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| # Gemmlowp's public entry points | ||
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| gemmlowp's public interface is defined in | ||
| [public/gemmlowp.h](../public/gemmlowp.h). | ||
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| ## GemmWithOutputPipeline | ||
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| The primary public entry point is: `GemmWithOutputPipeline`. | ||
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| A usage example is given in | ||
| [doc/quantization_example.cc](quantization_example.cc). | ||
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| The prototype is: | ||
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| ``` | ||
| template <typename InputScalar, typename OutputScalar, typename BitDepthParams, | ||
| MapOrder LhsOrder, MapOrder RhsOrder, MapOrder ResultOrder, | ||
| typename OutputPipelineType, typename GemmContextType> | ||
| void GemmWithOutputPipeline(GemmContextType* context, | ||
| const MatrixMap<const InputScalar, LhsOrder>& lhs, | ||
| const MatrixMap<const InputScalar, RhsOrder>& rhs, | ||
| MatrixMap<OutputScalar, ResultOrder>* result, | ||
| int lhs_offset, int rhs_offset, | ||
| const OutputPipelineType& output_pipeline); | ||
| ``` | ||
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| A typical call looks like (from the [usage example](quantization_example.cc)): | ||
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| ``` | ||
| gemmlowp::GemmWithOutputPipeline<std::uint8_t, std::uint8_t, | ||
| gemmlowp::DefaultL8R8BitDepthParams>( | ||
| &gemm_context, uint8_lhs_matrix, uint8_rhs_matrix, | ||
| &uint8_result_matrix, lhs_offset, rhs_offset, output_pipeline); | ||
| ``` | ||
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| ### Template parameters | ||
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| Typically only the 3 first template parameters need to be specified, the rest | ||
| being automatically deduced from function parameters: | ||
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| * `InputScalar`: The scalar type of the LHS and RHS operands. At the moment, | ||
| this must be `std::uint8_t`. | ||
| * `OutputScalar`: The scalar type of the LHS and RHS operands. At the moment, | ||
| this must be `std::uint8_t`. | ||
| * `BitDepthParams`: Defines the bit format of the input and output matrices | ||
| and the required accuracy of the computation. At the moment, the only | ||
| non-deprecated valid value is `gemmlowp::DefaultL8R8BitDepthParams`. See | ||
| [less-than-8-bit.md](less-than-8-bit.md) for other values and the general | ||
| idea of this, and how it may become more useful in the future. | ||
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| The other template parameters, which typically do not need to be specified, are: | ||
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| * `LhsOrder`, `RhsOrder`, `ResultOrder`: the storage orders (row-major or | ||
| column-major) of the LHS, RHS, result matrices. See | ||
| [public/map.h](../public/map.h). See the below performance note: we | ||
| recommend using respectively RowMajor, ColMajor, ColMajor for optimal | ||
| performance. | ||
| * `OutputPipelineType`: the actual `std::tuple` type of the output pipeline. | ||
| See below explanation of the `output_pipeline` parameter, and | ||
| [output.md](output.md). | ||
| * `GemmContextType`: the type of the `context` parameter. At the moment, this | ||
| must be `gemmlowp::GemmContext`. | ||
|
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| ### Function parameters | ||
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| The function parameters taken by `GemmWithOutputPipeline` are: | ||
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| * `context`: The `gemmlowp::GemmContext` object holding state and resources to | ||
| be used for this gemmlowp call. | ||
| * `lhs`, `rhs`: The LHS and RHS operand matrices. Note that these are | ||
| `MatrixMap` objects, mapping external buffers as matrices, not owning data. | ||
| See [public/map.h](../public/map.h). | ||
| * `result`: pointer to the destination `MatrixMap` object, which must be | ||
| already constructed, wrapping the external destination buffer with the | ||
| wanted destination matrix shape and storage layout. No memory allocation | ||
| will be performed by gemmlowp for the destination buffer. See | ||
| [public/map.h](../public/map.h). | ||
| * `lhs_offset`, `rhs_offset` are constants added to each matrix entry in the | ||
| LHS, RHS matrices respectively, as explained in | ||
| [low-precision.md](low-precision.md). This is only the part of the | ||
| quantization paradigm explained in [quantization.md](quantization.md) that | ||
| needs to be implemented as operations on the operands; everything else is | ||
| operations on the result, see `output_pipeline`. | ||
| * `output_pipeline` is a `std::tuple` of output stages (see | ||
| [public/output_stages.h](../public/output_stages.h)), specifying the output | ||
| pipeline (see [output.md](output.md)). This is the part of the quantization | ||
| paradigm explained in [quantization.md](quantization.md) that needs to be | ||
| implemented as operations on the result matrix. | ||
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| ### Performance note on storage orders. | ||
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| gemmlowp supports arbitrary combinations of storage orders for the LHS, RHS and | ||
| result matrices. However, not all are equally optimized for. | ||
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| Because gemmlowp is primarily aimed at neural network inference workloads, | ||
| optimization focus is on this particular combination of storage orders: | ||
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| * `LhsOrder=RowMajor` | ||
| * `RhsOrder=ColMajor` | ||
| * `ResultOrder=ColMajor` | ||
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| The rationale is that the LHS is typically the constant weights of a neural | ||
| network layer (e.g. the weights of a Convolutional layer implemented as a matrix | ||
| multiplication), while the RHS and result are neural network activations, | ||
| respectively the input and output activations of the layer. | ||
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| Because the RHS and result are activations, we want them to share the same | ||
| storage order -- so that one layer's output activations can be readily used as | ||
| the next layer's input activations. Thus, we focus on `RhsOrder=ResultOrder`. | ||
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| We also know from general considerations on matrix multiplication that it is | ||
| slightly more efficient to have the direction of accumulation (the "depth" | ||
| dimension) be the direction of contiguous storage in memory. That means that it | ||
| is always going to be slightly easier and more efficient to have | ||
| `LhsOrder=RowMajor` and `RhsOrder=ColMajor`. | ||
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| Putting this together, we arrive at gemmlowp's focus on the above-described | ||
| combination of storage orders. | ||
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| Using other storage orders will typically mean taking less efficient paths in | ||
| the packing and unpacking stages, see [packing.md](packing.md). The compute | ||
| kernel stage ([kernel.md](kernel.md)) is unaffected. | ||
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| ## GemmWithOutputPipelinePC | ||
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| This is a variant where `lhs_offset` and `rhs_offset` may be vectors instead of | ||
| scalar. They are then broadcasted against LHS, RHS respectively. | ||
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| This is useful for some flavors of neural network inference with "per-channel | ||
| quantization", whence the PC suffix. This has been useful in some settings where | ||
| a neural network trained in float arithmetic was subsequently quantized. On the | ||
| other hand, retraining neural networks for quantized inference tends to remove | ||
| the need for per-channel quantization. For that reason, the long-term usefulness | ||
| of this entry point is in question. | ||
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| ## Gemm | ||
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| This is gemmlowp's original, now legacy and deprecated, entry point. See the | ||
| section of [low-precision.md](low-precision.md) on the legacy quantization | ||
| paradigm. Avoid in new code. | ||
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| ## The eight_bit_int_gemm directory | ||
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| As explained in the top-level [README.md](../README.md#public-interfaces), this | ||
| is entirely deprecated. |
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