statistics.hh

来自「M5,一个功能强大的多处理器系统模拟器.很多针对处理器架构,性能的研究都使用它作」· HH 代码 · 共 2,775 行 · 第 1/5 页

                return false;
        return true;
    }

    bool
    check() const
    {
        return storage != NULL;
    }

    void
    reset()
    {
        for (int i = 0; i < size(); ++i)
            data(i)->reset();
    }

  public:
    VectorBase()
        : storage(NULL)
    {}

    ~VectorBase()
    {
        if (!storage)
            return;

        for (int i = 0; i < _size; ++i)
            data(i)->~Storage();
        delete [] reinterpret_cast<char *>(storage);
    }

    /**
     * Return a reference (ScalarProxy) to the stat at the given index.
     * @param index The vector index to access.
     * @return A reference of the stat.
     */
    Proxy
    operator[](int index)
    {
        assert (index >= 0 && index < size());
        return Proxy(this, index);
    }

    void update(StatData *data) {}
};

template <class Stat>
class VectorProxy
{
  private:
    Stat *stat;
    int offset;
    int len;

  private:
    mutable VResult vec;

    typename Stat::Storage *
    data(int index)
    {
        assert(index < len);
        return stat->data(offset + index);
    }

    const typename Stat::Storage *
    data(int index) const
    {
        assert(index < len);
        return const_cast<Stat *>(stat)->data(offset + index);
    }

  public:
    const VResult &
    result() const
    {
        vec.resize(size());

        for (int i = 0; i < size(); ++i)
            vec[i] = data(i)->result(stat->params);

        return vec;
    }

    Result
    total() const
    {
        Result total = 0;
        for (int i = 0; i < size(); ++i)
            total += data(i)->result(stat->params);
        return total;
    }

  public:
    VectorProxy(Stat *s, int o, int l)
        : stat(s), offset(o), len(l)
    {
    }

    VectorProxy(const VectorProxy &sp)
        : stat(sp.stat), offset(sp.offset), len(sp.len)
    {
    }

    const VectorProxy &
    operator=(const VectorProxy &sp)
    {
        stat = sp.stat;
        offset = sp.offset;
        len = sp.len;
        return *this;
    }

    ScalarProxy<Stat> operator[](int index)
    {
        assert (index >= 0 && index < size());
        return ScalarProxy<Stat>(stat, offset + index);
    }

    size_t size() const { return len; }

    /**
     * This stat has no state.  Nothing to reset.
     */
    void reset() { }
};

template <class Stor>
class Vector2dBase : public DataAccess
{
  public:
    typedef Stor Storage;
    typedef typename Storage::Params Params;
    typedef VectorProxy<Vector2dBase<Storage> > Proxy;
    friend class ScalarProxy<Vector2dBase<Storage> >;
    friend class VectorProxy<Vector2dBase<Storage> >;

  protected:
    size_t x;
    size_t y;
    size_t _size;
    Storage *storage;
    Params params;

  protected:
    Storage *data(int index) { return &storage[index]; }
    const Storage *data(int index) const { return &storage[index]; }

    void
    doInit(int _x, int _y)
    {
        assert(_x > 0 && _y > 0 && "sizes must be positive!");
        assert(!storage && "already initialized");

        Vector2dData *statdata = dynamic_cast<Vector2dData *>(find());

        x = _x;
        y = _y;
        statdata->x = _x;
        statdata->y = _y;
        _size = x * y;

        char *ptr = new char[_size * sizeof(Storage)];
        storage = reinterpret_cast<Storage *>(ptr);

        for (int i = 0; i < _size; ++i)
            new (&storage[i]) Storage(params);

        setInit();
    }

  public:
    Vector2dBase()
        : storage(NULL)
    {}

    ~Vector2dBase()
    {
        if (!storage)
            return;

        for (int i = 0; i < _size; ++i)
            data(i)->~Storage();
        delete [] reinterpret_cast<char *>(storage);
    }

    void
    update(Vector2dData *newdata)
    {
        int size = this->size();
        newdata->cvec.resize(size);
        for (int i = 0; i < size; ++i)
            newdata->cvec[i] = data(i)->value(params);
    }

    std::string ysubname(int i) const { return (*this->y_subnames)[i]; }

    Proxy
    operator[](int index)
    {
        int offset = index * y;
        assert (index >= 0 && offset + index < size());
        return Proxy(this, offset, y);
    }


    size_t
    size() const
    {
        return _size;
    }

    bool
    zero() const
    {
        return data(0)->zero();
#if 0
        for (int i = 0; i < size(); ++i)
            if (!data(i)->zero())
                return false;
        return true;
#endif
    }

    /**
     * Reset stat value to default
     */
    void
    reset()
    {
        for (int i = 0; i < size(); ++i)
            data(i)->reset();
    }

    bool
    check()
    {
        return storage != NULL;
    }
};

//////////////////////////////////////////////////////////////////////
//
// Non formula statistics
//
//////////////////////////////////////////////////////////////////////

/**
 * Templatized storage and interface for a distrbution stat.
 */
struct DistStor
{
  public:
    /** The parameters for a distribution stat. */
    struct Params
    {
        /** The minimum value to track. */
        Counter min;
        /** The maximum value to track. */
        Counter max;
        /** The number of entries in each bucket. */
        Counter bucket_size;
        /** The number of buckets. Equal to (max-min)/bucket_size. */
        int size;
    };
    enum { fancy = false };

  private:
    /** The smallest value sampled. */
    Counter min_val;
    /** The largest value sampled. */
    Counter max_val;
    /** The number of values sampled less than min. */
    Counter underflow;
    /** The number of values sampled more than max. */
    Counter overflow;
    /** The current sum. */
    Counter sum;
    /** The sum of squares. */
    Counter squares;
    /** The number of samples. */
    Counter samples;
    /** Counter for each bucket. */
    VCounter cvec;

  public:
    DistStor(const Params &params)
        : cvec(params.size)
    {
        reset();
    }

    /**
     * Add a value to the distribution for the given number of times.
     * @param val The value to add.
     * @param number The number of times to add the value.
     * @param params The paramters of the distribution.
     */
    void sample(Counter val, int number, const Params &params)
    {
        if (val < params.min)
            underflow += number;
        else if (val > params.max)
            overflow += number;
        else {
            int index = (int)std::floor((val - params.min) / params.bucket_size);
            assert(index < size(params));
            cvec[index] += number;
        }

        if (val < min_val)
            min_val = val;

        if (val > max_val)
            max_val = val;

        Counter sample = val * number;
        sum += sample;
        squares += sample * sample;
        samples += number;
    }

    /**
     * Return the number of buckets in this distribution.
     * @return the number of buckets.
     * @todo Is it faster to return the size from the parameters?
     */
    size_t size(const Params &) const { return cvec.size(); }

    /**
     * Returns true if any calls to sample have been made.
     * @param params The paramters of the distribution.
     * @return True if any values have been sampled.
     */
    bool zero(const Params &params) const
    {
        return samples == Counter();
    }

    void update(DistDataData *data, const Params &params)
    {
        data->min = params.min;
        data->max = params.max;
        data->bucket_size = params.bucket_size;
        data->size = params.size;

        data->min_val = (min_val == INT_MAX) ? 0 : min_val;
        data->max_val = (max_val == INT_MIN) ? 0 : max_val;
        data->underflow = underflow;
        data->overflow = overflow;
        data->cvec.resize(params.size);
        for (int i = 0; i < params.size; ++i)
            data->cvec[i] = cvec[i];

        data->sum = sum;
        data->squares = squares;
        data->samples = samples;
    }

    /**
     * Reset stat value to default
     */
    void reset()
    {
        min_val = INT_MAX;
        max_val = INT_MIN;
        underflow = 0;
        overflow = 0;

        int size = cvec.size();
        for (int i = 0; i < size; ++i)
            cvec[i] = Counter();

        sum = Counter();
        squares = Counter();
        samples = Counter();
    }
};

/**
 * Templatized storage and interface for a distribution that calculates mean
 * and variance.
 */
struct FancyStor
{
  public:
    /**
     * No paramters for this storage.
     */
    struct Params {};
    enum { fancy = true };

  private:
    /** The current sum. */
    Counter sum;
    /** The sum of squares. */
    Counter squares;
    /** The number of samples. */
    Counter samples;

  public:
    /**
     * Create and initialize this storage.
     */
    FancyStor(const Params &)
        : sum(Counter()), squares(Counter()), samples(Counter())
    { }

    /**
     * Add a value the given number of times to this running average.
     * Update the running sum and sum of squares, increment the number of
     * values seen by the given number.
     * @param val The value to add.
     * @param number The number of times to add the value.
     * @param p The parameters of this stat.
     */
    void sample(Counter val, int number, const Params &p)
    {
        Counter value = val * number;
        sum += value;
        squares += value * value;
        samples += number;
    }

    void update(DistDataData *data, const Params &params)
    {
        data->sum = sum;
        data->squares = squares;
        data->samples = samples;
    }

    /**
     * Return the number of entries in this stat, 1
     * @return 1.
     */
    size_t size(const Params &) const { return 1; }

    /**
     * Return true if no samples have been added.
     * @return True if no samples have been added.
     */
    bool zero(const Params &) const { return samples == Counter(); }

    /**
     * Reset stat value to default
     */
    void reset()
    {
        sum = Counter();
        squares = Counter();
        samples = Counter();
    }
};

/**
 * Templatized storage for distribution that calculates per tick mean and
 * variance.
 */
struct AvgFancy
{
  public:
    /** No parameters for this storage. */
    struct Params {};
    enum { fancy = true };

  private:
    /** Current total. */
    Counter sum;
    /** Current sum of squares. */
    Counter squares;

  public:
    /**
     * Create and initialize this storage.
     */
    AvgFancy(const Params &) : sum(Counter()), squares(Counter()) {}

    /**
     * Add a value to the distribution for the given number of times.
     * Update the running sum and sum of squares.
     * @param val The value to add.
     * @param number The number of times to add the value.
     * @param p The paramters of the distribution.
     */
    void sample(Counter val, int number, const Params &p)
    {
        Counter value = val * number;
        sum += value;
        squares += value * value;
    }

    void update(DistDataData *data, const Params &params)
    {
        data->sum = sum;
        data->squares = squares;
        data->samples = curTick;
    }

    /**
     * Return the number of entries, in this case 1.
     * @return 1.
     */
    size_t size(const Params &params) const { return 1; }
    /**
     * Return true if no samples have been added.
     * @return True if the sum is zero.
     */
    bool zero(const Params &params) const { return sum == Counter(); }
    /**
     * Reset stat value to default
     */
    void reset()
    {
        sum = Counter();
        squares = Counter();
    }
};

/**
 * Implementation of a distribution stat. The type of distribution is
 * determined by the Storage template. @sa ScalarBase
 */
template <class Stor>
class DistBase : public DataAccess
{
  public:
    typedef Stor Storage;
    /** Define the params of the storage class. */
    typedef typename Storage::Params Params;

  protected:
    /** The storage for this stat. */
    char storage[sizeof(Storage)] __attribute__ ((aligned (8)));

    /** The parameters for this stat. */
    Params params;

  protected:
    /**
     * Retrieve the storage.
     * @return The storage object for this stat.
     */
    Storage *data()
    {
        return reinterpret_cast<Storage *>(storage);
    }

    /**
     * Retrieve a const pointer to the storage.
     * @return A const pointer to the storage object for this stat.
     */
    const Storage *
    data() const
    {
        return reinterpret_cast<const Storage *>(storage);