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41 * Authors: Nathan Binkert
46 * Declaration of Statistics objects.
52 * Generalized N-dimensinal vector
56 * -- these both can use the same function that prints out a
57 * specific set of stats
58 * VectorStandardDeviation totals
61 #ifndef __BASE_STATISTICS_HH__
62 #define __BASE_STATISTICS_HH__
78 #include "base/stats/group.hh"
79 #include "base/stats/info.hh"
80 #include "base/stats/output.hh"
81 #include "base/stats/types.hh"
82 #include "base/cast.hh"
83 #include "base/cprintf.hh"
84 #include "base/intmath.hh"
85 #include "base/str.hh"
86 #include "base/types.hh"
90 /** The current simulated tick. */
91 extern Tick curTick();
93 /* A namespace for all of the Statistics */
96 template <class Stat, class Base>
97 class InfoProxy : public Base
103 InfoProxy(Stat &stat) : s(stat) {}
105 bool check() const { return s.check(); }
106 void prepare() { s.prepare(); }
107 void reset() { s.reset(); }
109 visit(Output &visitor)
111 visitor.visit(*static_cast<Base *>(this));
113 bool zero() const { return s.zero(); }
116 template <class Stat>
117 class ScalarInfoProxy : public InfoProxy<Stat, ScalarInfo>
120 ScalarInfoProxy(Stat &stat) : InfoProxy<Stat, ScalarInfo>(stat) {}
122 Counter value() const { return this->s.value(); }
123 Result result() const { return this->s.result(); }
124 Result total() const { return this->s.total(); }
127 template <class Stat>
128 class VectorInfoProxy : public InfoProxy<Stat, VectorInfo>
131 mutable VCounter cvec;
132 mutable VResult rvec;
135 VectorInfoProxy(Stat &stat) : InfoProxy<Stat, VectorInfo>(stat) {}
137 size_type size() const { return this->s.size(); }
149 this->s.result(rvec);
153 Result total() const { return this->s.total(); }
156 template <class Stat>
157 class DistInfoProxy : public InfoProxy<Stat, DistInfo>
160 DistInfoProxy(Stat &stat) : InfoProxy<Stat, DistInfo>(stat) {}
163 template <class Stat>
164 class VectorDistInfoProxy : public InfoProxy<Stat, VectorDistInfo>
167 VectorDistInfoProxy(Stat &stat) : InfoProxy<Stat, VectorDistInfo>(stat) {}
169 size_type size() const { return this->s.size(); }
172 template <class Stat>
173 class Vector2dInfoProxy : public InfoProxy<Stat, Vector2dInfo>
176 Vector2dInfoProxy(Stat &stat) : InfoProxy<Stat, Vector2dInfo>(stat) {}
178 Result total() const { return this->s.total(); }
183 virtual ~StorageParams();
192 /** Set up an info class for this statistic */
193 void setInfo(Group *parent, Info *info);
194 /** Save Storage class parameters if any */
195 void setParams(const StorageParams *params);
196 /** Save Storage class parameters if any */
199 /** Grab the information class for this statistic */
201 /** Grab the information class for this statistic */
202 const Info *info() const;
209 * Reset the stat to the default state.
214 * @return true if this stat has a value and satisfies its
215 * requirement as a prereq
217 bool zero() const { return true; }
220 * Check that this stat has been set up properly and is ready for
222 * @return true for success
224 bool check() const { return true; }
227 template <class Derived, template <class> class InfoProxyType>
228 class DataWrap : public InfoAccess
231 typedef InfoProxyType<Derived> Info;
234 Derived &self() { return *static_cast<Derived *>(this); }
240 return safe_cast<Info *>(InfoAccess::info());
247 return safe_cast<const Info *>(InfoAccess::info());
252 DataWrap(const DataWrap &) = delete;
253 DataWrap &operator=(const DataWrap &) = delete;
256 DataWrap(Group *parent, const char *name, const char *desc)
258 auto info = new Info(self());
259 this->setInfo(parent, info);
262 parent->addStat(info);
266 info->flags.set(display);
274 * Set the name and marks this stat to print at the end of simulation.
275 * @param name The new name.
276 * @return A reference to this stat.
279 name(const std::string &name)
281 Info *info = this->info();
283 info->flags.set(display);
286 const std::string &name() const { return this->info()->name; }
289 * Set the character(s) used between the name and vector number
290 * on vectors, dist, etc.
291 * @param _sep The new separator string
292 * @return A reference to this stat.
295 setSeparator(const std::string &_sep)
297 this->info()->setSeparator(_sep);
300 const std::string &setSeparator() const
302 return this->info()->separatorString;
306 * Set the description and marks this stat to print at the end of
308 * @param desc The new description.
309 * @return A reference to this stat.
312 desc(const std::string &_desc)
314 this->info()->desc = _desc;
319 * Set the precision and marks this stat to print at the end of simulation.
320 * @param _precision The new precision
321 * @return A reference to this stat.
324 precision(int _precision)
326 this->info()->precision = _precision;
331 * Set the flags and marks this stat to print at the end of simulation.
332 * @param f The new flags.
333 * @return A reference to this stat.
338 this->info()->flags.set(_flags);
343 * Set the prerequisite stat and marks this stat to print at the end of
345 * @param prereq The prerequisite stat.
346 * @return A reference to this stat.
348 template <class Stat>
350 prereq(const Stat &prereq)
352 this->info()->prereq = prereq.info();
357 template <class Derived, template <class> class InfoProxyType>
358 class DataWrapVec : public DataWrap<Derived, InfoProxyType>
361 typedef InfoProxyType<Derived> Info;
363 DataWrapVec(Group *parent = nullptr, const char *name = nullptr,
364 const char *desc = nullptr)
365 : DataWrap<Derived, InfoProxyType>(parent, name, desc)
368 // The following functions are specific to vectors. If you use them
369 // in a non vector context, you will get a nice compiler error!
372 * Set the subfield name for the given index, and marks this stat to print
373 * at the end of simulation.
374 * @param index The subfield index.
375 * @param name The new name of the subfield.
376 * @return A reference to this stat.
379 subname(off_type index, const std::string &name)
381 Derived &self = this->self();
382 Info *info = self.info();
384 std::vector<std::string> &subn = info->subnames;
385 if (subn.size() <= index)
386 subn.resize(index + 1);
391 // The following functions are specific to 2d vectors. If you use
392 // them in a non vector context, you will get a nice compiler
393 // error because info doesn't have the right variables.
396 * Set the subfield description for the given index and marks this stat to
397 * print at the end of simulation.
398 * @param index The subfield index.
399 * @param desc The new description of the subfield
400 * @return A reference to this stat.
403 subdesc(off_type index, const std::string &desc)
405 Info *info = this->info();
407 std::vector<std::string> &subd = info->subdescs;
408 if (subd.size() <= index)
409 subd.resize(index + 1);
418 Derived &self = this->self();
419 Info *info = this->info();
421 size_t size = self.size();
422 for (off_type i = 0; i < size; ++i)
423 self.data(i)->prepare(info);
429 Derived &self = this->self();
430 Info *info = this->info();
432 size_t size = self.size();
433 for (off_type i = 0; i < size; ++i)
434 self.data(i)->reset(info);
438 template <class Derived, template <class> class InfoProxyType>
439 class DataWrapVec2d : public DataWrapVec<Derived, InfoProxyType>
442 typedef InfoProxyType<Derived> Info;
444 DataWrapVec2d(Group *parent, const char *name, const char *desc)
445 : DataWrapVec<Derived, InfoProxyType>(parent, name, desc)
450 * @warning This makes the assumption that if you're gonna subnames a 2d
451 * vector, you're subnaming across all y
454 ysubnames(const char **names)
456 Derived &self = this->self();
457 Info *info = this->info();
459 info->y_subnames.resize(self.y);
460 for (off_type i = 0; i < self.y; ++i)
461 info->y_subnames[i] = names[i];
466 ysubname(off_type index, const std::string &subname)
468 Derived &self = this->self();
469 Info *info = this->info();
471 assert(index < self.y);
472 info->y_subnames.resize(self.y);
473 info->y_subnames[index] = subname.c_str();
478 ysubname(off_type i) const
480 return this->info()->y_subnames[i];
485 //////////////////////////////////////////////////////////////////////
489 //////////////////////////////////////////////////////////////////////
492 * Templatized storage and interface for a simple scalar stat.
497 /** The statistic value. */
501 struct Params : public StorageParams {};
505 * Builds this storage element and calls the base constructor of the
513 * The the stat to the given value.
514 * @param val The new value.
516 void set(Counter val) { data = val; }
518 * Increment the stat by the given value.
519 * @param val The new value.
521 void inc(Counter val) { data += val; }
523 * Decrement the stat by the given value.
524 * @param val The new value.
526 void dec(Counter val) { data -= val; }
528 * Return the value of this stat as its base type.
529 * @return The value of this stat.
531 Counter value() const { return data; }
533 * Return the value of this stat as a result type.
534 * @return The value of this stat.
536 Result result() const { return (Result)data; }
538 * Prepare stat data for dumping or serialization
540 void prepare(Info *info) { }
542 * Reset stat value to default
544 void reset(Info *info) { data = Counter(); }
547 * @return true if zero value
549 bool zero() const { return data == Counter(); }
553 * Templatized storage and interface to a per-tick average stat. This keeps
554 * a current count and updates a total (count * ticks) when this count
555 * changes. This allows the quick calculation of a per tick count of the item
556 * being watched. This is good for keeping track of residencies in structures
557 * among other things.
562 /** The current count. */
564 /** The tick of the last reset */
566 /** The total count for all tick. */
567 mutable Result total;
568 /** The tick that current last changed. */
572 struct Params : public StorageParams {};
576 * Build and initializes this stat storage.
579 : current(0), lastReset(0), total(0), last(0)
583 * Set the current count to the one provided, update the total and last
585 * @param val The new count.
590 total += current * (curTick() - last);
596 * Increment the current count by the provided value, calls set.
597 * @param val The amount to increment.
599 void inc(Counter val) { set(current + val); }
602 * Deccrement the current count by the provided value, calls set.
603 * @param val The amount to decrement.
605 void dec(Counter val) { set(current - val); }
608 * Return the current count.
609 * @return The current count.
611 Counter value() const { return current; }
614 * Return the current average.
615 * @return The current average.
620 assert(last == curTick());
621 return (Result)(total + current) / (Result)(curTick() - lastReset + 1);
625 * @return true if zero value
627 bool zero() const { return total == 0.0; }
630 * Prepare stat data for dumping or serialization
635 total += current * (curTick() - last);
640 * Reset stat value to default
647 lastReset = curTick();
653 * Implementation of a scalar stat. The type of stat is determined by the
656 template <class Derived, class Stor>
657 class ScalarBase : public DataWrap<Derived, ScalarInfoProxy>
660 typedef Stor Storage;
661 typedef typename Stor::Params Params;
664 /** The storage of this stat. */
665 char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
669 * Retrieve the storage.
670 * @param index The vector index to access.
671 * @return The storage object at the given index.
676 return reinterpret_cast<Storage *>(storage);
680 * Retrieve a const pointer to the storage.
681 * for the given index.
682 * @param index The vector index to access.
683 * @return A const pointer to the storage object at the given index.
688 return reinterpret_cast<const Storage *>(storage);
694 new (storage) Storage(this->info());
700 * Return the current value of this stat as its base type.
701 * @return The current value.
703 Counter value() const { return data()->value(); }
706 ScalarBase(Group *parent = nullptr, const char *name = nullptr,
707 const char *desc = nullptr)
708 : DataWrap<Derived, ScalarInfoProxy>(parent, name, desc)
714 // Common operators for stats
716 * Increment the stat by 1. This calls the associated storage object inc
719 void operator++() { data()->inc(1); }
721 * Decrement the stat by 1. This calls the associated storage object dec
724 void operator--() { data()->dec(1); }
726 /** Increment the stat by 1. */
727 void operator++(int) { ++*this; }
728 /** Decrement the stat by 1. */
729 void operator--(int) { --*this; }
732 * Set the data value to the given value. This calls the associated storage
733 * object set function.
734 * @param v The new value.
736 template <typename U>
737 void operator=(const U &v) { data()->set(v); }
740 * Increment the stat by the given value. This calls the associated
741 * storage object inc function.
742 * @param v The value to add.
744 template <typename U>
745 void operator+=(const U &v) { data()->inc(v); }
748 * Decrement the stat by the given value. This calls the associated
749 * storage object dec function.
750 * @param v The value to substract.
752 template <typename U>
753 void operator-=(const U &v) { data()->dec(v); }
756 * Return the number of elements, always 1 for a scalar.
759 size_type size() const { return 1; }
761 Counter value() { return data()->value(); }
763 Result result() { return data()->result(); }
765 Result total() { return result(); }
767 bool zero() { return result() == 0.0; }
769 void reset() { data()->reset(this->info()); }
770 void prepare() { data()->prepare(this->info()); }
773 class ProxyInfo : public ScalarInfo
776 std::string str() const { return std::to_string(value()); }
777 size_type size() const { return 1; }
778 bool check() const { return true; }
781 bool zero() const { return value() == 0; }
783 void visit(Output &visitor) { visitor.visit(*this); }
787 class ValueProxy : public ProxyInfo
793 ValueProxy(T &val) : scalar(&val) {}
794 Counter value() const { return *scalar; }
795 Result result() const { return *scalar; }
796 Result total() const { return *scalar; }
800 class FunctorProxy : public ProxyInfo
806 FunctorProxy(T &func) : functor(&func) {}
807 Counter value() const { return (*functor)(); }
808 Result result() const { return (*functor)(); }
809 Result total() const { return (*functor)(); }
813 * A proxy similar to the FunctorProxy, but allows calling a method of a bound
814 * object, instead of a global free-standing function.
816 template <class T, class V>
817 class MethodProxy : public ProxyInfo
821 typedef V (T::*MethodPointer) () const;
822 MethodPointer method;
825 MethodProxy(T *obj, MethodPointer meth) : object(obj), method(meth) {}
826 Counter value() const { return (object->*method)(); }
827 Result result() const { return (object->*method)(); }
828 Result total() const { return (object->*method)(); }
831 template <class Derived>
832 class ValueBase : public DataWrap<Derived, ScalarInfoProxy>
838 ValueBase(Group *parent, const char *name, const char *desc)
839 : DataWrap<Derived, ScalarInfoProxy>(parent, name, desc),
844 ~ValueBase() { if (proxy) delete proxy; }
850 proxy = new ValueProxy<T>(value);
859 proxy = new FunctorProxy<T>(func);
865 * Extended functor that calls the specified method of the provided object.
867 * @param obj Pointer to the object whose method should be called.
868 * @param method Pointer of the function / method of the object.
869 * @return Updated stats item.
871 template <class T, class V>
873 method(T *obj, V (T::*method)() const)
875 proxy = new MethodProxy<T,V>(obj, method);
880 Counter value() { return proxy->value(); }
881 Result result() const { return proxy->result(); }
882 Result total() const { return proxy->total(); };
883 size_type size() const { return proxy->size(); }
885 std::string str() const { return proxy->str(); }
886 bool zero() const { return proxy->zero(); }
887 bool check() const { return proxy != NULL; }
892 //////////////////////////////////////////////////////////////////////
896 //////////////////////////////////////////////////////////////////////
899 * A proxy class to access the stat at a given index in a VectorBase stat.
900 * Behaves like a ScalarBase.
902 template <class Stat>
906 /** Pointer to the parent Vector. */
909 /** The index to access in the parent VectorBase. */
914 * Return the current value of this stat as its base type.
915 * @return The current value.
917 Counter value() const { return stat.data(index)->value(); }
920 * Return the current value of this statas a result type.
921 * @return The current value.
923 Result result() const { return stat.data(index)->result(); }
927 * Create and initialize this proxy, do not register it with the database.
928 * @param i The index to access.
930 ScalarProxy(Stat &s, off_type i)
936 * Create a copy of the provided ScalarProxy.
937 * @param sp The proxy to copy.
939 ScalarProxy(const ScalarProxy &sp)
940 : stat(sp.stat), index(sp.index)
944 * Set this proxy equal to the provided one.
945 * @param sp The proxy to copy.
946 * @return A reference to this proxy.
949 operator=(const ScalarProxy &sp)
957 // Common operators for stats
959 * Increment the stat by 1. This calls the associated storage object inc
962 void operator++() { stat.data(index)->inc(1); }
964 * Decrement the stat by 1. This calls the associated storage object dec
967 void operator--() { stat.data(index)->dec(1); }
969 /** Increment the stat by 1. */
970 void operator++(int) { ++*this; }
971 /** Decrement the stat by 1. */
972 void operator--(int) { --*this; }
975 * Set the data value to the given value. This calls the associated storage
976 * object set function.
977 * @param v The new value.
979 template <typename U>
981 operator=(const U &v)
983 stat.data(index)->set(v);
987 * Increment the stat by the given value. This calls the associated
988 * storage object inc function.
989 * @param v The value to add.
991 template <typename U>
993 operator+=(const U &v)
995 stat.data(index)->inc(v);
999 * Decrement the stat by the given value. This calls the associated
1000 * storage object dec function.
1001 * @param v The value to substract.
1003 template <typename U>
1005 operator-=(const U &v)
1007 stat.data(index)->dec(v);
1011 * Return the number of elements, always 1 for a scalar.
1014 size_type size() const { return 1; }
1020 return csprintf("%s[%d]", stat.info()->name, index);
1025 * Implementation of a vector of stats. The type of stat is determined by the
1026 * Storage class. @sa ScalarBase
1028 template <class Derived, class Stor>
1029 class VectorBase : public DataWrapVec<Derived, VectorInfoProxy>
1032 typedef Stor Storage;
1033 typedef typename Stor::Params Params;
1036 typedef ScalarProxy<Derived> Proxy;
1037 friend class ScalarProxy<Derived>;
1038 friend class DataWrapVec<Derived, VectorInfoProxy>;
1041 /** The storage of this stat. */
1047 * Retrieve the storage.
1048 * @param index The vector index to access.
1049 * @return The storage object at the given index.
1051 Storage *data(off_type index) { return &storage[index]; }
1054 * Retrieve a const pointer to the storage.
1055 * @param index The vector index to access.
1056 * @return A const pointer to the storage object at the given index.
1058 const Storage *data(off_type index) const { return &storage[index]; }
1063 assert(s > 0 && "size must be positive!");
1064 assert(!storage && "already initialized");
1067 char *ptr = new char[_size * sizeof(Storage)];
1068 storage = reinterpret_cast<Storage *>(ptr);
1070 for (off_type i = 0; i < _size; ++i)
1071 new (&storage[i]) Storage(this->info());
1078 value(VCounter &vec) const
1081 for (off_type i = 0; i < size(); ++i)
1082 vec[i] = data(i)->value();
1086 * Copy the values to a local vector and return a reference to it.
1087 * @return A reference to a vector of the stat values.
1090 result(VResult &vec) const
1093 for (off_type i = 0; i < size(); ++i)
1094 vec[i] = data(i)->result();
1098 * Return a total of all entries in this vector.
1099 * @return The total of all vector entries.
1105 for (off_type i = 0; i < size(); ++i)
1106 total += data(i)->result();
1111 * @return the number of elements in this vector.
1113 size_type size() const { return _size; }
1118 for (off_type i = 0; i < size(); ++i)
1119 if (data(i)->zero())
1127 return storage != NULL;
1131 VectorBase(Group *parent, const char *name, const char *desc)
1132 : DataWrapVec<Derived, VectorInfoProxy>(parent, name, desc),
1133 storage(nullptr), _size(0)
1141 for (off_type i = 0; i < _size; ++i)
1142 data(i)->~Storage();
1143 delete [] reinterpret_cast<char *>(storage);
1147 * Set this vector to have the given size.
1148 * @param size The new size.
1149 * @return A reference to this stat.
1152 init(size_type size)
1154 Derived &self = this->self();
1160 * Return a reference (ScalarProxy) to the stat at the given index.
1161 * @param index The vector index to access.
1162 * @return A reference of the stat.
1165 operator[](off_type index)
1167 assert (index >= 0 && index < size());
1168 return Proxy(this->self(), index);
1172 template <class Stat>
1181 mutable VResult vec;
1183 typename Stat::Storage *
1184 data(off_type index)
1186 assert(index < len);
1187 return stat.data(offset + index);
1190 const typename Stat::Storage *
1191 data(off_type index) const
1193 assert(index < len);
1194 return stat.data(offset + index);
1203 for (off_type i = 0; i < size(); ++i)
1204 vec[i] = data(i)->result();
1213 for (off_type i = 0; i < size(); ++i)
1214 total += data(i)->result();
1219 VectorProxy(Stat &s, off_type o, size_type l)
1220 : stat(s), offset(o), len(l)
1224 VectorProxy(const VectorProxy &sp)
1225 : stat(sp.stat), offset(sp.offset), len(sp.len)
1230 operator=(const VectorProxy &sp)
1239 operator[](off_type index)
1241 assert (index >= 0 && index < size());
1242 return ScalarProxy<Stat>(stat, offset + index);
1245 size_type size() const { return len; }
1248 template <class Derived, class Stor>
1249 class Vector2dBase : public DataWrapVec2d<Derived, Vector2dInfoProxy>
1252 typedef Vector2dInfoProxy<Derived> Info;
1253 typedef Stor Storage;
1254 typedef typename Stor::Params Params;
1255 typedef VectorProxy<Derived> Proxy;
1256 friend class ScalarProxy<Derived>;
1257 friend class VectorProxy<Derived>;
1258 friend class DataWrapVec<Derived, Vector2dInfoProxy>;
1259 friend class DataWrapVec2d<Derived, Vector2dInfoProxy>;
1268 Storage *data(off_type index) { return &storage[index]; }
1269 const Storage *data(off_type index) const { return &storage[index]; }
1272 Vector2dBase(Group *parent, const char *name, const char *desc)
1273 : DataWrapVec2d<Derived, Vector2dInfoProxy>(parent, name, desc),
1274 x(0), y(0), _size(0), storage(nullptr)
1282 for (off_type i = 0; i < _size; ++i)
1283 data(i)->~Storage();
1284 delete [] reinterpret_cast<char *>(storage);
1288 init(size_type _x, size_type _y)
1290 assert(_x > 0 && _y > 0 && "sizes must be positive!");
1291 assert(!storage && "already initialized");
1293 Derived &self = this->self();
1294 Info *info = this->info();
1302 char *ptr = new char[_size * sizeof(Storage)];
1303 storage = reinterpret_cast<Storage *>(ptr);
1305 for (off_type i = 0; i < _size; ++i)
1306 new (&storage[i]) Storage(info);
1314 operator[](off_type index)
1316 off_type offset = index * y;
1317 assert (index >= 0 && offset + y <= size());
1318 return Proxy(this->self(), offset, y);
1331 return data(0)->zero();
1335 * Return a total of all entries in this vector.
1336 * @return The total of all vector entries.
1342 for (off_type i = 0; i < size(); ++i)
1343 total += data(i)->result();
1350 Info *info = this->info();
1351 size_type size = this->size();
1353 for (off_type i = 0; i < size; ++i)
1354 data(i)->prepare(info);
1356 info->cvec.resize(size);
1357 for (off_type i = 0; i < size; ++i)
1358 info->cvec[i] = data(i)->value();
1362 * Reset stat value to default
1367 Info *info = this->info();
1368 size_type size = this->size();
1369 for (off_type i = 0; i < size; ++i)
1370 data(i)->reset(info);
1376 return storage != NULL;
1380 //////////////////////////////////////////////////////////////////////
1382 // Non formula statistics
1384 //////////////////////////////////////////////////////////////////////
1385 /** The parameters for a distribution stat. */
1386 struct DistParams : public StorageParams
1388 const DistType type;
1389 DistParams(DistType t) : type(t) {}
1393 * Templatized storage and interface for a distribution stat.
1398 /** The parameters for a distribution stat. */
1399 struct Params : public DistParams
1401 /** The minimum value to track. */
1403 /** The maximum value to track. */
1405 /** The number of entries in each bucket. */
1406 Counter bucket_size;
1407 /** The number of buckets. Equal to (max-min)/bucket_size. */
1410 Params() : DistParams(Dist), min(0), max(0), bucket_size(0),
1415 /** The minimum value to track. */
1417 /** The maximum value to track. */
1419 /** The number of entries in each bucket. */
1420 Counter bucket_size;
1422 /** The smallest value sampled. */
1424 /** The largest value sampled. */
1426 /** The number of values sampled less than min. */
1428 /** The number of values sampled more than max. */
1430 /** The current sum. */
1432 /** The sum of squares. */
1434 /** The number of samples. */
1436 /** Counter for each bucket. */
1440 DistStor(Info *info)
1441 : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1447 * Add a value to the distribution for the given number of times.
1448 * @param val The value to add.
1449 * @param number The number of times to add the value.
1452 sample(Counter val, int number)
1454 if (val < min_track)
1455 underflow += number;
1456 else if (val > max_track)
1460 (size_type)std::floor((val - min_track) / bucket_size);
1461 assert(index < size());
1462 cvec[index] += number;
1471 sum += val * number;
1472 squares += val * val * number;
1477 * Return the number of buckets in this distribution.
1478 * @return the number of buckets.
1480 size_type size() const { return cvec.size(); }
1483 * Returns true if any calls to sample have been made.
1484 * @return True if any values have been sampled.
1489 return samples == Counter();
1493 prepare(Info *info, DistData &data)
1495 const Params *params = safe_cast<const Params *>(info->storageParams);
1497 assert(params->type == Dist);
1498 data.type = params->type;
1499 data.min = params->min;
1500 data.max = params->max;
1501 data.bucket_size = params->bucket_size;
1503 data.min_val = (min_val == CounterLimits::max()) ? 0 : min_val;
1504 data.max_val = (max_val == CounterLimits::min()) ? 0 : max_val;
1505 data.underflow = underflow;
1506 data.overflow = overflow;
1508 data.cvec.resize(params->buckets);
1509 for (off_type i = 0; i < params->buckets; ++i)
1510 data.cvec[i] = cvec[i];
1513 data.squares = squares;
1514 data.samples = samples;
1518 * Reset stat value to default
1523 const Params *params = safe_cast<const Params *>(info->storageParams);
1524 min_track = params->min;
1525 max_track = params->max;
1526 bucket_size = params->bucket_size;
1528 min_val = CounterLimits::max();
1529 max_val = CounterLimits::min();
1530 underflow = Counter();
1531 overflow = Counter();
1533 size_type size = cvec.size();
1534 for (off_type i = 0; i < size; ++i)
1535 cvec[i] = Counter();
1538 squares = Counter();
1539 samples = Counter();
1544 * Templatized storage and interface for a histogram stat.
1549 /** The parameters for a distribution stat. */
1550 struct Params : public DistParams
1552 /** The number of buckets.. */
1555 Params() : DistParams(Hist), buckets(0) {}
1559 /** The minimum value to track. */
1561 /** The maximum value to track. */
1563 /** The number of entries in each bucket. */
1564 Counter bucket_size;
1566 /** The current sum. */
1568 /** The sum of logarithm of each sample, used to compute geometric mean. */
1570 /** The sum of squares. */
1572 /** The number of samples. */
1574 /** Counter for each bucket. */
1578 HistStor(Info *info)
1579 : cvec(safe_cast<const Params *>(info->storageParams)->buckets)
1586 void grow_convert();
1587 void add(HistStor *);
1590 * Add a value to the distribution for the given number of times.
1591 * @param val The value to add.
1592 * @param number The number of times to add the value.
1595 sample(Counter val, int number)
1597 assert(min_bucket < max_bucket);
1598 if (val < min_bucket) {
1599 if (min_bucket == 0)
1602 while (val < min_bucket)
1604 } else if (val >= max_bucket + bucket_size) {
1605 if (min_bucket == 0) {
1606 while (val >= max_bucket + bucket_size)
1609 while (val >= max_bucket + bucket_size)
1615 (int64_t)std::floor((val - min_bucket) / bucket_size);
1617 assert(index < size());
1618 cvec[index] += number;
1620 sum += val * number;
1621 squares += val * val * number;
1622 logs += log(val) * number;
1627 * Return the number of buckets in this distribution.
1628 * @return the number of buckets.
1630 size_type size() const { return cvec.size(); }
1633 * Returns true if any calls to sample have been made.
1634 * @return True if any values have been sampled.
1639 return samples == Counter();
1643 prepare(Info *info, DistData &data)
1645 const Params *params = safe_cast<const Params *>(info->storageParams);
1647 assert(params->type == Hist);
1648 data.type = params->type;
1649 data.min = min_bucket;
1650 data.max = max_bucket + bucket_size - 1;
1651 data.bucket_size = bucket_size;
1653 data.min_val = min_bucket;
1654 data.max_val = max_bucket;
1656 int buckets = params->buckets;
1657 data.cvec.resize(buckets);
1658 for (off_type i = 0; i < buckets; ++i)
1659 data.cvec[i] = cvec[i];
1663 data.squares = squares;
1664 data.samples = samples;
1668 * Reset stat value to default
1673 const Params *params = safe_cast<const Params *>(info->storageParams);
1675 max_bucket = params->buckets - 1;
1678 size_type size = cvec.size();
1679 for (off_type i = 0; i < size; ++i)
1680 cvec[i] = Counter();
1683 squares = Counter();
1684 samples = Counter();
1690 * Templatized storage and interface for a distribution that calculates mean
1696 struct Params : public DistParams
1698 Params() : DistParams(Deviation) {}
1702 /** The current sum. */
1704 /** The sum of squares. */
1706 /** The number of samples. */
1711 * Create and initialize this storage.
1713 SampleStor(Info *info)
1714 : sum(Counter()), squares(Counter()), samples(Counter())
1718 * Add a value the given number of times to this running average.
1719 * Update the running sum and sum of squares, increment the number of
1720 * values seen by the given number.
1721 * @param val The value to add.
1722 * @param number The number of times to add the value.
1725 sample(Counter val, int number)
1727 Counter value = val * number;
1729 squares += value * value;
1734 * Return the number of entries in this stat, 1
1737 size_type size() const { return 1; }
1740 * Return true if no samples have been added.
1741 * @return True if no samples have been added.
1743 bool zero() const { return samples == Counter(); }
1746 prepare(Info *info, DistData &data)
1748 const Params *params = safe_cast<const Params *>(info->storageParams);
1750 assert(params->type == Deviation);
1751 data.type = params->type;
1753 data.squares = squares;
1754 data.samples = samples;
1758 * Reset stat value to default
1764 squares = Counter();
1765 samples = Counter();
1770 * Templatized storage for distribution that calculates per tick mean and
1776 struct Params : public DistParams
1778 Params() : DistParams(Deviation) {}
1782 /** Current total. */
1784 /** Current sum of squares. */
1789 * Create and initialize this storage.
1791 AvgSampleStor(Info *info)
1792 : sum(Counter()), squares(Counter())
1796 * Add a value to the distribution for the given number of times.
1797 * Update the running sum and sum of squares.
1798 * @param val The value to add.
1799 * @param number The number of times to add the value.
1802 sample(Counter val, int number)
1804 Counter value = val * number;
1806 squares += value * value;
1810 * Return the number of entries, in this case 1.
1813 size_type size() const { return 1; }
1816 * Return true if no samples have been added.
1817 * @return True if the sum is zero.
1819 bool zero() const { return sum == Counter(); }
1822 prepare(Info *info, DistData &data)
1824 const Params *params = safe_cast<const Params *>(info->storageParams);
1826 assert(params->type == Deviation);
1827 data.type = params->type;
1829 data.squares = squares;
1830 data.samples = curTick();
1834 * Reset stat value to default
1840 squares = Counter();
1845 * Implementation of a distribution stat. The type of distribution is
1846 * determined by the Storage template. @sa ScalarBase
1848 template <class Derived, class Stor>
1849 class DistBase : public DataWrap<Derived, DistInfoProxy>
1852 typedef DistInfoProxy<Derived> Info;
1853 typedef Stor Storage;
1854 typedef typename Stor::Params Params;
1857 /** The storage for this stat. */
1858 char storage[sizeof(Storage)] __attribute__ ((aligned (8)));
1862 * Retrieve the storage.
1863 * @return The storage object for this stat.
1868 return reinterpret_cast<Storage *>(storage);
1872 * Retrieve a const pointer to the storage.
1873 * @return A const pointer to the storage object for this stat.
1878 return reinterpret_cast<const Storage *>(storage);
1884 new (storage) Storage(this->info());
1889 DistBase(Group *parent, const char *name, const char *desc)
1890 : DataWrap<Derived, DistInfoProxy>(parent, name, desc)
1895 * Add a value to the distribtion n times. Calls sample on the storage
1897 * @param v The value to add.
1898 * @param n The number of times to add it, defaults to 1.
1900 template <typename U>
1901 void sample(const U &v, int n = 1) { data()->sample(v, n); }
1904 * Return the number of entries in this stat.
1905 * @return The number of entries.
1907 size_type size() const { return data()->size(); }
1909 * Return true if no samples have been added.
1910 * @return True if there haven't been any samples.
1912 bool zero() const { return data()->zero(); }
1917 Info *info = this->info();
1918 data()->prepare(info, info->data);
1922 * Reset stat value to default
1927 data()->reset(this->info());
1931 * Add the argument distribution to the this distribution.
1933 void add(DistBase &d) { data()->add(d.data()); }
1937 template <class Stat>
1940 template <class Derived, class Stor>
1941 class VectorDistBase : public DataWrapVec<Derived, VectorDistInfoProxy>
1944 typedef VectorDistInfoProxy<Derived> Info;
1945 typedef Stor Storage;
1946 typedef typename Stor::Params Params;
1947 typedef DistProxy<Derived> Proxy;
1948 friend class DistProxy<Derived>;
1949 friend class DataWrapVec<Derived, VectorDistInfoProxy>;
1957 data(off_type index)
1959 return &storage[index];
1963 data(off_type index) const
1965 return &storage[index];
1971 assert(s > 0 && "size must be positive!");
1972 assert(!storage && "already initialized");
1975 char *ptr = new char[_size * sizeof(Storage)];
1976 storage = reinterpret_cast<Storage *>(ptr);
1978 Info *info = this->info();
1979 for (off_type i = 0; i < _size; ++i)
1980 new (&storage[i]) Storage(info);
1986 VectorDistBase(Group *parent, const char *name, const char *desc)
1987 : DataWrapVec<Derived, VectorDistInfoProxy>(parent, name, desc),
1996 for (off_type i = 0; i < _size; ++i)
1997 data(i)->~Storage();
1998 delete [] reinterpret_cast<char *>(storage);
2001 Proxy operator[](off_type index)
2003 assert(index >= 0 && index < size());
2004 return Proxy(this->self(), index);
2016 for (off_type i = 0; i < size(); ++i)
2017 if (!data(i)->zero())
2025 Info *info = this->info();
2026 size_type size = this->size();
2027 info->data.resize(size);
2028 for (off_type i = 0; i < size; ++i)
2029 data(i)->prepare(info, info->data[i]);
2035 return storage != NULL;
2039 template <class Stat>
2047 typename Stat::Storage *data() { return stat.data(index); }
2048 const typename Stat::Storage *data() const { return stat.data(index); }
2051 DistProxy(Stat &s, off_type i)
2055 DistProxy(const DistProxy &sp)
2056 : stat(sp.stat), index(sp.index)
2060 operator=(const DistProxy &sp)
2068 template <typename U>
2070 sample(const U &v, int n = 1)
2072 data()->sample(v, n);
2084 return data()->zero();
2088 * Proxy has no state. Nothing to reset.
2093 //////////////////////////////////////////////////////////////////////
2097 //////////////////////////////////////////////////////////////////////
2100 * Base class for formula statistic node. These nodes are used to build a tree
2101 * that represents the formula.
2107 * Return the number of nodes in the subtree starting at this node.
2108 * @return the number of nodes in this subtree.
2110 virtual size_type size() const = 0;
2112 * Return the result vector of this subtree.
2113 * @return The result vector of this subtree.
2115 virtual const VResult &result() const = 0;
2117 * Return the total of the result vector.
2118 * @return The total of the result vector.
2120 virtual Result total() const = 0;
2125 virtual std::string str() const = 0;
2130 /** Shared pointer to a function Node. */
2131 typedef std::shared_ptr<Node> NodePtr;
2133 class ScalarStatNode : public Node
2136 const ScalarInfo *data;
2137 mutable VResult vresult;
2140 ScalarStatNode(const ScalarInfo *d) : data(d), vresult(1) {}
2145 vresult[0] = data->result();
2149 Result total() const { return data->result(); };
2151 size_type size() const { return 1; }
2156 std::string str() const { return data->name; }
2159 template <class Stat>
2160 class ScalarProxyNode : public Node
2163 const ScalarProxy<Stat> proxy;
2164 mutable VResult vresult;
2167 ScalarProxyNode(const ScalarProxy<Stat> &p)
2168 : proxy(p), vresult(1)
2174 vresult[0] = proxy.result();
2181 return proxy.result();
2200 class VectorStatNode : public Node
2203 const VectorInfo *data;
2206 VectorStatNode(const VectorInfo *d) : data(d) { }
2207 const VResult &result() const { return data->result(); }
2208 Result total() const { return data->total(); };
2210 size_type size() const { return data->size(); }
2212 std::string str() const { return data->name; }
2216 class ConstNode : public Node
2222 ConstNode(T s) : vresult(1, (Result)s) {}
2223 const VResult &result() const { return vresult; }
2224 Result total() const { return vresult[0]; };
2225 size_type size() const { return 1; }
2226 std::string str() const { return std::to_string(vresult[0]); }
2230 class ConstVectorNode : public Node
2236 ConstVectorNode(const T &s) : vresult(s.begin(), s.end()) {}
2237 const VResult &result() const { return vresult; }
2242 size_type size = this->size();
2244 for (off_type i = 0; i < size; i++)
2249 size_type size() const { return vresult.size(); }
2253 size_type size = this->size();
2254 std::string tmp = "(";
2255 for (off_type i = 0; i < size; i++)
2256 tmp += csprintf("%s ", std::to_string(vresult[i]));
2266 struct OpString<std::plus<Result> >
2268 static std::string str() { return "+"; }
2272 struct OpString<std::minus<Result> >
2274 static std::string str() { return "-"; }
2278 struct OpString<std::multiplies<Result> >
2280 static std::string str() { return "*"; }
2284 struct OpString<std::divides<Result> >
2286 static std::string str() { return "/"; }
2290 struct OpString<std::modulus<Result> >
2292 static std::string str() { return "%"; }
2296 struct OpString<std::negate<Result> >
2298 static std::string str() { return "-"; }
2302 class UnaryNode : public Node
2306 mutable VResult vresult;
2309 UnaryNode(NodePtr &p) : l(p) {}
2314 const VResult &lvec = l->result();
2315 size_type size = lvec.size();
2319 vresult.resize(size);
2321 for (off_type i = 0; i < size; ++i)
2322 vresult[i] = op(lvec[i]);
2330 const VResult &vec = this->result();
2332 for (off_type i = 0; i < size(); i++)
2337 size_type size() const { return l->size(); }
2342 return OpString<Op>::str() + l->str();
2347 class BinaryNode : public Node
2352 mutable VResult vresult;
2355 BinaryNode(NodePtr &a, NodePtr &b) : l(a), r(b) {}
2358 result() const override
2361 const VResult &lvec = l->result();
2362 const VResult &rvec = r->result();
2364 assert(lvec.size() > 0 && rvec.size() > 0);
2366 if (lvec.size() == 1 && rvec.size() == 1) {
2368 vresult[0] = op(lvec[0], rvec[0]);
2369 } else if (lvec.size() == 1) {
2370 size_type size = rvec.size();
2371 vresult.resize(size);
2372 for (off_type i = 0; i < size; ++i)
2373 vresult[i] = op(lvec[0], rvec[i]);
2374 } else if (rvec.size() == 1) {
2375 size_type size = lvec.size();
2376 vresult.resize(size);
2377 for (off_type i = 0; i < size; ++i)
2378 vresult[i] = op(lvec[i], rvec[0]);
2379 } else if (rvec.size() == lvec.size()) {
2380 size_type size = rvec.size();
2381 vresult.resize(size);
2382 for (off_type i = 0; i < size; ++i)
2383 vresult[i] = op(lvec[i], rvec[i]);
2390 total() const override
2392 const VResult &vec = this->result();
2393 const VResult &lvec = l->result();
2394 const VResult &rvec = r->result();
2400 assert(lvec.size() > 0 && rvec.size() > 0);
2401 assert(lvec.size() == rvec.size() ||
2402 lvec.size() == 1 || rvec.size() == 1);
2404 /** If vectors are the same divide their sums (x0+x1)/(y0+y1) */
2405 if (lvec.size() == rvec.size() && lvec.size() > 1) {
2406 for (off_type i = 0; i < size(); ++i) {
2410 return op(lsum, rsum);
2413 /** Otherwise divide each item by the divisor */
2414 for (off_type i = 0; i < size(); ++i) {
2422 size() const override
2424 size_type ls = l->size();
2425 size_type rs = r->size();
2428 } else if (rs == 1) {
2431 assert(ls == rs && "Node vector sizes are not equal");
2437 str() const override
2439 return csprintf("(%s %s %s)", l->str(), OpString<Op>::str(), r->str());
2444 class SumNode : public Node
2448 mutable VResult vresult;
2451 SumNode(NodePtr &p) : l(p), vresult(1) {}
2456 const VResult &lvec = l->result();
2457 size_type size = lvec.size();
2463 for (off_type i = 0; i < size; ++i)
2464 vresult[0] = op(vresult[0], lvec[i]);
2472 const VResult &lvec = l->result();
2473 size_type size = lvec.size();
2476 Result result = 0.0;
2479 for (off_type i = 0; i < size; ++i)
2480 result = op(result, lvec[i]);
2485 size_type size() const { return 1; }
2490 return csprintf("total(%s)", l->str());
2495 //////////////////////////////////////////////////////////////////////
2497 // Visible Statistics Types
2499 //////////////////////////////////////////////////////////////////////
2501 * @defgroup VisibleStats "Statistic Types"
2502 * These are the statistics that are used in the simulator.
2507 * This is a simple scalar statistic, like a counter.
2508 * @sa Stat, ScalarBase, StatStor
2510 class Scalar : public ScalarBase<Scalar, StatStor>
2513 using ScalarBase<Scalar, StatStor>::operator=;
2515 Scalar(Group *parent = nullptr, const char *name = nullptr,
2516 const char *desc = nullptr)
2517 : ScalarBase<Scalar, StatStor>(parent, name, desc)
2523 * A stat that calculates the per tick average of a value.
2524 * @sa Stat, ScalarBase, AvgStor
2526 class Average : public ScalarBase<Average, AvgStor>
2529 using ScalarBase<Average, AvgStor>::operator=;
2531 Average(Group *parent = nullptr, const char *name = nullptr,
2532 const char *desc = nullptr)
2533 : ScalarBase<Average, AvgStor>(parent, name, desc)
2538 class Value : public ValueBase<Value>
2541 Value(Group *parent = nullptr, const char *name = nullptr,
2542 const char *desc = nullptr)
2543 : ValueBase<Value>(parent, name, desc)
2549 * A vector of scalar stats.
2550 * @sa Stat, VectorBase, StatStor
2552 class Vector : public VectorBase<Vector, StatStor>
2555 Vector(Group *parent = nullptr, const char *name = nullptr,
2556 const char *desc = nullptr)
2557 : VectorBase<Vector, StatStor>(parent, name, desc)
2563 * A vector of Average stats.
2564 * @sa Stat, VectorBase, AvgStor
2566 class AverageVector : public VectorBase<AverageVector, AvgStor>
2569 AverageVector(Group *parent = nullptr, const char *name = nullptr,
2570 const char *desc = nullptr)
2571 : VectorBase<AverageVector, AvgStor>(parent, name, desc)
2577 * A 2-Dimensional vecto of scalar stats.
2578 * @sa Stat, Vector2dBase, StatStor
2580 class Vector2d : public Vector2dBase<Vector2d, StatStor>
2583 Vector2d(Group *parent = nullptr, const char *name = nullptr,
2584 const char *desc = nullptr)
2585 : Vector2dBase<Vector2d, StatStor>(parent, name, desc)
2591 * A simple distribution stat.
2592 * @sa Stat, DistBase, DistStor
2594 class Distribution : public DistBase<Distribution, DistStor>
2597 Distribution(Group *parent = nullptr, const char *name = nullptr,
2598 const char *desc = nullptr)
2599 : DistBase<Distribution, DistStor>(parent, name, desc)
2604 * Set the parameters of this distribution. @sa DistStor::Params
2605 * @param min The minimum value of the distribution.
2606 * @param max The maximum value of the distribution.
2607 * @param bkt The number of values in each bucket.
2608 * @return A reference to this distribution.
2611 init(Counter min, Counter max, Counter bkt)
2613 DistStor::Params *params = new DistStor::Params;
2616 params->bucket_size = bkt;
2617 // Division by zero is especially serious in an Aarch64 host,
2618 // where it gets rounded to allocate 32GiB RAM.
2620 params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2621 this->setParams(params);
2623 return this->self();
2628 * A simple histogram stat.
2629 * @sa Stat, DistBase, HistStor
2631 class Histogram : public DistBase<Histogram, HistStor>
2634 Histogram(Group *parent = nullptr, const char *name = nullptr,
2635 const char *desc = nullptr)
2636 : DistBase<Histogram, HistStor>(parent, name, desc)
2641 * Set the parameters of this histogram. @sa HistStor::Params
2642 * @param size The number of buckets in the histogram
2643 * @return A reference to this histogram.
2646 init(size_type size)
2648 HistStor::Params *params = new HistStor::Params;
2649 params->buckets = size;
2650 this->setParams(params);
2652 return this->self();
2657 * Calculates the mean and variance of all the samples.
2658 * @sa DistBase, SampleStor
2660 class StandardDeviation : public DistBase<StandardDeviation, SampleStor>
2664 * Construct and initialize this distribution.
2666 StandardDeviation(Group *parent = nullptr, const char *name = nullptr,
2667 const char *desc = nullptr)
2668 : DistBase<StandardDeviation, SampleStor>(parent, name, desc)
2670 SampleStor::Params *params = new SampleStor::Params;
2672 this->setParams(params);
2677 * Calculates the per tick mean and variance of the samples.
2678 * @sa DistBase, AvgSampleStor
2680 class AverageDeviation : public DistBase<AverageDeviation, AvgSampleStor>
2684 * Construct and initialize this distribution.
2686 AverageDeviation(Group *parent = nullptr, const char *name = nullptr,
2687 const char *desc = nullptr)
2688 : DistBase<AverageDeviation, AvgSampleStor>(parent, name, desc)
2690 AvgSampleStor::Params *params = new AvgSampleStor::Params;
2692 this->setParams(params);
2697 * A vector of distributions.
2698 * @sa VectorDistBase, DistStor
2700 class VectorDistribution : public VectorDistBase<VectorDistribution, DistStor>
2703 VectorDistribution(Group *parent = nullptr, const char *name = nullptr,
2704 const char *desc = nullptr)
2705 : VectorDistBase<VectorDistribution, DistStor>(parent, name, desc)
2710 * Initialize storage and parameters for this distribution.
2711 * @param size The size of the vector (the number of distributions).
2712 * @param min The minimum value of the distribution.
2713 * @param max The maximum value of the distribution.
2714 * @param bkt The number of values in each bucket.
2715 * @return A reference to this distribution.
2717 VectorDistribution &
2718 init(size_type size, Counter min, Counter max, Counter bkt)
2720 DistStor::Params *params = new DistStor::Params;
2723 params->bucket_size = bkt;
2724 params->buckets = (size_type)ceil((max - min + 1.0) / bkt);
2725 this->setParams(params);
2727 return this->self();
2732 * This is a vector of StandardDeviation stats.
2733 * @sa VectorDistBase, SampleStor
2735 class VectorStandardDeviation
2736 : public VectorDistBase<VectorStandardDeviation, SampleStor>
2739 VectorStandardDeviation(Group *parent = nullptr, const char *name = nullptr,
2740 const char *desc = nullptr)
2741 : VectorDistBase<VectorStandardDeviation, SampleStor>(parent, name,
2747 * Initialize storage for this distribution.
2748 * @param size The size of the vector.
2749 * @return A reference to this distribution.
2751 VectorStandardDeviation &
2752 init(size_type size)
2754 SampleStor::Params *params = new SampleStor::Params;
2756 this->setParams(params);
2757 return this->self();
2762 * This is a vector of AverageDeviation stats.
2763 * @sa VectorDistBase, AvgSampleStor
2765 class VectorAverageDeviation
2766 : public VectorDistBase<VectorAverageDeviation, AvgSampleStor>
2769 VectorAverageDeviation(Group *parent = nullptr, const char *name = nullptr,
2770 const char *desc = nullptr)
2771 : VectorDistBase<VectorAverageDeviation, AvgSampleStor>(parent, name,
2777 * Initialize storage for this distribution.
2778 * @param size The size of the vector.
2779 * @return A reference to this distribution.
2781 VectorAverageDeviation &
2782 init(size_type size)
2784 AvgSampleStor::Params *params = new AvgSampleStor::Params;
2786 this->setParams(params);
2787 return this->self();
2791 template <class Stat>
2792 class FormulaInfoProxy : public InfoProxy<Stat, FormulaInfo>
2795 mutable VResult vec;
2796 mutable VCounter cvec;
2799 FormulaInfoProxy(Stat &stat) : InfoProxy<Stat, FormulaInfo>(stat) {}
2801 size_type size() const { return this->s.size(); }
2806 this->s.result(vec);
2809 Result total() const { return this->s.total(); }
2810 VCounter &value() const { return cvec; }
2812 std::string str() const { return this->s.str(); }
2815 template <class Stat>
2816 class SparseHistInfoProxy : public InfoProxy<Stat, SparseHistInfo>
2819 SparseHistInfoProxy(Stat &stat) : InfoProxy<Stat, SparseHistInfo>(stat) {}
2823 * Implementation of a sparse histogram stat. The storage class is
2824 * determined by the Storage template.
2826 template <class Derived, class Stor>
2827 class SparseHistBase : public DataWrap<Derived, SparseHistInfoProxy>
2830 typedef SparseHistInfoProxy<Derived> Info;
2831 typedef Stor Storage;
2832 typedef typename Stor::Params Params;
2835 /** The storage for this stat. */
2836 char storage[sizeof(Storage)];
2840 * Retrieve the storage.
2841 * @return The storage object for this stat.
2846 return reinterpret_cast<Storage *>(storage);
2850 * Retrieve a const pointer to the storage.
2851 * @return A const pointer to the storage object for this stat.
2856 return reinterpret_cast<const Storage *>(storage);
2862 new (storage) Storage(this->info());
2867 SparseHistBase(Group *parent, const char *name, const char *desc)
2868 : DataWrap<Derived, SparseHistInfoProxy>(parent, name, desc)
2873 * Add a value to the distribtion n times. Calls sample on the storage
2875 * @param v The value to add.
2876 * @param n The number of times to add it, defaults to 1.
2878 template <typename U>
2879 void sample(const U &v, int n = 1) { data()->sample(v, n); }
2882 * Return the number of entries in this stat.
2883 * @return The number of entries.
2885 size_type size() const { return data()->size(); }
2887 * Return true if no samples have been added.
2888 * @return True if there haven't been any samples.
2890 bool zero() const { return data()->zero(); }
2895 Info *info = this->info();
2896 data()->prepare(info, info->data);
2900 * Reset stat value to default
2905 data()->reset(this->info());
2910 * Templatized storage and interface for a sparse histogram stat.
2912 class SparseHistStor
2915 /** The parameters for a sparse histogram stat. */
2916 struct Params : public DistParams
2918 Params() : DistParams(Hist) {}
2922 /** Counter for number of samples */
2924 /** Counter for each bucket. */
2928 SparseHistStor(Info *info)
2934 * Add a value to the distribution for the given number of times.
2935 * @param val The value to add.
2936 * @param number The number of times to add the value.
2939 sample(Counter val, int number)
2941 cmap[val] += number;
2946 * Return the number of buckets in this distribution.
2947 * @return the number of buckets.
2949 size_type size() const { return cmap.size(); }
2952 * Returns true if any calls to sample have been made.
2953 * @return True if any values have been sampled.
2958 return samples == Counter();
2962 prepare(Info *info, SparseHistData &data)
2964 MCounter::iterator it;
2966 for (it = cmap.begin(); it != cmap.end(); it++) {
2967 data.cmap[(*it).first] = (*it).second;
2970 data.samples = samples;
2974 * Reset stat value to default
2984 class SparseHistogram : public SparseHistBase<SparseHistogram, SparseHistStor>
2987 SparseHistogram(Group *parent = nullptr, const char *name = nullptr,
2988 const char *desc = nullptr)
2989 : SparseHistBase<SparseHistogram, SparseHistStor>(parent, name, desc)
2994 * Set the parameters of this histogram. @sa HistStor::Params
2995 * @param size The number of buckets in the histogram
2996 * @return A reference to this histogram.
2999 init(size_type size)
3001 SparseHistStor::Params *params = new SparseHistStor::Params;
3002 this->setParams(params);
3004 return this->self();
3010 * A formula for statistics that is calculated when printed. A formula is
3011 * stored as a tree of Nodes that represent the equation to calculate.
3012 * @sa Stat, ScalarStat, VectorStat, Node, Temp
3014 class Formula : public DataWrapVec<Formula, FormulaInfoProxy>
3017 /** The root of the tree which represents the Formula */
3023 * Create and initialize thie formula, and register it with the database.
3025 Formula(Group *parent = nullptr, const char *name = nullptr,
3026 const char *desc = nullptr);
3028 Formula(Group *parent, const char *name, const char *desc,
3032 * Set an unitialized Formula to the given root.
3033 * @param r The root of the expression tree.
3034 * @return a reference to this formula.
3036 const Formula &operator=(const Temp &r);
3038 template<typename T>
3039 const Formula &operator=(const T &v)
3046 * Add the given tree to the existing one.
3047 * @param r The root of the expression tree.
3048 * @return a reference to this formula.
3050 const Formula &operator+=(Temp r);
3053 * Divide the existing tree by the given one.
3054 * @param r The root of the expression tree.
3055 * @return a reference to this formula.
3057 const Formula &operator/=(Temp r);
3060 * Return the result of the Fomula in a vector. If there were no Vector
3061 * components to the Formula, then the vector is size 1. If there were,
3062 * like x/y with x being a vector of size 3, then the result returned will
3063 * be x[0]/y, x[1]/y, x[2]/y, respectively.
3064 * @return The result vector.
3066 void result(VResult &vec) const;
3069 * Return the total Formula result. If there is a Vector
3070 * component to this Formula, then this is the result of the
3071 * Formula if the formula is applied after summing all the
3072 * components of the Vector. For example, if Formula is x/y where
3073 * x is size 3, then total() will return (x[1]+x[2]+x[3])/y. If
3074 * there is no Vector component, total() returns the same value as
3075 * the first entry in the VResult val() returns.
3076 * @return The total of the result vector.
3078 Result total() const;
3081 * Return the number of elements in the tree.
3083 size_type size() const;
3088 * Formulas don't need to be reset
3097 std::string str() const;
3100 class FormulaNode : public Node
3103 const Formula &formula;
3104 mutable VResult vec;
3107 FormulaNode(const Formula &f) : formula(f) {}
3109 size_type size() const { return formula.size(); }
3110 const VResult &result() const { formula.result(vec); return vec; }
3111 Result total() const { return formula.total(); }
3113 std::string str() const { return formula.str(); }
3117 * Helper class to construct formula node trees.
3123 * Pointer to a Node object.
3129 * Copy the given pointer to this class.
3130 * @param n A pointer to a Node object to copy.
3132 Temp(const NodePtr &n) : node(n) { }
3134 Temp(NodePtr &&n) : node(std::move(n)) { }
3137 * Return the node pointer.
3138 * @return the node pointer.
3140 operator NodePtr&() { return node; }
3143 * Makde gcc < 4.6.3 happy and explicitly get the underlying node.
3145 NodePtr getNodePtr() const { return node; }
3149 * Create a new ScalarStatNode.
3150 * @param s The ScalarStat to place in a node.
3152 Temp(const Scalar &s)
3153 : node(new ScalarStatNode(s.info()))
3157 * Create a new ScalarStatNode.
3158 * @param s The ScalarStat to place in a node.
3160 Temp(const Value &s)
3161 : node(new ScalarStatNode(s.info()))
3165 * Create a new ScalarStatNode.
3166 * @param s The ScalarStat to place in a node.
3168 Temp(const Average &s)
3169 : node(new ScalarStatNode(s.info()))
3173 * Create a new VectorStatNode.
3174 * @param s The VectorStat to place in a node.
3176 Temp(const Vector &s)
3177 : node(new VectorStatNode(s.info()))
3180 Temp(const AverageVector &s)
3181 : node(new VectorStatNode(s.info()))
3187 Temp(const Formula &f)
3188 : node(new FormulaNode(f))
3192 * Create a new ScalarProxyNode.
3193 * @param p The ScalarProxy to place in a node.
3195 template <class Stat>
3196 Temp(const ScalarProxy<Stat> &p)
3197 : node(new ScalarProxyNode<Stat>(p))
3201 * Create a ConstNode
3202 * @param value The value of the const node.
3204 Temp(signed char value)
3205 : node(new ConstNode<signed char>(value))
3209 * Create a ConstNode
3210 * @param value The value of the const node.
3212 Temp(unsigned char value)
3213 : node(new ConstNode<unsigned char>(value))
3217 * Create a ConstNode
3218 * @param value The value of the const node.
3220 Temp(signed short value)
3221 : node(new ConstNode<signed short>(value))
3225 * Create a ConstNode
3226 * @param value The value of the const node.
3228 Temp(unsigned short value)
3229 : node(new ConstNode<unsigned short>(value))
3233 * Create a ConstNode
3234 * @param value The value of the const node.
3236 Temp(signed int value)
3237 : node(new ConstNode<signed int>(value))
3241 * Create a ConstNode
3242 * @param value The value of the const node.
3244 Temp(unsigned int value)
3245 : node(new ConstNode<unsigned int>(value))
3249 * Create a ConstNode
3250 * @param value The value of the const node.
3252 Temp(signed long value)
3253 : node(new ConstNode<signed long>(value))
3257 * Create a ConstNode
3258 * @param value The value of the const node.
3260 Temp(unsigned long value)
3261 : node(new ConstNode<unsigned long>(value))
3265 * Create a ConstNode
3266 * @param value The value of the const node.
3268 Temp(signed long long value)
3269 : node(new ConstNode<signed long long>(value))
3273 * Create a ConstNode
3274 * @param value The value of the const node.
3276 Temp(unsigned long long value)
3277 : node(new ConstNode<unsigned long long>(value))
3281 * Create a ConstNode
3282 * @param value The value of the const node.
3285 : node(new ConstNode<float>(value))
3289 * Create a ConstNode
3290 * @param value The value of the const node.
3293 : node(new ConstNode<double>(value))
3303 operator+(Temp l, Temp r)
3305 return Temp(std::make_shared<BinaryNode<std::plus<Result> > >(l, r));
3309 operator-(Temp l, Temp r)
3311 return Temp(std::make_shared<BinaryNode<std::minus<Result> > >(l, r));
3315 operator*(Temp l, Temp r)
3317 return Temp(std::make_shared<BinaryNode<std::multiplies<Result> > >(l, r));
3321 operator/(Temp l, Temp r)
3323 return Temp(std::make_shared<BinaryNode<std::divides<Result> > >(l, r));
3329 return Temp(std::make_shared<UnaryNode<std::negate<Result> > >(l));
3332 template <typename T>
3336 return Temp(std::make_shared<ConstNode<T> >(val));
3339 template <typename T>
3341 constantVector(T val)
3343 return Temp(std::make_shared<ConstVectorNode<T> >(val));
3349 return Temp(std::make_shared<SumNode<std::plus<Result> > >(val));
3352 /** Dump all statistics data to the registered outputs */
3359 * Register reset and dump handlers. These are the functions which
3360 * will actually perform the whole statistics reset/dump actions
3361 * including processing the reset/dump callbacks
3363 typedef void (*Handler)();
3365 void registerHandlers(Handler reset_handler, Handler dump_handler);
3368 * Register a callback that should be called whenever statistics are
3371 void registerResetCallback(Callback *cb);
3374 * Register a callback that should be called whenever statistics are
3375 * about to be dumped
3377 void registerDumpCallback(Callback *cb);
3380 * Process all the callbacks in the reset callbacks queue
3382 void processResetQueue();
3385 * Process all the callbacks in the dump callbacks queue
3387 void processDumpQueue();
3389 std::list<Info *> &statsList();
3391 typedef std::map<const void *, Info *> MapType;
3392 MapType &statsMap();
3394 typedef std::map<std::string, Info *> NameMapType;
3395 NameMapType &nameMap();
3397 bool validateStatName(const std::string &name);
3399 } // namespace Stats
3401 void debugDumpStats();
3403 #endif // __BASE_STATISTICS_HH__