docs/namespacecutlass_1_1reference_1_1device.html
| | CUTLASS
CUDA Templates for Linear Algebra Subroutines and Solvers |
Namespaces | Classes | Functions
cutlass::reference::device Namespace Reference
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| | | detail | | | | | kernel | | | | | thread | | |
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| struct | BlockForEach |
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| struct | Gemm |
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| struct | Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, AccumulatorType, arch::OpMultiplyAdd > |
| | Partial specialization for multiply-add. More...
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| struct | Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, AccumulatorType, arch::OpMultiplyAddSaturate > |
| | Partial specialization for multiply-add-saturate. More...
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| struct | Gemm< ElementA, LayoutA, ElementB, LayoutB, ElementC, LayoutC, ScalarType, AccumulatorType, arch::OpXorPopc > |
| | Partial specialization for XOR-popc. More...
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| struct | TensorDiagonalForEach |
| | Launches a kernel calling a functor for each element along a tensor's diagonal. More...
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| struct | TensorForEach |
| | Launches a kernel calling a functor for each element in a tensor's index space. More...
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| template<typename ElementA , typename LayoutA , typename ElementB , typename LayoutB , typename ElementC , typename LayoutC , typename ScalarType , typename AccumulatorType , typename InnerProductOp = multiply_add<AccumulatorType>, typename ConvertOp = NumericConverter<ElementC, ScalarType>> |
| void | compute_gemm (gemm::GemmCoord problem_size, ScalarType alpha, TensorRef< ElementA, LayoutA > tensor_a, TensorRef< ElementB, LayoutB > tensor_b, ScalarType beta, TensorRef< ElementC, LayoutC > tensor_c, TensorRef< ElementC, LayoutC > tensor_d, AccumulatorType initial_accum) |
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| template<typename ElementA , typename LayoutA , typename ElementB , typename LayoutB , typename ElementC , typename LayoutC , typename ScalarType , typename AccumulatorType , typename InnerProductOp = multiply_add<AccumulatorType>, typename ConvertOp = NumericConverter<ElementC, ScalarType>> |
| void | compute_gemm (gemm::GemmCoord problem_size, ScalarType alpha, TensorRef< ElementA, LayoutA > tensor_a, TensorRef< ElementB, LayoutB > tensor_b, ScalarType beta, TensorRef< ElementC, LayoutC > tensor_c, AccumulatorType initial_accum) |
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| template<typename TensorRefCollectionA , typename TensorRefCollectionB , typename TensorRefCollectionC , typename ScalarType , typename AccumulatorType , typename InnerProductOp , typename ConvertOp > |
| void | BatchedGemm (gemm::GemmCoord problem_size, int batch_count, ScalarType alpha, TensorRefCollectionA const &tensor_a, TensorRefCollectionB const &tensor_b, ScalarType beta, TensorRefCollectionC &tensor_c, AccumulatorType initial_accum) |
| | Computes a batch of GEMMs over a set of matrices of common dimension. More...
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| template<typename TensorRefCollectionA , typename TensorRefCollectionB , typename TensorRefCollectionC , typename ScalarType , typename AccumulatorType > |
| void | BatchedGemm (gemm::GemmCoord problem_size, int batch_count, ScalarType alpha, TensorRefCollectionA const &tensor_a, TensorRefCollectionB const &tensor_b, ScalarType beta, TensorRefCollectionC &tensor_c) |
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| template<typename Element > |
| bool | BlockCompareEqual (Element const *ptr_A, Element const *ptr_B, size_t capacity, int grid_size=0, int block_size=0) |
| | Performs a bit-level equality check between two blocks. More...
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| template<typename Element > |
| bool | BlockCompareRelativelyEqual (Element const *ptr_A, Element const *ptr_B, size_t capacity, Element epsilon, Element nonzero_floor, int grid_size=0, int block_size=0) |
| | Performs a bit-level equality check between two blocks. More...
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| template<typename Element , typename Layout > |
| void | TensorFillRandomGaussian (TensorView< Element, Layout > view, uint64_t seed, Element mean=Element(0), Element stddev=Element(1), int bits=-1) |
| | Fills a tensor with random values with a Gaussian distribution. More...
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| template<typename Element > |
| void | BlockFillRandomGaussian (Element *ptr, size_t capacity, uint64_t seed, Element mean=Element(0), Element stddev=Element(1), int bits=-1) |
| | Fills a tensor with random values with a Gaussian distribution. More...
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| template<typename Element , typename Layout > |
| void | TensorFillRandomUniform (TensorView< Element, Layout > view, uint64_t seed, Element max=Element(1), Element min=Element(0), int bits=-1) |
| | Fills a tensor with random values with a uniform random distribution. More...
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| template<typename Element > |
| void | BlockFillRandomUniform (Element *ptr, size_t capacity, uint64_t seed, Element max=Element(1), Element min=Element(0), int bits=-1) |
| | Fills a tensor with random values with a uniform random distribution. More...
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| template<typename Element , typename Layout > |
| void | TensorFillDiagonal (TensorView< Element, Layout > view, Element diag=Element(1), Element other=Element(0)) |
| | Fills a tensor everywhere with a unique value for its diagonal. More...
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| template<typename Element , typename Layout > |
| void | TensorFill (TensorView< Element, Layout > view, Element val=Element(0)) |
| | Fills a tensor with a uniform value. More...
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| template<typename Element , typename Layout > |
| void | TensorFillIdentity (TensorView< Element, Layout > view) |
| | Fills a tensor's diagonal with 1 and 0 everywhere else. More...
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| template<typename Element , typename Layout > |
| void | TensorUpdateDiagonal (TensorView< Element, Layout > view, Element diag=Element(1)) |
| | Writes a uniform value to the diagonal of a tensor without modifying off-diagonal elements. More...
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| template<typename Element , typename Layout > |
| void | TensorUpdateOffDiagonal (TensorView< Element, Layout > view, Element other=Element(1)) |
| | Writes a uniform value to all elements in the tensor without modifying diagonal elements. More...
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| template<typename Element , typename Layout > |
| void | TensorFillLinear (TensorView< Element, Layout > view, Array< Element, Layout::kRank > const &v, Element s=Element(0)) |
| | Fills tensor with a linear combination of its coordinate and another vector. More...
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| template<typename Element > |
| void | BlockFillSequential (Element *ptr, int64_t capacity, Element v=Element(1), Element s=Element(0)) |
| | Fills a block of data with sequential elements. More...
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| template<typename Element > |
| void | BlockFillRandom (Element *ptr, size_t capacity, uint64_t seed, Distribution dist) |
| | Fills a block of data with sequential elements. More...
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| template<typename Element , typename Layout > |
| void | TensorCopyDiagonalIn (TensorView< Element, Layout > view, Element const *ptr) |
| | Copies a diagonal in from host memory without modifying off-diagonal elements. More...
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| template<typename Element , typename Layout > |
| void | TensorCopyDiagonalOut (Element *ptr, TensorView< Element, Layout > view) |
| | Copies the diagonal of a tensor into a dense buffer in host memory. More...
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template<typename TensorRefCollectionA , typename TensorRefCollectionB , typename TensorRefCollectionC , typename ScalarType , typename AccumulatorType , typename InnerProductOp , typename ConvertOp >
| void cutlass::reference::device::BatchedGemm | ( | gemm::GemmCoord | problem_size, | | | | int | batch_count, | | | | ScalarType | alpha, | | | | TensorRefCollectionA const & | tensor_a, | | | | TensorRefCollectionB const & | tensor_b, | | | | ScalarType | beta, | | | | TensorRefCollectionC & | tensor_c, | | | | AccumulatorType | initial_accum | | | ) | | |
template<typename TensorRefCollectionA , typename TensorRefCollectionB , typename TensorRefCollectionC , typename ScalarType , typename AccumulatorType >
| void cutlass::reference::device::BatchedGemm | ( | gemm::GemmCoord | problem_size, | | | | int | batch_count, | | | | ScalarType | alpha, | | | | TensorRefCollectionA const & | tensor_a, | | | | TensorRefCollectionB const & | tensor_b, | | | | ScalarType | beta, | | | | TensorRefCollectionC & | tensor_c | | | ) | | |
Computes a general matrix product among matrices (tensors of rank=2) pointed to by TensorRef objects.
template<typename Element >
| bool cutlass::reference::device::BlockCompareEqual | ( | Element const * | ptr_A, |
| | | Element const * | ptr_B, |
| | | size_t | capacity, |
| | | int | grid_size = 0, |
| | | int | block_size = 0 |
| | ) | | |
template<typename Element >
| bool cutlass::reference::device::BlockCompareRelativelyEqual | ( | Element const * | ptr_A, |
| | | Element const * | ptr_B, |
| | | size_t | capacity, |
| | | Element | epsilon, |
| | | Element | nonzero_floor, |
| | | int | grid_size = 0, |
| | | int | block_size = 0 |
| | ) | | |
template<typename Element >
| void cutlass::reference::device::BlockFillRandom | ( | Element * | ptr, | | | | size_t | capacity, | | | | uint64_t | seed, | | | | Distribution | dist | | | ) | | |
template<typename Element >
| void cutlass::reference::device::BlockFillRandomGaussian | ( | Element * | ptr, |
| | | size_t | capacity, |
| | | uint64_t | seed, |
| | | Element | mean = Element(0), |
| | | Element | stddev = Element(1), |
| | | int | bits = -1 |
| | ) | | |
< Element type
< If non-negative, specifies number of fractional bits that are not truncated to zero. Permits reducing precision of data.
Parameters
| seed | seed for RNG | | mean | Gaussian distribution's mean | | stddev | Gaussian distribution's standard deviation |
template<typename Element >
| void cutlass::reference::device::BlockFillRandomUniform | ( | Element * | ptr, |
| | | size_t | capacity, |
| | | uint64_t | seed, |
| | | Element | max = Element(1), |
| | | Element | min = Element(0), |
| | | int | bits = -1 |
| | ) | | |
< If non-negative, specifies number of fractional bits that are not truncated to zero. Permits reducing precision of data.
Parameters
| seed | seed for RNG | | max | upper bound of distribution | | min | lower bound for distribution |
template<typename Element >
| void cutlass::reference::device::BlockFillSequential | ( | Element * | ptr, |
| | | int64_t | capacity, |
| | | Element | v = Element(1), |
| | | Element | s = Element(0) |
| | ) | | |
template<typename ElementA , typename LayoutA , typename ElementB , typename LayoutB , typename ElementC , typename LayoutC , typename ScalarType , typename AccumulatorType , typename InnerProductOp = multiply_add<AccumulatorType>, typename ConvertOp = NumericConverter<ElementC, ScalarType>>
| void cutlass::reference::device::compute_gemm | ( | gemm::GemmCoord | problem_size, | | | | ScalarType | alpha, | | | | TensorRef< ElementA, LayoutA > | tensor_a, | | | | TensorRef< ElementB, LayoutB > | tensor_b, | | | | ScalarType | beta, | | | | TensorRef< ElementC, LayoutC > | tensor_c, | | | | TensorRef< ElementC, LayoutC > | tensor_d, | | | | AccumulatorType | initial_accum | | | ) | | |
Computes a general matrix product among matrices (tensors of rank=2) pointed to by TensorRef objects.
Explicitly naming types needed by this template can be cumbersome, particularly for the accumulator type, so a function argument 'initial_accum' is exposed. Passing AccumulatorType(0) as the last function argument can be easier than naming all template arguments explicitly.
template<typename ElementA , typename LayoutA , typename ElementB , typename LayoutB , typename ElementC , typename LayoutC , typename ScalarType , typename AccumulatorType , typename InnerProductOp = multiply_add<AccumulatorType>, typename ConvertOp = NumericConverter<ElementC, ScalarType>>
| void cutlass::reference::device::compute_gemm | ( | gemm::GemmCoord | problem_size, | | | | ScalarType | alpha, | | | | TensorRef< ElementA, LayoutA > | tensor_a, | | | | TensorRef< ElementB, LayoutB > | tensor_b, | | | | ScalarType | beta, | | | | TensorRef< ElementC, LayoutC > | tensor_c, | | | | AccumulatorType | initial_accum | | | ) | | |
Computes a general matrix product among matrices (tensors of rank=2) pointed to by TensorRef objects.
This assumes the accumulator type is the same type as the scalars.
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorCopyDiagonalIn | ( | TensorView< Element, Layout > | view, | | | | Element const * | ptr | | | ) | | |
< Layout function
< dense buffer of elements
Parameters
| view | destination tensor |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorCopyDiagonalOut | ( | Element * | ptr, | | | | TensorView< Element, Layout > | view | | | ) | | |
< Layout function
< source tensor
Parameters
| ptr | dense buffer of elements |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorFill | ( | TensorView< Element, Layout > | view, |
| | | Element | val = Element(0) |
| | ) | | |
< Layout function
< value to uniformly fill it with
Parameters
| view | destination tensor |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorFillDiagonal | ( | TensorView< Element, Layout > | view, |
| | | Element | diag = Element(1), |
| | | Element | other = Element(0) |
| | ) | | |
< Layout function
< value to write off the diagonal
Parameters
| view | destination tensor | | diag | value to write in the diagonal |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorFillIdentity | ( | TensorView< Element, Layout > | view | ) | |
< Layout function
< destination tensor
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorFillLinear | ( | TensorView< Element, Layout > | view, |
| | | Array< Element, Layout::kRank > const & | v, |
| | | Element | s = Element(0) |
| | ) | | |
< Layout function
Parameters
| view | destination tensor |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorFillRandomGaussian | ( | TensorView< Element, Layout > | view, |
| | | uint64_t | seed, |
| | | Element | mean = Element(0), |
| | | Element | stddev = Element(1), |
| | | int | bits = -1 |
| | ) | | |
< Layout function
< If non-negative, specifies number of fractional bits that are not truncated to zero. Permits reducing precision of data.
Parameters
| view | destination tensor | | seed | seed for RNG | | mean | Gaussian distribution's mean | | stddev | Gaussian distribution's standard deviation |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorFillRandomUniform | ( | TensorView< Element, Layout > | view, |
| | | uint64_t | seed, |
| | | Element | max = Element(1), |
| | | Element | min = Element(0), |
| | | int | bits = -1 |
| | ) | | |
< Layout function
< If non-negative, specifies number of fractional bits that are not truncated to zero. Permits reducing precision of data.
Parameters
| view | destination tensor | | seed | seed for RNG | | max | upper bound of distribution | | min | lower bound for distribution |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorUpdateDiagonal | ( | TensorView< Element, Layout > | view, |
| | | Element | diag = Element(1) |
| | ) | | |
< Layout function
Parameters
| view | destination tensor |
template<typename Element , typename Layout >
| void cutlass::reference::device::TensorUpdateOffDiagonal | ( | TensorView< Element, Layout > | view, |
| | | Element | other = Element(1) |
| | ) | | |
< Layout function
Parameters
| view | destination tensor |
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