Detailed Description

Tiling optimizer for SMV convolution kernel.

Definition at line 19 of file smv_convolution_tiling.h.

Static Public Member Functions
static std::array< TiledTensor, 3 >	doTiling (SmvConvolutionOp *op)

static TilingConfig	computeBasicTileShapes (SmvConvolutionOp *op)
	Determine the best basic tiling shape for this convolution layer. More...

static TiledTensor	generateRowwiseOutputTiledTensor (SmvConvolutionOp op, const TiledTensor &inputTiledTensor, const TiledTensor &weightsTiledTensor, const TensorShape &maxOutputTileSize, Tensor outputTensor, bool copyData=false)
	A specialized output tiling function when the output is tiled rowwise. More...

Static Protected Member Functions
static std::array< TilingDims, 3 >	determineBestTilingDims (Tensor inputs, Tensor weights, Tensor *outputs, int maxTileSize)
	Determine the best tiling dimensions for running convolution on SMV. More...

Static Protected Member Functions inherited from smaug::smv::TilingOptimizerBase
static TilingDims	findBestTilingDims (const TensorShape &shape, int maxTileSize, const std::vector< int > &minShape)
	Find the best set of dimensions to tile a given tensor shape. More...

static void	enum2DTensorTilingConfigs (TensorShape shape, int maxTileSize, const std::vector< int > &minShape, const std::vector< int > &strides, std::vector< TensorShape > &configs)
	Enumerates all tiling configs for a two dimensional Tensor. More...

static void	enum4DTensorTilingConfigs (TensorShape shape, int maxTileSize, const std::vector< int > &minShape, const std::vector< int > &strides, std::vector< TensorShape > &configs)
	Enumerates all tiling configs for a four dimensional Tensor. More...

Member Function Documentation

◆ computeBasicTileShapes()

TilingConfig smaug::smv::conv::TilingOptimizer::computeBasicTileShapes ( SmvConvolutionOp * op )

static

Determine the best basic tiling shape for this convolution layer.

The algorithm first determines the dimensions along which the inputs, weights, and outputs will be tiled. Then based on those dimensions, we enumerate all possible basic tile shapes for inputs, weights, and outputs. A basic shape is the shape that all but potentially the last tile along a set of dimensions will use. This triplet of tile shapes defines a TilingConfig. The TilingConfig that maximizes the total combined size of input, weights, and output tiles is chosen as the best.

To limit the number of possibilities, we only enumerate each dimension in certain increments. For example, input channels are only enumerated in multiples of kNumMaccsPerPE, and output channels are only enumerated in multiples in kNumPEs.

This algorithm assumes that the maximum tile size for weights, inputs, and outputs are all the same and that they will reside in separate scratchpads (no sharing).

Parameters

op	The SMV convolution operator. All tensors must have been created with createAllTensors() prior to calling this function.

Returns: The TilingConfig that describes the best tiling shapes.

Definition at line 57 of file smv_convolution_tiling.cpp.

◆ determineBestTilingDims()

std::array< TilingDims, 3 > smaug::smv::conv::TilingOptimizer::determineBestTilingDims	(	Tensor *	inputs,
		Tensor *	weights,
		Tensor *	outputs,
		int	maxTileSize
	)

staticprotected

Determine the best tiling dimensions for running convolution on SMV.

This function imposes some additional constraints on the tiling dimensions, in that certain combinations of input/weight/output tiling dimensions are not allowed in the interest of tiling code complexity.

Returns: A 3-element array of TilingDims enums (inputs, weights, outputs).

Definition at line 13 of file smv_convolution_tiling.cpp.

◆ generateRowwiseOutputTiledTensor()

TiledTensor smaug::smv::conv::TilingOptimizer::generateRowwiseOutputTiledTensor	(	SmvConvolutionOp *	op,
		const TiledTensor &	inputTiledTensor,
		const TiledTensor &	weightsTiledTensor,
		const TensorShape &	maxOutputTileSize,
		Tensor *	outputTensor,
		bool	copyData = `false`
	)

static

A specialized output tiling function when the output is tiled rowwise.

This accounts for additional corner cases in filter field size and zero-padding that arise with specific inputs/weights tile sizes.

Definition at line 249 of file smv_convolution_tiling.cpp.

The documentation for this class was generated from the following files:

smaug/operators/smv/smv_convolution_tiling.h
smaug/operators/smv/smv_convolution_tiling.cpp

Detailed Description

Static Public Member Functions

Static Protected Member Functions

Member Function Documentation

◆ computeBasicTileShapes()

◆ determineBestTilingDims()

◆ generateRowwiseOutputTiledTensor()