AI Engine architectures offer multiplication instructions that can perform additional operations on the input arguments. Instead of adding one variant for each possible combination, AI Engine API offers types that can wrap an existing vector, accumulator of element reference and be passed into the multiplication function. Then the API will merge the operations into a single instruction or apply the operation on the vector before the multiplication, depending on the hardware support.
The pre-multiplication operations are special empty operations that simply return the original objects they wrap. These include:
-
op_abs -
op_add -
op_conj -
op_max -
op_min -
op_none -
op_sub -
op_sign -
op_zero
The following example performs an element-wise multiplication of the
absolute of vector a and the conjugate of vector
b.
aie::accum<cacc48,16> foo(aie::vector<int16,16> a, aie::vector<cint16,16> b){
aie::accum<cacc48,16> ret;
ret = aie::mul(aie::op_abs(a), aie::op_conj(b));
return ret;
}alignas(aie::vector_decl_align) int16 data[16]=0,-1,2,-3,4,-5,6,-7,8,-9,10,-11,12,-13,14,-15};
aie::vector<int16,16> a=aie::load_v<16>(data);
aie::vector<int16,16> b=aie::load_v<16>(data);
aie::accum<acc48,16> ret;
bool is_zero=true;
bool is_sign=true;
ret = aie::mac(aie::op_zero(ret,is_zero),aie::op_sign(a,is_sign), aie::op_sign(b,is_sign));
aie::print(ret,true,"ret=");
//Output: ret=0x00000000 0x00000001 0x00000004 0x00000009 0x000000010 0x000000019 0x000000024 0x000000031 0x000000040 0x000000051 0x000000064 0x000000079 0x000000090 0x0000000a9 0x0000000c4 0x0000000e1