C++ Template Support - 2024.1 English

AI Engine-ML Kernel and Graph Programming Guide (UG1603)

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2024.1 English

A template is a powerful tool in C++. By passing the data type as a parameter, you eliminate the need to rewrite code to support different data types. Templates are expanded at compile time, like macros. The difference is that the compiler performs type checking before template expansion. The source code contains template functions and class definitions, but the compiled code can contain multiple copies of same function or class. Type parameters, non-type parameters, default arguments, scalar parameters, and template parameters can be passed to a template, where the compiler instantiates the function or class accordingly.

  • Support for general C++ template features.
  • Supported data types (T) and connection types between kernels:
    • Data type (T): int8, uint8, int16, uint16, cint16, int32, uint32, cint32, int64, uint64, float, and bfloat16(supported only on AI Engine-ML devices).
      Important: acc48 and cacc48 data types are not supported in template stream connections.
  • The compiler does not support pre-compiled headers for template kernels.

Function Templates

Function template source code defines a generic function that can be used for different data types. Example function template:

// add.h

using namespace adf;
template<typename ELEMENT_TYPE, int FACTOR, size_t NUM_SAMPLES> void add(input_buffer<ELEMENT_TYPE> &in, output_buffer<ELEMENT_TYPE> &out);
// add.cpp

#include <aie_api/aie.hpp>
#include <aie_api/aie_adf.hpp>
using namespace adf;
template<typename ELEMENT_TYPE, int FACTOR, size_t NUM_SAMPLES> void add(input_buffer<ELEMENT_TYPE> &in, output_buffer<ELEMENT_TYPE> &out){
  auto inIter=aie::begin(in);
  auto outIter=aie::begin(out);
  for (int i=0; i<NUM_SAMPLES; i++){
    ELEMENT_TYPE value = *inIter++;
    value += FACTOR;
// graph.h
    k[0] = kernel::create(add<int32, 6, 8>);
    k[1] = kernel::create(add<int16, 3, 8>);
    for (int i=0; i<NUM_KERNELS; i++)
        runtime<ratio>(k[i]) = 0.3;
        source(k[i]) = "src/add.cpp";

    connect(in[0], k[0].in[0]);
    connect(k[0].out[0], out[0]);

    connect(in[1], k[1].in[0]);
    connect(k[1].out[0], out[1]);


  • add.h defines a template add() function.
  • add.cpp defines the code for the template add() function.
  • graph.h uses the template add() function within mygraph class.

Class Templates

Like function templates, class templates are useful when a class defines an object that is independent of a specific data type. Example class template:

// fir.h
template<size_t NUM_COEFFS, typename ELEMENT_TYPE> class FIR
    uint32 numSamples;

    FIR(ELEMENT_TYPE(&coefficients)[NUM_COEFFS], uint32 samples);

    void filter(input_buffer<ELEMENT_TYPE> &in, output_buffer<ELEMENT_TYPE> &out);

    //user needs to write this function to register necessary info
    static void registerKernelClass()
// fir.cpp
template<size_t NUM_COEFFS, typename ELEMENT_TYPE> FIR<NUM_COEFFS, ELEMENT_TYPE>::FIR(ELEMENT_TYPE(&coefficients)[NUM_COEFFS], uint32 samples):coeffs(coefficients)

template<size_t NUM_COEFFS, typename ELEMENT_TYPE> void FIR<NUM_COEFFS,ELEMENT_TYPE>::filter(input_buffer<ELEMENT_TYPE> &in, output_buffer<ELEMENT_TYPE> &out)
// graph.h
    k1 = kernel::create_object<FIR<12, int32>>(std::vector<int>({ 180, 89, -80, -391, -720, -834, -478, 505, 2063, 3896, 5535, 6504 }), 8);
    runtime<ratio>(k1) = 0.1;
    source(k1) = "src/fir.cpp";
    headers(k1) = { "src/fir.h" };

    k2 = kernel::create_object<FIR<15, int32>>(std::vector<int>({ -21, -249, 319, -78, -511, 977, -610, -844, 2574, -2754, -1066, 18539, 0, 0, 0 }), 8);
    runtime<ratio>(k2) = 0.1;
    source(k2) = "src/fir.cpp";
    headers(k2) = { "src/fir.h" };


  • fir.h defines a class template where class FIR is declared.
  • fir.cpp contains class FIR implementation and the class FIR member function filter implementation.
  • graph.h demonstrates the template class FIR instantiation within the mygraph class.