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Choose TensorBlock StridedLinearCopy type statically

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This commit is contained in:
Eugene Zhulenev 2019-09-24 16:04:29 -07:00
parent c97b208468
commit c64396b4c6
1 changed files with 60 additions and 31 deletions
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91
unsupported/Eigen/CXX11/src/Tensor/TensorBlockV2.h
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@ -459,6 +459,16 @@ class StridedLinearBufferCopy {
};
public:
// Specifying linear copy kind statically gives ~30% speedup for small sizes.
enum Kind {
Linear = 0, // src_stride == 1 && dst_stride == 1
Scatter = 1, // src_stride == 1 && dst_stride != 1
FillLinear = 2, // src_stride == 0 && dst_stride == 1
FillScatter = 3, // src_stride == 0 && dst_stride != 1
Gather = 4, // dst_stride == 1
Random = 5 // everything else
};
struct Dst {
Dst(IndexType o, IndexType s, Scalar* d) : offset(o), stride(s), data(d) {}
@ -476,14 +486,16 @@ class StridedLinearBufferCopy {
const Scalar* data;
};
template <StridedLinearBufferCopy::Kind kind>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void Run(const Dst& dst,
const Src& src,
const size_t count) {
Run(count, dst.offset, dst.stride, dst.data, src.offset, src.stride,
src.data);
Run<kind>(count, dst.offset, dst.stride, dst.data, src.offset, src.stride,
src.data);
}
private:
template <StridedLinearBufferCopy::Kind kind>
static EIGEN_DEVICE_FUNC EIGEN_STRONG_INLINE void Run(
const IndexType count, const IndexType dst_offset,
const IndexType dst_stride, Scalar* EIGEN_RESTRICT dst_data,
@ -499,13 +511,14 @@ class StridedLinearBufferCopy {
return;
}
const IndexType unrolled_size = count - 4 * PacketSize;
const IndexType vectorized_size = count - PacketSize;
IndexType i = 0;
if (src_stride == 1 && dst_stride == 1) {
if (kind == Linear) {
// ******************************************************************** //
// Linear copy from `src` to `dst`.
const IndexType unrolled_size = count - 4 * PacketSize;
eigen_assert(src_stride == 1 && dst_stride == 1);
for (; i <= unrolled_size; i += 4 * PacketSize) {
for (int j = 0; j < 4; ++j) {
Packet p = ploadu<Packet>(src + i + j * PacketSize);
@ -520,8 +533,9 @@ class StridedLinearBufferCopy {
dst[i] = src[i];
}
// ******************************************************************** //
} else if (src_stride == 1 && dst_stride != 1) {
} else if (kind == Scatter) {
// Scatter from `src` to `dst`.
eigen_assert(src_stride == 1 && dst_stride != 1);
for (; i <= vectorized_size; i += PacketSize) {
Packet p = ploadu<Packet>(src + i);
pscatter<Scalar, Packet>(dst + i * dst_stride, p, dst_stride);
@ -530,14 +544,10 @@ class StridedLinearBufferCopy {
dst[i * dst_stride] = src[i];
}
// ******************************************************************** //
} else if (src_stride == 0 && dst_stride == 1) {
} else if (kind == FillLinear) {
// Fill `dst` with value at `*src`.
eigen_assert(src_stride == 0 && dst_stride == 1);
Packet p = pload1<Packet>(src);
for (; i <= unrolled_size; i += 4 * PacketSize) {
for (int j = 0; j < 4; ++j) {
pstoreu<Scalar, Packet>(dst + i + j * PacketSize, p);
}
}
for (; i <= vectorized_size; i += PacketSize) {
pstoreu<Scalar, Packet>(dst + i, p);
}
@ -545,8 +555,9 @@ class StridedLinearBufferCopy {
dst[i] = *src;
}
// ******************************************************************** //
} else if (src_stride == 0 && dst_stride != 1) {
} else if (kind == FillScatter) {
// Scatter `*src` into `dst`.
eigen_assert(src_stride == 0 && dst_stride != 1);
Packet p = pload1<Packet>(src);
for (; i <= vectorized_size; i += PacketSize) {
pscatter<Scalar, Packet>(dst + i * dst_stride, p, dst_stride);
@ -555,8 +566,9 @@ class StridedLinearBufferCopy {
dst[i * dst_stride] = *src;
}
// ******************************************************************** //
} else if (dst_stride == 1) {
} else if (kind == Gather) {
// Gather from `src` into `dst`.
eigen_assert(dst_stride == 1);
for (; i <= vectorized_size; i += PacketSize) {
Packet p = pgather<Scalar, Packet>(src + i * src_stride, src_stride);
pstoreu<Scalar, Packet>(dst + i, p);
@ -565,11 +577,13 @@ class StridedLinearBufferCopy {
dst[i] = src[i * src_stride];
}
// ******************************************************************** //
} else {
} else if (kind == Random) {
// Random.
for (; i < count; ++i) {
dst[i * dst_stride] = src[i * src_stride];
}
} else {
eigen_assert(false);
}
}
};
@ -716,25 +730,40 @@ class TensorBlockIOV2 {
// Iterate copying data from src to dst.
const IndexType block_total_size = NumDims == 0 ? 1 : dst.dims.TotalSize();
for (IndexType i = 0; i < block_total_size; i += dst_inner_dim_size) {
// Copy data for the innermost dimension.
LinCopy::Run(
typename LinCopy::Dst(output_offset, output_stride, dst.data),
typename LinCopy::Src(input_offset, input_stride, src.data),
dst_inner_dim_size);
#define COPY_INNER_DIM(KIND) \
for (IndexType i = 0; i < block_total_size; i += dst_inner_dim_size) { \
LinCopy::template Run<KIND>( \
typename LinCopy::Dst(output_offset, output_stride, dst.data), \
typename LinCopy::Src(input_offset, input_stride, src.data), \
dst_inner_dim_size); \
\
for (int j = 0; j < idx; ++j) { \
if (++it[j].count < it[j].size) { \
input_offset += it[j].input_stride; \
output_offset += it[j].output_stride; \
break; \
} \
it[j].count = 0; \
input_offset -= it[j].input_span; \
output_offset -= it[j].output_span; \
} \
}
// Update offsets (idx is the number of initialize block iterators).
for (int j = 0; j < idx; ++j) {
if (++it[j].count < it[j].size) {
input_offset += it[j].input_stride;
output_offset += it[j].output_stride;
break;
}
it[j].count = 0;
input_offset -= it[j].input_span;
output_offset -= it[j].output_span;
}
if (input_stride == 1 && output_stride == 1) {
COPY_INNER_DIM(LinCopy::Linear);
} else if (input_stride == 1 && output_stride != 1) {
COPY_INNER_DIM(LinCopy::Scatter);
} else if (input_stride == 0 && output_stride == 1) {
COPY_INNER_DIM(LinCopy::FillLinear);
} else if (input_stride == 0 && output_stride != 1) {
COPY_INNER_DIM(LinCopy::FillScatter);
} else if (output_stride == 1) {
COPY_INNER_DIM(LinCopy::Gather);
} else {
COPY_INNER_DIM(LinCopy::Random);
}
#undef COPY_INNER_DIM
}
// Copy from `src` to `dst` with an identity src->dst dimension map.