GSFFindIndexOfMinimum.h

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/*
  Copyright (C) 2002-2024 CERN for the benefit of the ATLAS collaboration
*/
 
#ifndef GSFFindIndexOfMimimum_H
#define GSFFindIndexOfMimimum_H
#include "CxxUtils/features.h"
#include "CxxUtils/inline_hints.h"
#include "CxxUtils/restrict.h"
#include "CxxUtils/vec.h"
#include "GaudiKernel/Kernel.h"
#include "TrkGaussianSumFilterUtils/GsfConstants.h"
//
#include <algorithm>
#include <memory>
#include <numeric>
#include <climits>
 
namespace vAlgs{
 
template <size_t ISA_WIDTH>
constexpr size_t alignmentForArray(){
  return ISA_WIDTH / CHAR_BIT;
}
 
template <size_t ISA_WIDTH, typename T>
constexpr size_t strideOfNumSIMDVec(size_t NumSIMDVec){
  return NumSIMDVec * (ISA_WIDTH / (sizeof(T) * CHAR_BIT));
}
 
template <size_t STRIDE>
constexpr int numPadded(const int n) {
  // This always return a padded number dividable
  // with STRIDE , eg if STRIDE = 16
  // e.g ((33+15)&~15) = 48
  constexpr size_t STRIDEMINUS1 = STRIDE - 1;
  return ((n + STRIDEMINUS1) & ~STRIDEMINUS1);
}
 
template <size_t ISA_WIDTH, typename T>
ATH_ALWAYS_INLINE
T vFindMinimum(const T* distancesIn, int n) {
 
  using namespace CxxUtils;
  static_assert(std::is_floating_point_v<T>, "T not a floating point type");
  constexpr size_t VEC_WIDTH = ISA_WIDTH / (sizeof(T) * CHAR_BIT);
  const T* array =
      std::assume_aligned<alignmentForArray<ISA_WIDTH>()>(distancesIn);
  using vec_t = vec<T, VEC_WIDTH>;
  vec_t minValues1;
  vec_t minValues2;
  vec_t minValues3;
  vec_t minValues4;
  vload(minValues1, array);
  vload(minValues2, array + VEC_WIDTH);
  vload(minValues3, array + VEC_WIDTH * 2);
  vload(minValues4, array + VEC_WIDTH * 3);
  vec_t values1;
  vec_t values2;
  vec_t values3;
  vec_t values4;
  for (int i = 4 * VEC_WIDTH; i < n; i += 4 * VEC_WIDTH) {
    // 1
    vload(values1, array + i);
    vmin(minValues1, values1, minValues1);
    // 2
    vload(values2, array + i + VEC_WIDTH);
    vmin(minValues2, values2, minValues2);
    // 3
    vload(values3, array + i + 2 * VEC_WIDTH);
    vmin(minValues3, values3, minValues3);
    // 4
    vload(values4, array + i + 3 * VEC_WIDTH);
    vmin(minValues4, values4, minValues4);
  }
  // Compare //1 with //2
  vmin(minValues1, minValues1, minValues2);
  // compare //3 with //4
  vmin(minValues3, minValues3, minValues4);
  // Compare //1 with //3
  vmin(minValues1, minValues1, minValues3);
  // Do the final calculation scalar way
  T finalMinValues[VEC_WIDTH];
  vstore(finalMinValues, minValues1);
 
  // Do the final calculation scalar way
  return std::reduce(std::begin(finalMinValues), std::end(finalMinValues),
                     finalMinValues[0],
                     [](T a, T b) { return a < b ? a : b; });
}
 
template <size_t ISA_WIDTH, typename T>
ATH_ALWAYS_INLINE
int vIdxOfValue(const T value,
                const T* distancesIn, int n) {
  using namespace CxxUtils;
 
  static_assert(std::is_floating_point_v<T>, "T not a floating point type");
  constexpr int VEC_WIDTH = ISA_WIDTH / (sizeof(T) * CHAR_BIT);
  const T* array =
      std::assume_aligned<alignmentForArray<ISA_WIDTH>()>(distancesIn);
  using vec_t = vec<T, VEC_WIDTH>;
  using vec_mask = vec_mask_type_t<vec_t>;
  vec_t values1;
  vec_t values2;
  vec_t values3;
  vec_t values4;
  vec_t target;
  vbroadcast(target, value);
  for (int i = 0; i < n; i += 4 * VEC_WIDTH) {
    // 1
    vload(values1, array + i);
    vec_mask eq1 = values1 == target;
    // 2
    vload(values2, array + i + VEC_WIDTH);
    vec_mask eq2 = values2 == target;
    // 3
    vload(values3, array + i + VEC_WIDTH * 2);
    vec_mask eq3 = values3 == target;
    // 4
    vload(values4, array + i + VEC_WIDTH * 3);
    vec_mask eq4 = values4 == target;
 
    vec_mask eq12 = eq1 || eq2;
    vec_mask eq34 = eq3 || eq4;
    vec_mask eqAny = eq12 || eq34;
    if (vany(eqAny)) {
      for (int idx = i; idx < i + 4 * VEC_WIDTH; ++idx) {
        if (distancesIn[idx] == value) {
          return idx;
        }
      }
    }
  }
  return -1;
}
 
template <int ISA_WIDTH, typename T>
ATH_ALWAYS_INLINE
int vIdxOfMin(const T* distancesIn, int n) {
  using namespace CxxUtils;
  const T* array =
      std::assume_aligned<vAlgs::alignmentForArray<ISA_WIDTH>()>(distancesIn);
  static_assert(std::is_floating_point_v<T>, "T not a floating point type");
  //We process elements in blocks. When we find the minimum we also
  //keep track in which block it was
  constexpr int blockSize = 512;
  // case for n less than blockSize
  if (n <= blockSize) {
    T min = vFindMinimum<ISA_WIDTH>(array, n);
    return vIdxOfValue<ISA_WIDTH>(min, array, n);
  }
  int idx = 0;
  T min = array[0];
  // We might have a remainder that we need to handle
  const int remainder = n & (blockSize - 1);
  // process elements up to the remainder in blocks
  for (int i = 0; i < (n - remainder); i += blockSize) {
    T mintmp = vFindMinimum<ISA_WIDTH>(array + i, blockSize);
    if (mintmp < min) {
      min = mintmp;
      idx = i;
    }
  }
 
  //Process the remaining elements if any
  if (remainder != 0) {
    int index = n - remainder;
    T mintmp = vFindMinimum<ISA_WIDTH>(array + index, remainder);
    // if the minimu is here
    if (mintmp < min) {
      min = mintmp;
      return index + vIdxOfValue<ISA_WIDTH>(min, array + index, remainder);
    }
  }
  // Return the idx of the minimum just looping over a single block
  return idx + vIdxOfValue<ISA_WIDTH>(min, array + idx, blockSize);
}
 
} // namespace vAlgs
 
#endif