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1 /*-------------------------------------------------------------------------
2  * drawElements Quality Program OpenGL (ES) Module
3  * -----------------------------------------------
4  *
5  * Copyright 2014 The Android Open Source Project
6  *
7  * Licensed under the Apache License, Version 2.0 (the "License");
8  * you may not use this file except in compliance with the License.
9  * You may obtain a copy of the License at
10  *
11  *      http://www.apache.org/licenses/LICENSE-2.0
12  *
13  * Unless required by applicable law or agreed to in writing, software
14  * distributed under the License is distributed on an "AS IS" BASIS,
15  * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
16  * See the License for the specific language governing permissions and
17  * limitations under the License.
18  *
19  *//*!
20  * \file
21  * \brief Calibration tools.
22  *//*--------------------------------------------------------------------*/
23 
24 #include "glsCalibration.hpp"
25 #include "tcuTestLog.hpp"
26 #include "tcuVectorUtil.hpp"
27 #include "deStringUtil.hpp"
28 #include "deMath.h"
29 #include "deClock.h"
30 
31 #include <algorithm>
32 #include <limits>
33 
34 using std::string;
35 using std::vector;
36 using tcu::Vec2;
37 using tcu::TestLog;
38 using tcu::TestNode;
39 using namespace glu;
40 
41 namespace deqp
42 {
43 namespace gls
44 {
45 
46 // Reorders input arbitrarily, linear complexity and no allocations
47 template<typename T>
destructiveMedian(vector<T> & data)48 float destructiveMedian (vector<T>& data)
49 {
50 	const typename vector<T>::iterator mid = data.begin()+data.size()/2;
51 
52 	std::nth_element(data.begin(), mid, data.end());
53 
54 	if (data.size()%2 == 0) // Even number of elements, need average of two centermost elements
55 		return (*mid + *std::max_element(data.begin(), mid))*0.5f; // Data is partially sorted around mid, mid is half an item after center
56 	else
57 		return *mid;
58 }
59 
theilSenLinearRegression(const std::vector<tcu::Vec2> & dataPoints)60 LineParameters theilSenLinearRegression (const std::vector<tcu::Vec2>& dataPoints)
61 {
62 	const float		epsilon					= 1e-6f;
63 
64 	const int		numDataPoints			= (int)dataPoints.size();
65 	vector<float>	pairwiseCoefficients;
66 	vector<float>	pointwiseOffsets;
67 	LineParameters	result					(0.0f, 0.0f);
68 
69 	// Compute the pairwise coefficients.
70 	for (int i = 0; i < numDataPoints; i++)
71 	{
72 		const Vec2& ptA = dataPoints[i];
73 
74 		for (int j = 0; j < i; j++)
75 		{
76 			const Vec2& ptB = dataPoints[j];
77 
78 			if (de::abs(ptA.x() - ptB.x()) > epsilon)
79 				pairwiseCoefficients.push_back((ptA.y() - ptB.y()) / (ptA.x() - ptB.x()));
80 		}
81 	}
82 
83 	// Find the median of the pairwise coefficients.
84 	// \note If there are no data point pairs with differing x values, the coefficient variable will stay zero as initialized.
85 	if (!pairwiseCoefficients.empty())
86 		result.coefficient = destructiveMedian(pairwiseCoefficients);
87 
88 	// Compute the offsets corresponding to the median coefficient, for all data points.
89 	for (int i = 0; i < numDataPoints; i++)
90 		pointwiseOffsets.push_back(dataPoints[i].y() - result.coefficient*dataPoints[i].x());
91 
92 	// Find the median of the offsets.
93 	// \note If there are no data points, the offset variable will stay zero as initialized.
94 	if (!pointwiseOffsets.empty())
95 		result.offset = destructiveMedian(pointwiseOffsets);
96 
97 	return result;
98 }
99 
100 // Sample from given values using linear interpolation at a given position as if values were laid to range [0, 1]
101 template <typename T>
linearSample(const std::vector<T> & values,float position)102 static float linearSample (const std::vector<T>& values, float position)
103 {
104 	DE_ASSERT(position >= 0.0f);
105 	DE_ASSERT(position <= 1.0f);
106 
107 	const int	maxNdx				= (int)values.size() - 1;
108 	const float	floatNdx			= (float)maxNdx * position;
109 	const int	lowerNdx			= (int)deFloatFloor(floatNdx);
110 	const int	higherNdx			= lowerNdx + (lowerNdx == maxNdx ? 0 : 1); // Use only last element if position is 1.0
111 	const float	interpolationFactor = floatNdx - (float)lowerNdx;
112 
113 	DE_ASSERT(lowerNdx >= 0 && lowerNdx < (int)values.size());
114 	DE_ASSERT(higherNdx >= 0 && higherNdx < (int)values.size());
115 	DE_ASSERT(interpolationFactor >= 0 && interpolationFactor < 1.0f);
116 
117 	return tcu::mix((float)values[lowerNdx], (float)values[higherNdx], interpolationFactor);
118 }
119 
theilSenSiegelLinearRegression(const std::vector<tcu::Vec2> & dataPoints,float reportedConfidence)120 LineParametersWithConfidence theilSenSiegelLinearRegression (const std::vector<tcu::Vec2>& dataPoints, float reportedConfidence)
121 {
122 	DE_ASSERT(!dataPoints.empty());
123 
124 	// Siegel's variation
125 
126 	const float						epsilon				= 1e-6f;
127 	const int						numDataPoints		= (int)dataPoints.size();
128 	std::vector<float>				medianSlopes;
129 	std::vector<float>				pointwiseOffsets;
130 	LineParametersWithConfidence	result;
131 
132 	// Compute the median slope via each element
133 	for (int i = 0; i < numDataPoints; i++)
134 	{
135 		const tcu::Vec2&	ptA		= dataPoints[i];
136 		std::vector<float>	slopes;
137 
138 		slopes.reserve(numDataPoints);
139 
140 		for (int j = 0; j < numDataPoints; j++)
141 		{
142 			const tcu::Vec2& ptB = dataPoints[j];
143 
144 			if (de::abs(ptA.x() - ptB.x()) > epsilon)
145 				slopes.push_back((ptA.y() - ptB.y()) / (ptA.x() - ptB.x()));
146 		}
147 
148 		// Add median of slopes through point i
149 		medianSlopes.push_back(destructiveMedian(slopes));
150 	}
151 
152 	DE_ASSERT(!medianSlopes.empty());
153 
154 	// Find the median of the pairwise coefficients.
155 	std::sort(medianSlopes.begin(), medianSlopes.end());
156 	result.coefficient = linearSample(medianSlopes, 0.5f);
157 
158 	// Compute the offsets corresponding to the median coefficient, for all data points.
159 	for (int i = 0; i < numDataPoints; i++)
160 		pointwiseOffsets.push_back(dataPoints[i].y() - result.coefficient*dataPoints[i].x());
161 
162 	// Find the median of the offsets.
163 	std::sort(pointwiseOffsets.begin(), pointwiseOffsets.end());
164 	result.offset = linearSample(pointwiseOffsets, 0.5f);
165 
166 	// calculate confidence intervals
167 	result.coefficientConfidenceLower = linearSample(medianSlopes, 0.5f - reportedConfidence*0.5f);
168 	result.coefficientConfidenceUpper = linearSample(medianSlopes, 0.5f + reportedConfidence*0.5f);
169 
170 	result.offsetConfidenceLower = linearSample(pointwiseOffsets, 0.5f - reportedConfidence*0.5f);
171 	result.offsetConfidenceUpper = linearSample(pointwiseOffsets, 0.5f + reportedConfidence*0.5f);
172 
173 	result.confidence = reportedConfidence;
174 
175 	return result;
176 }
177 
isDone(void) const178 bool MeasureState::isDone (void) const
179 {
180 	return (int)frameTimes.size() >= maxNumFrames || (frameTimes.size() >= 2 &&
181 													  frameTimes[frameTimes.size()-2] >= (deUint64)frameShortcutTime &&
182 													  frameTimes[frameTimes.size()-1] >= (deUint64)frameShortcutTime);
183 }
184 
getTotalTime(void) const185 deUint64 MeasureState::getTotalTime (void) const
186 {
187 	deUint64 time = 0;
188 	for (int i = 0; i < (int)frameTimes.size(); i++)
189 		time += frameTimes[i];
190 	return time;
191 }
192 
clear(void)193 void MeasureState::clear (void)
194 {
195 	maxNumFrames		= 0;
196 	frameShortcutTime	= std::numeric_limits<float>::infinity();
197 	numDrawCalls		= 0;
198 	frameTimes.clear();
199 }
200 
start(int maxNumFrames_,float frameShortcutTime_,int numDrawCalls_)201 void MeasureState::start (int maxNumFrames_, float frameShortcutTime_, int numDrawCalls_)
202 {
203 	frameTimes.clear();
204 	frameTimes.reserve(maxNumFrames_);
205 	maxNumFrames		= maxNumFrames_;
206 	frameShortcutTime	= frameShortcutTime_;
207 	numDrawCalls		= numDrawCalls_;
208 }
209 
TheilSenCalibrator(void)210 TheilSenCalibrator::TheilSenCalibrator (void)
211 	: m_params	(1 /* initial calls */, 10 /* calibrate iter frames */, 2000.0f /* calibrate iter shortcut threshold */, 31 /* max calibration iterations */,
212 				 1000.0f/30.0f /* target frame time */, 1000.0f/60.0f /* frame time cap */, 1000.0f /* target measure duration */)
213 	, m_state	(INTERNALSTATE_LAST)
214 {
215 	clear();
216 }
217 
TheilSenCalibrator(const CalibratorParameters & params)218 TheilSenCalibrator::TheilSenCalibrator (const CalibratorParameters& params)
219 	: m_params	(params)
220 	, m_state	(INTERNALSTATE_LAST)
221 {
222 	clear();
223 }
224 
~TheilSenCalibrator()225 TheilSenCalibrator::~TheilSenCalibrator()
226 {
227 }
228 
clear(void)229 void TheilSenCalibrator::clear (void)
230 {
231 	m_measureState.clear();
232 	m_calibrateIterations.clear();
233 	m_state = INTERNALSTATE_CALIBRATING;
234 }
235 
clear(const CalibratorParameters & params)236 void TheilSenCalibrator::clear (const CalibratorParameters& params)
237 {
238 	m_params = params;
239 	clear();
240 }
241 
getState(void) const242 TheilSenCalibrator::State TheilSenCalibrator::getState (void) const
243 {
244 	if (m_state == INTERNALSTATE_FINISHED)
245 		return STATE_FINISHED;
246 	else
247 	{
248 		DE_ASSERT(m_state == INTERNALSTATE_CALIBRATING || !m_measureState.isDone());
249 		return m_measureState.isDone() ? STATE_RECOMPUTE_PARAMS : STATE_MEASURE;
250 	}
251 }
252 
recordIteration(deUint64 iterationTime)253 void TheilSenCalibrator::recordIteration (deUint64 iterationTime)
254 {
255 	DE_ASSERT((m_state == INTERNALSTATE_CALIBRATING || m_state == INTERNALSTATE_RUNNING) && !m_measureState.isDone());
256 	m_measureState.frameTimes.push_back(iterationTime);
257 
258 	if (m_state == INTERNALSTATE_RUNNING && m_measureState.isDone())
259 		m_state = INTERNALSTATE_FINISHED;
260 }
261 
recomputeParameters(void)262 void TheilSenCalibrator::recomputeParameters (void)
263 {
264 	DE_ASSERT(m_state == INTERNALSTATE_CALIBRATING);
265 	DE_ASSERT(m_measureState.isDone());
266 
267 	// Minimum and maximum acceptable frame times.
268 	const float		minGoodFrameTimeUs	= m_params.targetFrameTimeUs * 0.95f;
269 	const float		maxGoodFrameTimeUs	= m_params.targetFrameTimeUs * 1.15f;
270 
271 	const int		numIterations		= (int)m_calibrateIterations.size();
272 
273 	// Record frame time.
274 	if (numIterations > 0)
275 	{
276 		m_calibrateIterations.back().frameTime = (float)((double)m_measureState.getTotalTime() / (double)m_measureState.frameTimes.size());
277 
278 		// Check if we're good enough to stop calibrating.
279 		{
280 			bool endCalibration = false;
281 
282 			// Is the maximum calibration iteration limit reached?
283 			endCalibration = endCalibration || (int)m_calibrateIterations.size() >= m_params.maxCalibrateIterations;
284 
285 			// Do a few past iterations have frame time in acceptable range?
286 			{
287 				const int numRelevantPastIterations = 2;
288 
289 				if (!endCalibration && (int)m_calibrateIterations.size() >= numRelevantPastIterations)
290 				{
291 					const CalibrateIteration* const		past			= &m_calibrateIterations[m_calibrateIterations.size() - numRelevantPastIterations];
292 					bool								allInGoodRange	= true;
293 
294 					for (int i = 0; i < numRelevantPastIterations && allInGoodRange; i++)
295 					{
296 						const float frameTimeUs = past[i].frameTime;
297 						if (!de::inRange(frameTimeUs, minGoodFrameTimeUs, maxGoodFrameTimeUs))
298 							allInGoodRange = false;
299 					}
300 
301 					endCalibration = endCalibration || allInGoodRange;
302 				}
303 			}
304 
305 			// Do a few past iterations have similar-enough call counts?
306 			{
307 				const int numRelevantPastIterations = 3;
308 				if (!endCalibration && (int)m_calibrateIterations.size() >= numRelevantPastIterations)
309 				{
310 					const CalibrateIteration* const		past			= &m_calibrateIterations[m_calibrateIterations.size() - numRelevantPastIterations];
311 					int									minCallCount	= std::numeric_limits<int>::max();
312 					int									maxCallCount	= std::numeric_limits<int>::min();
313 
314 					for (int i = 0; i < numRelevantPastIterations; i++)
315 					{
316 						minCallCount = de::min(minCallCount, past[i].numDrawCalls);
317 						maxCallCount = de::max(maxCallCount, past[i].numDrawCalls);
318 					}
319 
320 					if ((float)(maxCallCount - minCallCount) <= (float)minCallCount * 0.1f)
321 						endCalibration = true;
322 				}
323 			}
324 
325 			// Is call count just 1, and frame time still way too high?
326 			endCalibration = endCalibration || (m_calibrateIterations.back().numDrawCalls == 1 && m_calibrateIterations.back().frameTime > m_params.targetFrameTimeUs*2.0f);
327 
328 			if (endCalibration)
329 			{
330 				const int	minFrames			= 10;
331 				const int	maxFrames			= 60;
332 				int			numMeasureFrames	= deClamp32(deRoundFloatToInt32(m_params.targetMeasureDurationUs / m_calibrateIterations.back().frameTime), minFrames, maxFrames);
333 
334 				m_state = INTERNALSTATE_RUNNING;
335 				m_measureState.start(numMeasureFrames, m_params.calibrateIterationShortcutThreshold, m_calibrateIterations.back().numDrawCalls);
336 				return;
337 			}
338 		}
339 	}
340 
341 	DE_ASSERT(m_state == INTERNALSTATE_CALIBRATING);
342 
343 	// Estimate new call count.
344 	{
345 		int newCallCount;
346 
347 		if (numIterations == 0)
348 			newCallCount = m_params.numInitialCalls;
349 		else
350 		{
351 			vector<Vec2> dataPoints;
352 			for (int i = 0; i < numIterations; i++)
353 			{
354 				if (m_calibrateIterations[i].numDrawCalls == 1 || m_calibrateIterations[i].frameTime > m_params.frameTimeCapUs*1.05f) // Only account for measurements not too near the cap.
355 					dataPoints.push_back(Vec2((float)m_calibrateIterations[i].numDrawCalls, m_calibrateIterations[i].frameTime));
356 			}
357 
358 			if (numIterations == 1)
359 				dataPoints.push_back(Vec2(0.0f, 0.0f)); // If there's just one measurement so far, this will help in getting the next estimate.
360 
361 			{
362 				const float				targetFrameTimeUs	= m_params.targetFrameTimeUs;
363 				const float				coeffEpsilon		= 0.001f; // Coefficient must be large enough (and positive) to be considered sensible.
364 
365 				const LineParameters	estimatorLine		= theilSenLinearRegression(dataPoints);
366 
367 				int						prevMaxCalls		= 0;
368 
369 				// Find the maximum of the past call counts.
370 				for (int i = 0; i < numIterations; i++)
371 					prevMaxCalls = de::max(prevMaxCalls, m_calibrateIterations[i].numDrawCalls);
372 
373 				if (estimatorLine.coefficient < coeffEpsilon) // Coefficient not good for sensible estimation; increase call count enough to get a reasonably different value.
374 					newCallCount = 2*prevMaxCalls;
375 				else
376 				{
377 					// Solve newCallCount such that approximately targetFrameTime = offset + coefficient*newCallCount.
378 					newCallCount = (int)((targetFrameTimeUs - estimatorLine.offset) / estimatorLine.coefficient + 0.5f);
379 
380 					// We should generally prefer FPS counts below the target rather than above (i.e. higher frame times rather than lower).
381 					if (estimatorLine.offset + estimatorLine.coefficient*(float)newCallCount < minGoodFrameTimeUs)
382 						newCallCount++;
383 				}
384 
385 				// Make sure we have at least minimum amount of calls, and don't allow increasing call count too much in one iteration.
386 				newCallCount = de::clamp(newCallCount, 1, prevMaxCalls*10);
387 			}
388 		}
389 
390 		m_measureState.start(m_params.maxCalibrateIterationFrames, m_params.calibrateIterationShortcutThreshold, newCallCount);
391 		m_calibrateIterations.push_back(CalibrateIteration(newCallCount, 0.0f));
392 	}
393 }
394 
logCalibrationInfo(tcu::TestLog & log,const TheilSenCalibrator & calibrator)395 void logCalibrationInfo (tcu::TestLog& log, const TheilSenCalibrator& calibrator)
396 {
397 	const CalibratorParameters&				params				= calibrator.getParameters();
398 	const std::vector<CalibrateIteration>&	calibrateIterations	= calibrator.getCalibrationInfo();
399 
400 	// Write out default calibration info.
401 
402 	log << TestLog::Section("CalibrationInfo", "Calibration Info")
403 		<< TestLog::Message  << "Target frame time: " << params.targetFrameTimeUs << " us (" << 1000000 / params.targetFrameTimeUs << " fps)" << TestLog::EndMessage;
404 
405 	for (int iterNdx = 0; iterNdx < (int)calibrateIterations.size(); iterNdx++)
406 	{
407 		log << TestLog::Message << "  iteration " << iterNdx << ": " << calibrateIterations[iterNdx].numDrawCalls << " calls => "
408 								<< de::floatToString(calibrateIterations[iterNdx].frameTime, 2) << " us ("
409 								<< de::floatToString(1000000.0f / calibrateIterations[iterNdx].frameTime, 2) << " fps)" << TestLog::EndMessage;
410 	}
411 	log << TestLog::Integer("CallCount",	"Calibrated call count",	"",	QP_KEY_TAG_NONE, calibrator.getMeasureState().numDrawCalls)
412 		<< TestLog::Integer("FrameCount",	"Calibrated frame count",	"", QP_KEY_TAG_NONE, (int)calibrator.getMeasureState().frameTimes.size());
413 	log << TestLog::EndSection;
414 }
415 
416 } // gls
417 } // deqp
418