linear_combination.h

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/*! \file
  \brief Functor performing linear combination operations used by epilogues.
*/

#pragma once

#include "cutlass/cutlass.h"
#include "cutlass/numeric_types.h"
#include "cutlass/array.h"
#include "cutlass/functional.h"
#include "cutlass/numeric_conversion.h"
#include "cutlass/epilogue/thread/scale_type.h"
#include "cutlass/epilogue/thread/linear_combination_params.h"

/////////////////////////////////////////////////////////////////////////////////////////////////

namespace cutlass {
namespace epilogue {
namespace thread {

/////////////////////////////////////////////////////////////////////////////////////////////////

/// Applies a linear combination operator to an array of elements.
///
/// D = alpha * accumulator + beta * source + uniform
///
template <
  typename ElementOutput_,                             ///< Data type used to load and store tensors
  int Count,                                           ///< Number of elements computed per operation.
                                                       ///< Usually it is 128/sizeof_bits<ElementOutput_>,
                                                       ///< but we use 64 or 32 sometimes when there are not enough data to store
  typename ElementAccumulator_ = ElementOutput_,       ///< Accumulator data type
  typename ElementCompute_ = ElementOutput_,           ///< Data type used to compute linear combination
  ScaleType::Kind Scale = ScaleType::Default,          ///< Control Alpha and Beta scaling
  FloatRoundStyle Round = FloatRoundStyle::round_to_nearest
>
class LinearCombination {
public:

  using ElementOutput = ElementOutput_;
  using ElementAccumulator = ElementAccumulator_;
  using ElementCompute = ElementCompute_;

  static int const kCount = Count;
  static const ScaleType::Kind kScale = Scale;
  using FragmentOutput = Array<ElementOutput, kCount>;
  using FragmentAccumulator = Array<ElementAccumulator, kCount>;
  using ComputeFragment = Array<ElementCompute, kCount>;

  using ParamsBase = LinearCombinationParams;
  
  static FloatRoundStyle const kRound = Round;

  /// Host-constructable parameters structure
  struct Params : ParamsBase{
    ElementCompute alpha;                  ///< scales accumulators
    ElementCompute beta;                   ///< scales source tensor
    ElementCompute const *alpha_ptr;       ///< pointer to accumulator scalar - if not null, loads it from memory
    ElementCompute const *beta_ptr;        ///< pointer to source scalar - if not null, loads it from memory

    CUTLASS_HOST_DEVICE
    Params(): 
      ParamsBase(
        ElementCompute(1), 
        ElementCompute(0)
      ),
      alpha(ElementCompute(1)), 
      beta(ElementCompute(0)), 
      alpha_ptr(nullptr), 
      beta_ptr(nullptr) { }

    CUTLASS_HOST_DEVICE
    Params(
      ElementCompute alpha,
      ElementCompute beta
    ): 
      ParamsBase(alpha, beta),
      alpha(alpha), beta(beta), alpha_ptr(nullptr), beta_ptr(nullptr) { } 

    CUTLASS_HOST_DEVICE
    Params(
      ElementCompute alpha
    ): 
      ParamsBase(alpha, ElementCompute(0)),
      alpha(alpha), beta(0), alpha_ptr(nullptr), beta_ptr(nullptr) { }

    CUTLASS_HOST_DEVICE
    Params(
      ElementCompute const *alpha_ptr,
      ElementCompute const *beta_ptr
    ): 
      ParamsBase(*alpha_ptr, *beta_ptr),
      alpha(0), beta(0), alpha_ptr(alpha_ptr), beta_ptr(beta_ptr) { }

    CUTLASS_HOST_DEVICE
    Params(
      ElementCompute const *alpha_ptr
    ):
      ParamsBase(*alpha_ptr, ElementCompute(0)),
      alpha(0), beta(0), alpha_ptr(alpha_ptr), beta_ptr(nullptr) { }

    CUTLASS_HOST_DEVICE
    Params(
      ParamsBase const& base
    ): ParamsBase(base), alpha_ptr(nullptr), beta_ptr(nullptr) { 
      #if defined(__CUDA_ARCH__)
      alpha = reinterpret_cast<ElementCompute const&>(base.alpha_data);
      beta = reinterpret_cast<ElementCompute const&>(base.beta_data);
      #else
      memcpy( alpha, base.alpha_data, sizeof(ElementCompute) ); 
      memcpy( beta, base.alpha_data, sizeof(ElementCompute) ); 
      #endif
    }
  };

private:

  //
  // Data members
  //

  ElementCompute alpha_;
  ElementCompute beta_;

public:

  /// Constructs the function object, possibly loading from pointers in host memory
  CUTLASS_HOST_DEVICE
  LinearCombination(Params const &params) {
    alpha_ = (params.alpha_ptr ? *params.alpha_ptr : params.alpha);
    beta_ = (params.beta_ptr ? *params.beta_ptr : params.beta);
  }

  /// Returns true if source is needed
  CUTLASS_HOST_DEVICE
  bool is_source_needed() const {
    if (Scale == ScaleType::NoBetaScaling) return true;

    if (Scale == ScaleType::OnlyAlphaScaling) return false;

    if (Scale == ScaleType::Nothing) return false;

    return beta_ != ElementCompute(0);
  }

  /// Functionally required for serial reduction in the epilogue
  CUTLASS_HOST_DEVICE
  void set_k_partition(int k_partition, int k_partition_count) {
    if (k_partition) {
      beta_ = ElementCompute(1);
    }
  }

  /// Computes linear scaling: D = alpha * accumulator + beta * source
  CUTLASS_HOST_DEVICE
  FragmentOutput operator()(
    FragmentAccumulator const &accumulator, 
    FragmentOutput const &source) const {

    // Convert source to interal compute numeric type
    NumericArrayConverter<ElementCompute, ElementOutput, kCount, Round> source_converter;
    NumericArrayConverter<ElementCompute, ElementAccumulator, kCount, Round> accumulator_converter;

    // Convert to destination numeric type
    NumericArrayConverter<ElementOutput, ElementCompute, kCount, Round> destination_converter;

    ComputeFragment converted_source = source_converter(source);
    ComputeFragment converted_accumulator = accumulator_converter(accumulator);

    if (Scale == ScaleType::Nothing)
      return destination_converter(converted_accumulator);

    // Perform binary operations
    ComputeFragment intermediate;

    multiplies<ComputeFragment> mul_add_source;
    multiply_add<ComputeFragment> mul_add_accumulator;

    if (Scale == ScaleType::NoBetaScaling)
      intermediate = converted_source;
    else
      intermediate = mul_add_source(beta_, converted_source);                             // X =  beta * C + uniform

    intermediate = mul_add_accumulator(alpha_, converted_accumulator, intermediate);    // D = alpha * Accum + X

    return destination_converter(intermediate);
  }

  /// Computes linear scaling: D = alpha * accumulator
  CUTLASS_HOST_DEVICE
  FragmentOutput operator()(
    FragmentAccumulator const &accumulator) const {

    // Convert source to interal compute numeric type
    NumericArrayConverter<ElementCompute, ElementAccumulator, kCount, Round> accumulator_converter;

    // Convert to destination numeric type
    NumericArrayConverter<ElementOutput, ElementCompute, kCount, Round> destination_converter;

    ComputeFragment converted_accumulator = accumulator_converter(accumulator);

    if (Scale == ScaleType::Nothing)
      return destination_converter(converted_accumulator);

    // Perform binary operations
    ComputeFragment intermediate;
    multiplies<ComputeFragment> mul_accumulator;

    intermediate = mul_accumulator(alpha_, converted_accumulator);    // D = alpha * Accum 

    return destination_converter(intermediate);
  }
};

/////////////////////////////////////////////////////////////////////////////////////////////////

} // namespace thread
} // namespace epilogue
} // namespace cutlass

/////////////////////////////////////////////////////////////////////////////////////////////////