Exemplo n.º 1
0
func (u *ΔUpdater) Update() {

	qin := u.in.Array()
	qout := u.out.Array()
	q0 := u.q0.Array()

	qinMul := u.in.Multiplier()
	qoutMul := u.out.Multiplier()
	q0Mul := u.q0.Multiplier()

	COMP := u.in.NComp()
	pre := make([]float64, COMP)

	for ii := 0; ii < COMP; ii++ {
		qoutMul[ii] = qinMul[ii]
		pre[ii] = -q0Mul[ii] / qinMul[ii] //0?
	}

	switch COMP {
	case 1:
		gpu.Madd(qout.Component(0), qin.Component(0), q0.Component(0), pre[0])
	case 3:
		gpu.VecMadd(qout, qin, q0, pre)
	default:
		panic(InputErrF("Δ is not implemented for NComp: ", COMP))
	}

}
Exemplo n.º 2
0
func (u *SumUpdater) addTerms() {
	// TODO: optimize for 0,1,2 or more parents
	sum := u.sum
	parents := u.parents
	if sum.IsSpaceDependent() {
		for i := range parents {
			parent := parents[i]
			weight := u.weight[i]

			parMul := make([]float64, sum.NComp())

			for c := 0; c < sum.NComp(); c++ {
				parMul[c] = weight * parent.Multiplier()[c] / sum.Multiplier()[c]
			}

			switch sum.NComp() {
			case 1:
				gpu.Madd(sum.array.Component(0), sum.array.Component(0), parent.array.Component(0), parMul[0])
			case 3:
				gpu.VecMadd(sum.Array(), sum.Array(), parent.Array(), parMul)
			default:
				panic(InputErr("sum is not implemented for NComp: " + fmt.Sprint(sum.NComp())))
			}

		}
	} else {
		for p, parent := range parents {
			for c := range sum.multiplier {
				sum.multiplier[c] += parent.multiplier[c] * u.weight[p]
			}
		}
	}
}