API Operation Examples - 2024.1 English

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

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2024.1 English

The following example takes two vectors with reals in rva and imaginary in rvb (with type aie::vector<int32,8>) and creates a new complex vector, using the offsets to interleave the values as required.

aie::vector<int32,8> rva,rvb;
auto rv=aie::interleave_zip(rva,rvb,1);
aie::vector<cint32,8> cv=aie::concat(rv.first.cast_to<cint32>(),rv.second.cast_to<cint32>());

The following example shows how to extract real and imaginary portion of a vector cv with type aie::vector<cint32,8>.

aie::vector<cint32,8> cv;
aie::vector<int32,16> re_im=cv.cast_to<int32>();
aie::vector<int32,8> re=aie::filter_even(re_im,1);
aie::vector<int32,8> im=aie::filter_odd(re_im,1);

aie::broadcast can be used to set every element of a vector to a given value. The following example shows how to implement a function to set all four elements in a vector to a constant value.

aie::vector<int32,8> v1=aie::broadcast<int32,8>(100); //set all elements to 100

The following example shows how to use aie::broadcast to set multiple values repeatedly in the vector.

alignas(aie::vector_decl_align) int16 init_data[16]={0,1,2,3,4,5,6,7,8,9,10,11,12,13,14,15};
aie::vector<int16,32> buff=aie::broadcast<cint32,8>(*(cint32*)init_data).cast_to<int16>();//set 0 1 2 3 repeatedly into buff
//buff=0 1 2 3 0 1 2 3 0 1 2 3 0 1 2 3 0 1 2 3 0 1 2 3 0 1 2 3 0 1 2 3

The following example shows how to multiply each element in rva by the first element in rvb. This is efficient for a vector multiplied by constant value.

aie::vector<int16,16> rva,rvb;
auto acc = aie::mul(rva,rvb[0]);

The following examples show how to multiply each element in rva by its corresponding element in rvb.

aie::vector<int16,16> va,vb;
auto acc=aie::mul(va,vb);

The following examples show how to perform matrix multiplication for int8 x int8 data types with mmul intrinsic, assuming that data storage is row based.

//Z_{2x8} * X_{8x8} = A_{2x8}
aie::vector<int8,16> Z;
aie::vector<int8,64> X;
aie::mmul<2,8,8,int8,int8> m;
//Z_{4x8} * X_{8x4} = A_{4x4}
aie::vector<int8,32> Z;
aie::vector<int8,32> X;
aie::mmul<4,8,4,int8,int8> m;

For more information about vector lane permutations, see the AI Engine ML Intrinsics User Guide (UG1583).