period = mRateMap[mIdealPeriod].slope;
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const nsecs_t justBeforeTimePoint = timePoint - period / 2;
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const nsecs_t dividedPeriod = mIdealPeriod / divider;
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// If this is the first time we have asked about this divider with the
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// current vsync period, it is considered in phase and we store the closest
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// vsync timestamp
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const auto knownTimestampIter = mRateDividerKnownTimestampMap.find(dividedPeriod);
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if (knownTimestampIter == mRateDividerKnownTimestampMap.end()) {
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const auto vsync = nextAnticipatedVSyncTimeFromLocked(justBeforeTimePoint);
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mRateDividerKnownTimestampMap[dividedPeriod] = vsync;
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return true;
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}
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// Find the next N vsync timestamp where N is the divider.
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// One of these vsyncs will be in phase. We return the one which is
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// the most aligned with the last known in phase vsync
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std::vector<VsyncError> vsyncs(static_cast<size_t>(divider));
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const nsecs_t knownVsync = knownTimestampIter->second;
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nsecs_t point = justBeforeTimePoint;
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for (size_t i = 0; i < divider; i++) {
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const nsecs_t vsync = nextAnticipatedVSyncTimeFromLocked(point);
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const auto numPeriods = static_cast<float>(vsync - knownVsync) / (period * divider);
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const auto error = std::abs(std::round(numPeriods) - numPeriods);
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vsyncs[i] = {vsync, error};
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point = vsync + 1;
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}
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const auto minVsyncError = std::min_element(vsyncs.begin(), vsyncs.end());
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mRateDividerKnownTimestampMap[dividedPeriod] = minVsyncError->vsyncTimestamp;
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return std::abs(minVsyncError->vsyncTimestamp - timePoint) < period / 2;
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}
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VSyncPredictor::Model VSyncPredictor::getVSyncPredictionModel() const {
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std::lock_guard lock(mMutex);
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const auto model = VSyncPredictor::getVSyncPredictionModelLocked();
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return {model.slope, model.intercept};
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}
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VSyncPredictor::Model VSyncPredictor::getVSyncPredictionModelLocked() const {
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return mRateMap.find(mIdealPeriod)->second;
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}
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void VSyncPredictor::setPeriod(nsecs_t period) {
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ATRACE_CALL();
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std::lock_guard lock(mMutex);
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static constexpr size_t kSizeLimit = 30;
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if (CC_UNLIKELY(mRateMap.size() == kSizeLimit)) {
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mRateMap.erase(mRateMap.begin());
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}
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mIdealPeriod = period;
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if (mRateMap.find(period) == mRateMap.end()) {
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mRateMap[mIdealPeriod] = {period, 0};
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}
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clearTimestamps();
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}
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void VSyncPredictor::clearTimestamps() {
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if (!mTimestamps.empty()) {
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auto const maxRb = *std::max_element(mTimestamps.begin(), mTimestamps.end());
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if (mKnownTimestamp) {
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mKnownTimestamp = std::max(*mKnownTimestamp, maxRb);
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} else {
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mKnownTimestamp = maxRb;
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}
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mTimestamps.clear();
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mLastTimestampIndex = 0;
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}
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}
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bool VSyncPredictor::needsMoreSamples() const {
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std::lock_guard lock(mMutex);
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return mTimestamps.size() < kMinimumSamplesForPrediction;
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}
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void VSyncPredictor::resetModel() {
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std::lock_guard lock(mMutex);
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mRateMap[mIdealPeriod] = {mIdealPeriod, 0};
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clearTimestamps();
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}
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void VSyncPredictor::dump(std::string& result) const {
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std::lock_guard lock(mMutex);
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StringAppendF(&result, "\tmIdealPeriod=%.2f\n", mIdealPeriod / 1e6f);
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StringAppendF(&result, "\tRefresh Rate Map:\n");
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for (const auto& [idealPeriod, periodInterceptTuple] : mRateMap) {
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StringAppendF(&result,
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"\t\tFor ideal period %.2fms: period = %.2fms, intercept = %" PRId64 "\n",
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idealPeriod / 1e6f, periodInterceptTuple.slope / 1e6f,
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periodInterceptTuple.intercept);
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}
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}
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} // namespace android::scheduler
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// TODO(b/129481165): remove the #pragma below and fix conversion issues
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#pragma clang diagnostic pop // ignored "-Wextra"
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