cpp/src/arrow/compute/kernels/aggregate_basic_avx2.cc

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//   http://www.apache.org/licenses/LICENSE-2.0
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#include "arrow/compute/kernels/aggregate_basic_internal.h"

namespace arrow {
namespace compute {
namespace aggregate {

// ----------------------------------------------------------------------
// Sum implementation

template <typename ArrowType>
struct SumImplAvx2 : public SumImpl<ArrowType, SimdLevel::AVX2> {};

template <typename ArrowType>
struct MeanImplAvx2 : public MeanImpl<ArrowType, SimdLevel::AVX2> {};

Result<std::unique_ptr<KernelState>> SumInitAvx2(KernelContext* ctx,
                                                 const KernelInitArgs& args) {
  SumLikeInit<SumImplAvx2> visitor(ctx, *args.inputs[0].type);
  return visitor.Create();
}

Result<std::unique_ptr<KernelState>> MeanInitAvx2(KernelContext* ctx,
                                                  const KernelInitArgs& args) {
  SumLikeInit<MeanImplAvx2> visitor(ctx, *args.inputs[0].type);
  return visitor.Create();
}

// ----------------------------------------------------------------------
// MinMax implementation

Result<std::unique_ptr<KernelState>> MinMaxInitAvx2(KernelContext* ctx,
                                                    const KernelInitArgs& args) {
  MinMaxInitState<SimdLevel::AVX2> visitor(
      ctx, *args.inputs[0].type, args.kernel->signature->out_type().type(),
      static_cast<const MinMaxOptions&>(*args.options));
  return visitor.Create();
}

void AddSumAvx2AggKernels(ScalarAggregateFunction* func) {
  AddBasicAggKernels(SumInitAvx2, internal::SignedIntTypes(), int64(), func,
                     SimdLevel::AVX2);
  AddBasicAggKernels(SumInitAvx2, internal::UnsignedIntTypes(), uint64(), func,
                     SimdLevel::AVX2);
  AddBasicAggKernels(SumInitAvx2, internal::FloatingPointTypes(), float64(), func,
                     SimdLevel::AVX2);
}

void AddMeanAvx2AggKernels(ScalarAggregateFunction* func) {
  AddBasicAggKernels(MeanInitAvx2, internal::NumericTypes(), float64(), func,
                     SimdLevel::AVX2);
}

void AddMinMaxAvx2AggKernels(ScalarAggregateFunction* func) {
  // Enable int types for AVX2 variants.
  // No auto vectorize for float/double as it use fmin/fmax which has NaN handling.
  AddMinMaxKernels(MinMaxInitAvx2, internal::IntTypes(), func, SimdLevel::AVX2);
}

}  // namespace aggregate
}  // namespace compute
}  // namespace arrow