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CPUCruncher.cpp
Go to the documentation of this file.
1 #include "CPUCruncher.h"
2 #include "HiveNumbers.h"
3 #include <ctime>
4 #include <sys/resource.h>
5 #include <sys/times.h>
6
7 #include <tbb/tick_count.h>
8 #include <thread>
9
10 std::vector<unsigned int> CPUCruncher::m_niters_vect;
11 std::vector<double> CPUCruncher::m_times_vect;
12 CPUCruncher::CHM CPUCruncher::m_name_ncopies_map;
13
14 //DECLARE_ALGORITHM_FACTORY(CPUCruncher)
15 DECLARE_COMPONENT(CPUCruncher)
16
17 //------------------------------------------------------------------------------
18
19 CPUCruncher::CPUCruncher(const std::string& name, // the algorithm instance name
20 ISvcLocator*pSvc) :
21 GaudiAlgorithm(name, pSvc), m_avg_runtime(1.), m_var_runtime(.01), m_shortCalib(
22 false) {
23
24 declareProperty("inpKeys", m_inpKeys);
25 declareProperty("outKeys", m_outKeys);
26
27
28 declareProperty("avgRuntime", m_avg_runtime,
29 "Average runtime of the module.");
30 declareProperty("varRuntime", m_var_runtime,
31 "Variance of the runtime of the module.");
32 declareProperty("localRndm", m_local_rndm_gen = true,
33 "Decide if the local random generator is to be used");
34 declareProperty("NIterationsVect", m_niters_vect,
35 "Number of iterations for the calibration.");
36 declareProperty("NTimesVect", m_times_vect,
37 "Number of seconds for the calibration.");
38 declareProperty("shortCalib", m_shortCalib = false,
39 "Enable coarse grained calibration");
40 declareProperty("RwRepetitions", m_rwRepetitions = 1,
41 "Increase access to the WB");
42 declareProperty("SleepyExecution", m_sleepyExecution = false,
43 "Sleep during execution instead of crunching");
44
45 // Register the algo in the static concurrent hash map in order to
46 // monitor the # of copies
47 CHM::accessor name_ninstances;
48 m_name_ncopies_map.insert(name_ninstances, name);
49 name_ninstances->second += 1;
50 }
51
52 CPUCruncher::~CPUCruncher() {
53 for (uint i = 0; i < m_inputHandles.size(); ++i) {
54 delete m_inputHandles[i];
55 }
56
57 m_outputHandles.resize(MAX_OUTPUTS);
58 for (uint i = 0; i < m_outputHandles.size(); ++i) {
59 delete m_outputHandles[i];
60 }
61 }
62
63 StatusCode CPUCruncher::initialize(){
64 if (m_times_vect.size()==0){
65 calibrate();
66 }
67
68 // This is a bit ugly. There is no way to declare a vector of DataObjectHandles, so
69 // we need to wait until initialize when we've read in the input and output key
70 // properties, and know their size, and then turn them
71 // into Handles and register them with the framework by calling declareProperty. We
72 // could call declareInput/declareOutput on them too.
73
74 int i=0;
75 for (auto k: m_inpKeys) {
76 debug() << "adding input key " << k << endmsg;
77 m_inputHandles.push_back( new DataObjectHandle<DataObject>( k, Gaudi::DataHandle::Reader, this ));
78 declareProperty("dummy_in_" + std::to_string(i), *(m_inputHandles.back()) );
79 i++;
80 }
81
82 i = 0;
83 for (auto k: m_outKeys) {
84 debug() << "adding output key " << k << endmsg;
85 m_outputHandles.push_back( new DataObjectHandle<DataObject>( k, Gaudi::DataHandle::Writer, this ));
86 declareProperty("dummy_out_" + std::to_string(i), *(m_outputHandles.back()) );
87 i++;
88 }
89
90 return StatusCode::SUCCESS ;
91 }
92
93 /*
94 Calibrate the crunching finding the right relation between max number to be searched and time spent.
95 The relation is a sqrt for times greater than 10^-4 seconds.
96 */
97 void CPUCruncher::calibrate(){
98
99 MsgStream log(msgSvc(), name());
100 m_niters_vect.push_back(0);
101 m_niters_vect.push_back(500);
102 m_niters_vect.push_back(600);
103 m_niters_vect.push_back(700);
104 m_niters_vect.push_back(800);
105 m_niters_vect.push_back(1000);
106 m_niters_vect.push_back(1300);
107 m_niters_vect.push_back(1600);
108 m_niters_vect.push_back(2000);
109 m_niters_vect.push_back(2300);
110 m_niters_vect.push_back(2600);
111 m_niters_vect.push_back(3000);
112 m_niters_vect.push_back(3300);
113 m_niters_vect.push_back(3500);
114 m_niters_vect.push_back(3900);
115 m_niters_vect.push_back(4200);
116 m_niters_vect.push_back(5000);
117 m_niters_vect.push_back(6000);
118 m_niters_vect.push_back(8000);
119 m_niters_vect.push_back(10000);
120 m_niters_vect.push_back(12000);
121 m_niters_vect.push_back(15000);
122 m_niters_vect.push_back(17000);
123 m_niters_vect.push_back(20000);
124 m_niters_vect.push_back(25000);
125 m_niters_vect.push_back(30000);
126 m_niters_vect.push_back(35000);
127 m_niters_vect.push_back(40000);
128 m_niters_vect.push_back(60000);
129 if (!m_shortCalib){
130 m_niters_vect.push_back(100000);
131 m_niters_vect.push_back(200000);
132 }
133
134
135 m_times_vect.resize(m_niters_vect.size());
136 m_times_vect[0]=0.;
137
138
139 log << MSG::INFO << "Starting calibration..." << endmsg;
140 for (unsigned int i=1;i<m_niters_vect.size();++i){
141 unsigned long niters=m_niters_vect[i];
142 unsigned int trials = 30;
143 do{
144 auto start_cali=tbb::tick_count::now();
145 findPrimes(niters);
146 auto stop_cali=tbb::tick_count::now();
147 double deltat = (stop_cali-start_cali).seconds();
148 m_times_vect[i]=deltat;
149 log << MSG::DEBUG << "Calibration: # iters = " << niters << " => " << deltat << endmsg;
150 trials--;
151 } while(trials > 0 and m_times_vect[i]<m_times_vect[i-1]); // make sure that they are monotonic
152 }
153 log << MSG::INFO << "Calibration finished!" << endmsg;
154 }
155
156 unsigned long CPUCruncher::getNCaliIters(double runtime){
157
158 unsigned int smaller_i=0;
159 double time=0.;
160 bool found=false;
161 // We know that the first entry is 0, so we start to iterate from 1
162 for (unsigned int i=1;i<m_times_vect.size();i++){
163 time = m_times_vect[i];
164 if (time>runtime){
165 smaller_i=i-1;
166 found=true;
167 break;
168 }
169 }
170
171 // Case 1: we are outside the interpolation range, we take the last 2 points
172 if (not found)
173 smaller_i=m_times_vect.size()-2;
174
175 // Case 2: we maeke a linear interpolation
176 // y=mx+q
177 const double x0=m_times_vect[smaller_i];
178 const double x1=m_times_vect[smaller_i+1];
179 const double y0=m_niters_vect[smaller_i];
180 const double y1=m_niters_vect[smaller_i+1];
181 const double m=(y1-y0)/(x1-x0);
182 const double q=y0-m*x0;
183
184 const unsigned long nCaliIters = m * runtime + q ;
185 //always() << x0 << "<" << runtime << "<" << x1 << " Corresponding to " << nCaliIters << " iterations" << endmsg;
186
187 return nCaliIters ;
188 }
189
190
191 void CPUCruncher::findPrimes (const unsigned long int n_iterations) {
192
193
194 MsgStream log(msgSvc(), name());
195
196 // Flag to trigger the allocation
197 bool is_prime;
198
199 // Let's prepare the material for the allocations
200 unsigned int primes_size=1;
201 unsigned long* primes = new unsigned long[primes_size];
202 primes[0]=2;
203
204 unsigned long i = 2;
205
206 // Loop on numbers
207 for (unsigned long int iiter=0;iiter<n_iterations;iiter++ ){
208 // Once at max, it returns to 0
209 i+=1;
210
211 // Check if it can be divided by the smaller ones
212 is_prime = true;
213 for (unsigned long j=2;j<i && is_prime;++j){
214 if (i%j == 0){
215 is_prime = false;
216 }
217 }// end loop on numbers < than tested one
218 if (is_prime){
219 // copy the array of primes (INEFFICIENT ON PURPOSE!)
220 unsigned int new_primes_size = 1 + primes_size;
221 unsigned long* new_primes = new unsigned long[new_primes_size];
222
223 for (unsigned int prime_index=0; prime_index<primes_size;prime_index++){
224 new_primes[prime_index]=primes[prime_index];
225 }
226 // attach the last prime
227 new_primes[primes_size]=i;
228
229 // Update primes array
230 delete[] primes;
231 primes = new_primes;
232 primes_size=new_primes_size;
233 } // end is prime
234
235 } // end of while loop
236
237 // Fool Compiler optimisations:
238 for (unsigned int prime_index=0; prime_index<primes_size;prime_index++)
239 if (primes[prime_index] == 4)
240 log << "This does never happen, but it's necessary too fool aggressive compiler optimisations!"<< endmsg ;
241
242 delete[] primes;
243
244 }
245
246 //------------------------------------------------------------------------------
247
248 StatusCode CPUCruncher::execute () // the execution of the algorithm
249 {
250
251 MsgStream logstream(msgSvc(), name());
252
253 if (m_sleepyExecution) {
254 logstream << MSG::DEBUG << "Going to dream for: "<< m_avg_runtime << endmsg;
255 std::chrono::duration<double> dreamtime( m_avg_runtime );
256
257 tbb::tick_count starttbb=tbb::tick_count::now();
258 std::this_thread::sleep_for(dreamtime);
259 tbb::tick_count endtbb=tbb::tick_count::now();
260 // actual sleeping time can be longer due to scheduling or resource contention delays
261 const double actualDreamTime=(endtbb-starttbb).seconds();
262
263 logstream << MSG::DEBUG << "Actual dreaming time was: "<< actualDreamTime << "s" << endmsg;
264
265 return StatusCode::SUCCESS;
266 }
267
268 float runtime;
269
270 if (m_local_rndm_gen){
271 /* This will disappear with a thread safe random number generator svc
272 * Use box mueller to generate gaussian randoms
273 * The quality is not good for in depth study given that the generator is a
274 * linear congruent.
275 * Throw away basically a free number: we are in a cpu cruncher after all.
276 * The seed is taken from the clock, but we could assign a seed per module to
277 * ensure reproducibility.
278 *
279 * This is not an overkill but rather an exercise towards a thread safe
280 * random number generation.
281 */
282
283 auto getGausRandom = [] (double mean, double sigma) -> double {
284
285 unsigned int seed = std::clock();
286
287 auto getUnifRandom = [] (unsigned int & seed) ->double {
288 // from numerical recipies
289 constexpr unsigned int m = 232;
290 constexpr unsigned int a = 1664525;
291 constexpr unsigned int c = 1013904223;
292 seed = (a * seed + c) % m;
293 const double unif = double(seed) / m;
294 return unif;
295 };
296
297 const double unif1 = getUnifRandom(seed);
298 const double unif2 = getUnifRandom(seed);
299 const double normal = sqrt(-2.*log(unif1))*cos(2*M_PI*unif2);
300 return normal*sigma + mean;
301 };
302 runtime = fabs(getGausRandom( m_avg_runtime , m_var_runtime ));
303 //End Of temp block
304 } else {
305 // Should be a member.
306 HiveRndm::HiveNumbers rndmgaus(randSvc(), Rndm::Gauss( m_avg_runtime , m_var_runtime ));
307 runtime = std::fabs(rndmgaus());
308 }
309
310 tbb::tick_count starttbb=tbb::tick_count::now();
311 logstream << MSG::DEBUG << "Runtime will be: "<< runtime << endmsg;
312 if (getContext())
313 logstream << MSG::DEBUG << "Start event " << getContext()->evt()
314 << " in slot " << getContext()->slot()
315 << " on pthreadID " << std::hex << pthread_self() << std::dec
316 << endmsg;
317
318 for (auto & inputHandle: m_inputHandles){
319 if(!inputHandle->isValid())
320 continue;
321
322 DataObject* obj = nullptr;
323 for (unsigned int i=0; i<m_rwRepetitions;++i){
324 obj = inputHandle->get();
325 }
326 if (obj == nullptr)
327 logstream << MSG::ERROR << "A read object was a null pointer." << endmsg;
328 }
329
330 const unsigned long n_iters= getNCaliIters(runtime);
331 findPrimes( n_iters );
332
333 for (auto & outputHandle: m_outputHandles){
334 if(!outputHandle->isValid())
335 continue;
336
337 outputHandle->put(new DataObject());
338 }
339
340 for (auto & inputHandle: m_inputHandles){
341 if(!inputHandle->isValid())
342 continue;
343
344 for (unsigned int i=1; i<m_rwRepetitions;++i){
345 inputHandle->get();
346 }
347 }
348
349 tbb::tick_count endtbb=tbb::tick_count::now();
350
351 const double actualRuntime=(endtbb-starttbb).seconds();
352
353 if (getContext())
354 logstream << MSG::DEBUG << "Finish event " << getContext()->evt()
355 // << " on pthreadID " << getContext()->m_thread_id
356 << " in " << actualRuntime << " seconds" << endmsg;
357
358 logstream << MSG::DEBUG << "Timing: ExpectedRuntime= " << runtime
359 << " ActualRuntime= " << actualRuntime
360 << " Ratio= " << runtime/actualRuntime
361 << " Niters= " << n_iters << endmsg;
362
363
364 return StatusCode::SUCCESS ;
365 }
366
367 //------------------------------------------------------------------------------
368
369 StatusCode CPUCruncher::finalize () // the finalization of the algorithm
370 {
371 MsgStream log(msgSvc(), name());
372
373 unsigned int ninstances;
374
375 {
376 CHM::const_accessor const_name_ninstances;
377 m_name_ncopies_map.find(const_name_ninstances,name());
378 ninstances=const_name_ninstances->second;
379 }
380
381 constexpr double s2ms=1000.;
382 // do not show repetitions
383 if (ninstances!=0){
384 log << MSG::INFO << "Summary: name= "<< name()
385 <<"\t avg_runtime= " << m_avg_runtime*s2ms
386 << "\t n_clones= " << ninstances << endmsg;
387
388 CHM::accessor name_ninstances;
389 m_name_ncopies_map.find(name_ninstances,name());
390 name_ninstances->second=0;
391 }
392
393 return GaudiAlgorithm::finalize () ;
394 }
395
396 //------------------------------------------------------------------------------
397
398
399
CPUCruncher::m_sleepyExecution
bool m_sleepyExecution
Definition: CPUCruncher.h:81
MsgStream
Definition of the MsgStream class used to transmit messages.
Definition: MsgStream.h:24
std::chrono::duration
ISvcLocator
The ISvcLocator is the interface implemented by the Service Factory in the Application Manager to loc...
Definition: ISvcLocator.h:25
CPUCruncher::initialize
virtual StatusCode initialize()
Its initialization.
Definition: CPUCruncher.cpp:63
gaudiComponentHelp.name
name
Definition: gaudiComponentHelp.py:28
CPUCruncher::m_shortCalib
bool m_shortCalib
Definition: CPUCruncher.h:60
EventContext::slot
ContextID_t slot() const
Definition: EventContext.h:41
plotSpeedupsPyRoot.time
tuple time
Definition: plotSpeedupsPyRoot.py:146
CPUCruncher::MAX_OUTPUTS
const uint MAX_OUTPUTS
Definition: CPUCruncher.h:69
Gaudi.Configuration.log
tuple log
Definition: Configuration.py:13
gaudirun.c
tuple c
Definition: gaudirun.py:391
CPUCruncher::~CPUCruncher
virtual ~CPUCruncher()
virtual & protected desctrustor
Definition: CPUCruncher.cpp:52
std::to_string
T to_string(T...args)
CPUCruncher::findPrimes
void findPrimes(const unsigned long int)
The CPU intensive function.
Definition: CPUCruncher.cpp:191
MSG::DEBUG
Definition: IMessageSvc.h:18
std::clock
T clock(T...args)
CPUCruncher::m_avg_runtime
double m_avg_runtime
Definition: CPUCruncher.h:57
std
STL namespace.
std::this_thread::sleep_for
T sleep_for(T...args)
GaudiAlgorithm::declareProperty
Property * declareProperty(const std::string &name, DataObjectHandle< T > &hndl, const std::string &doc="none") const
Definition: GaudiAlgorithm.h:695
Rndm::Gauss
Parameters for the Gauss random number generation.
Definition: RndmGenerators.h:21
Algorithm::getContext
EventContext * getContext() const
get the context
Definition: Algorithm.h:571
CPUCruncher::calibrate
void calibrate()
Calibrate.
Definition: CPUCruncher.cpp:97
CPUCruncher::execute
virtual StatusCode execute()
the execution of the algorithm
Definition: CPUCruncher.cpp:248
CPUCruncher::getNCaliIters
long unsigned int getNCaliIters(double)
Definition: CPUCruncher.cpp:156
Gaudi::DataHandle::Reader
Definition: DataHandle.h:31
DECLARE_COMPONENT
#define DECLARE_COMPONENT(type)
Definition: PluginService.h:36
std::vector::resize
T resize(T...args)
EventContext::evt
ContextEvt_t evt() const
Definition: EventContext.h:40
Algorithm::name
const std::string & name() const override
The identifying name of the algorithm object.
Definition: Algorithm.cpp:820
CPUCruncher::finalize
virtual StatusCode finalize()
the finalization of the algorithm
Definition: CPUCruncher.cpp:369
DataObjectHandle< DataObject >
std::vector::push_back
T push_back(T...args)
CPUCruncher::m_niters_vect
static std::vector< unsigned int > m_niters_vect
Definition: CPUCruncher.h:63
CPUCruncher::m_name_ncopies_map
static CHM m_name_ncopies_map
Definition: CPUCruncher.h:78
StatusCode::SUCCESS
Definition: StatusCode.h:30
StatusCode
This class is used for returning status codes from appropriate routines.
Definition: StatusCode.h:26
Gaudi::Units::m
constexpr double m
Definition: SystemOfUnits.h:93
GaudiAlgorithm::finalize
StatusCode finalize() override
standard finalization method
Definition: GaudiAlgorithm.cpp:62
HiveRndm::HiveNumbers
Definition: HiveNumbers.h:28
GaudiAlgorithm
The useful base class for data processing algorithms.
Definition: GaudiAlgorithm.h:93
CPUCruncher.h
Algorithm::randSvc
SmartIF< IRndmGenSvc > & randSvc() const
AIDA-based NTuple service Returns a pointer to the AIDATuple service if present.
std::fabs
T fabs(T...args)
CPUCruncher::m_times_vect
static std::vector< double > m_times_vect
Definition: CPUCruncher.h:64
CPUCruncher::m_inputHandles
std::vector< DataObjectHandle< DataObject > * > m_inputHandles
Definition: CPUCruncher.h:71
GaudiPython.Bindings.DataObject
DataObject
Definition: Bindings.py:50
std::vector::size
T size(T...args)
std::vector< unsigned int >
CommonMessagingBase::debug
MsgStream & debug() const
shortcut for the method msgStream(MSG::DEBUG)
Definition: CommonMessaging.h:127
std::vector::back
T back(T...args)
CommonMessagingBase::msgSvc
SmartIF< IMessageSvc > & msgSvc() const
The standard message service.
Definition: CommonMessaging.h:73
Gaudi::DataHandle::Writer
Definition: DataHandle.h:32
std::hex
T hex(T...args)
MSG::ERROR
Definition: IMessageSvc.h:21
CPUCruncher::m_outKeys
std::vector< std::string > m_outKeys
Definition: CPUCruncher.h:74
CPUCruncher::m_rwRepetitions
unsigned int m_rwRepetitions
Definition: CPUCruncher.h:76
CPUCruncher::m_inpKeys
std::vector< std::string > m_inpKeys
Definition: CPUCruncher.h:74
MSG::INFO
Definition: IMessageSvc.h:19
CPUCruncher::m_local_rndm_gen
bool m_local_rndm_gen
Definition: CPUCruncher.h:59
CPUCruncher::m_outputHandles
std::vector< DataObjectHandle< DataObject > * > m_outputHandles
Definition: CPUCruncher.h:72
DataObject
A DataObject is the base class of any identifiable object on any data store.
Definition: DataObject.h:30
ana.i
list i
Definition: ana.py:128
CPUCruncher::m_var_runtime
double m_var_runtime
Definition: CPUCruncher.h:58
CPUCruncher::CHM
tbb::concurrent_hash_map< std::string, unsigned int > CHM
Definition: CPUCruncher.h:24
endmsg
MsgStream & endmsg(MsgStream &s)
MsgStream Modifier: endmsg. Calls the output method of the MsgStream.
Definition: MsgStream.h:244
CPUCruncher
Definition: CPUCruncher.py:1
HiveNumbers.h