Move the evalGemm method into the TensorContractionEvaluatorBase class to make it accessible from both the single and multithreaded contraction evaluators.

This commit is contained in:
Benoit Steiner 2016-04-15 16:48:10 -07:00
parent 1a16fb1532
commit c8e8f93d6c

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@ -426,6 +426,99 @@ struct TensorContractionEvaluatorBase
buffer, resIncr, alpha);
}
template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
EIGEN_DEVICE_FUNC void evalGemm(Scalar* buffer) const {
// columns in left side, rows in right side
const Index k = this->m_k_size;
// rows in left side
const Index m = this->m_i_size;
// columns in right side
const Index n = this->m_j_size;
// zero out the result buffer (which must be of size at least m * n * sizeof(Scalar)
this->m_device.memset(buffer, 0, m * n * sizeof(Scalar));
// define mr, nr, and all of my data mapper types
typedef typename internal::remove_const<typename EvalLeftArgType::Scalar>::type LhsScalar;
typedef typename internal::remove_const<typename EvalRightArgType::Scalar>::type RhsScalar;
typedef typename internal::gebp_traits<LhsScalar, RhsScalar> Traits;
const Index nr = Traits::nr;
const Index mr = Traits::mr;
typedef TensorEvaluator<EvalLeftArgType, Device> LeftEvaluator;
typedef TensorEvaluator<EvalRightArgType, Device> RightEvaluator;
const Index lhs_packet_size = internal::unpacket_traits<typename LeftEvaluator::PacketReturnType>::size;
const Index rhs_packet_size = internal::unpacket_traits<typename RightEvaluator::PacketReturnType>::size;
typedef internal::TensorContractionInputMapper<LhsScalar, Index, internal::Lhs,
LeftEvaluator, left_nocontract_t,
contract_t, lhs_packet_size,
lhs_inner_dim_contiguous,
false, Unaligned> LhsMapper;
typedef internal::TensorContractionInputMapper<RhsScalar, Index, internal::Rhs,
RightEvaluator, right_nocontract_t,
contract_t, rhs_packet_size,
rhs_inner_dim_contiguous,
rhs_inner_dim_reordered, Unaligned> RhsMapper;
typedef internal::blas_data_mapper<Scalar, Index, ColMajor> OutputMapper;
// Declare GEBP packing and kernel structs
internal::gemm_pack_lhs<LhsScalar, Index, typename LhsMapper::SubMapper, mr, Traits::LhsProgress, ColMajor> pack_lhs;
internal::gemm_pack_rhs<RhsScalar, Index, typename RhsMapper::SubMapper, nr, ColMajor> pack_rhs;
internal::gebp_kernel<LhsScalar, RhsScalar, Index, OutputMapper, mr, nr, false, false> gebp;
// initialize data mappers
LhsMapper lhs(this->m_leftImpl, this->m_left_nocontract_strides, this->m_i_strides,
this->m_left_contracting_strides, this->m_k_strides);
RhsMapper rhs(this->m_rightImpl, this->m_right_nocontract_strides, this->m_j_strides,
this->m_right_contracting_strides, this->m_k_strides);
OutputMapper output(buffer, m);
// Sizes of the blocks to load in cache. See the Goto paper for details.
internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index, internal::ShardByCol> blocking(k, m, n, 1);
const Index kc = blocking.kc();
const Index mc = numext::mini(m, blocking.mc());
const Index nc = numext::mini(n, blocking.nc());
const Index sizeA = mc * kc;
const Index sizeB = kc * nc;
LhsScalar* blockA = static_cast<LhsScalar *>(this->m_device.allocate(sizeA * sizeof(LhsScalar)));
RhsScalar* blockB = static_cast<RhsScalar *>(this->m_device.allocate(sizeB * sizeof(RhsScalar)));
for(Index i2=0; i2<m; i2+=mc)
{
const Index actual_mc = numext::mini(i2+mc,m)-i2;
for (Index k2 = 0; k2 < k; k2 += kc) {
// make sure we don't overshoot right edge of left matrix, then pack vertical panel
const Index actual_kc = numext::mini(k2 + kc, k) - k2;
pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc, 0, 0);
// series of horizontal blocks
for (Index j2 = 0; j2 < n; j2 += nc) {
// make sure we don't overshoot right edge of right matrix, then pack block
const Index actual_nc = numext::mini(j2 + nc, n) - j2;
pack_rhs(blockB, rhs.getSubMapper(k2, j2), actual_kc, actual_nc, 0, 0);
// call gebp (matrix kernel)
// The parameters here are copied from Eigen's GEMM implementation
gebp(output.getSubMapper(i2, j2), blockA, blockB, actual_mc, actual_kc, actual_nc, 1.0, -1, -1, 0, 0);
}
}
}
this->m_device.deallocate(blockA);
this->m_device.deallocate(blockB);
}
EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void cleanup() {
m_leftImpl.cleanup();
m_rightImpl.cleanup();
@ -533,100 +626,7 @@ struct TensorEvaluator<const TensorContractionOp<Indices, LeftArgType, RightArgT
return;
}
evalGemm<lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered, Alignment>(buffer);
}
template <bool lhs_inner_dim_contiguous, bool rhs_inner_dim_contiguous, bool rhs_inner_dim_reordered, int Alignment>
EIGEN_DEVICE_FUNC void evalGemm(Scalar* buffer) const {
// columns in left side, rows in right side
const Index k = this->m_k_size;
// rows in left side
const Index m = this->m_i_size;
// columns in right side
const Index n = this->m_j_size;
// zero out the result buffer (which must be of size at least m * n * sizeof(Scalar)
this->m_device.memset(buffer, 0, m * n * sizeof(Scalar));
// define mr, nr, and all of my data mapper types
typedef typename internal::remove_const<typename EvalLeftArgType::Scalar>::type LhsScalar;
typedef typename internal::remove_const<typename EvalRightArgType::Scalar>::type RhsScalar;
typedef typename internal::gebp_traits<LhsScalar, RhsScalar> Traits;
const Index nr = Traits::nr;
const Index mr = Traits::mr;
typedef TensorEvaluator<EvalLeftArgType, Device> LeftEvaluator;
typedef TensorEvaluator<EvalRightArgType, Device> RightEvaluator;
const Index lhs_packet_size = internal::unpacket_traits<typename LeftEvaluator::PacketReturnType>::size;
const Index rhs_packet_size = internal::unpacket_traits<typename RightEvaluator::PacketReturnType>::size;
typedef internal::TensorContractionInputMapper<LhsScalar, Index, internal::Lhs,
LeftEvaluator, left_nocontract_t,
contract_t, lhs_packet_size,
lhs_inner_dim_contiguous,
false, Unaligned> LhsMapper;
typedef internal::TensorContractionInputMapper<RhsScalar, Index, internal::Rhs,
RightEvaluator, right_nocontract_t,
contract_t, rhs_packet_size,
rhs_inner_dim_contiguous,
rhs_inner_dim_reordered, Unaligned> RhsMapper;
typedef internal::blas_data_mapper<Scalar, Index, ColMajor> OutputMapper;
// Declare GEBP packing and kernel structs
internal::gemm_pack_lhs<LhsScalar, Index, typename LhsMapper::SubMapper, mr, Traits::LhsProgress, ColMajor> pack_lhs;
internal::gemm_pack_rhs<RhsScalar, Index, typename RhsMapper::SubMapper, nr, ColMajor> pack_rhs;
internal::gebp_kernel<LhsScalar, RhsScalar, Index, OutputMapper, mr, nr, false, false> gebp;
// initialize data mappers
LhsMapper lhs(this->m_leftImpl, this->m_left_nocontract_strides, this->m_i_strides,
this->m_left_contracting_strides, this->m_k_strides);
RhsMapper rhs(this->m_rightImpl, this->m_right_nocontract_strides, this->m_j_strides,
this->m_right_contracting_strides, this->m_k_strides);
OutputMapper output(buffer, m);
// Sizes of the blocks to load in cache. See the Goto paper for details.
internal::TensorContractionBlocking<LhsMapper, RhsMapper, Index, internal::ShardByCol> blocking(k, m, n, 1);
const Index kc = blocking.kc();
const Index mc = numext::mini(m, blocking.mc());
const Index nc = numext::mini(n, blocking.nc());
const Index sizeA = mc * kc;
const Index sizeB = kc * nc;
LhsScalar* blockA = static_cast<LhsScalar *>(this->m_device.allocate(sizeA * sizeof(LhsScalar)));
RhsScalar* blockB = static_cast<RhsScalar *>(this->m_device.allocate(sizeB * sizeof(RhsScalar)));
for(Index i2=0; i2<m; i2+=mc)
{
const Index actual_mc = numext::mini(i2+mc,m)-i2;
for (Index k2 = 0; k2 < k; k2 += kc) {
// make sure we don't overshoot right edge of left matrix, then pack vertical panel
const Index actual_kc = numext::mini(k2 + kc, k) - k2;
pack_lhs(blockA, lhs.getSubMapper(i2, k2), actual_kc, actual_mc, 0, 0);
// series of horizontal blocks
for (Index j2 = 0; j2 < n; j2 += nc) {
// make sure we don't overshoot right edge of right matrix, then pack block
const Index actual_nc = numext::mini(j2 + nc, n) - j2;
pack_rhs(blockB, rhs.getSubMapper(k2, j2), actual_kc, actual_nc, 0, 0);
// call gebp (matrix kernel)
// The parameters here are copied from Eigen's GEMM implementation
gebp(output.getSubMapper(i2, j2), blockA, blockB, actual_mc, actual_kc, actual_nc, 1.0, -1, -1, 0, 0);
}
}
}
this->m_device.deallocate(blockA);
this->m_device.deallocate(blockB);
this->template evalGemm<lhs_inner_dim_contiguous, rhs_inner_dim_contiguous, rhs_inner_dim_reordered, Alignment>(buffer);
}
};