Perf: Improve MultiLin.Eval number of constraints

[Tabaie]

Evaluation of large multilinear extensions is a major bottleneck in GKR verification. Currently the hypercube bases are evaluated at the requested point and the linear combination of these results with the corresponding hypercube values is taken. A massive reduction in the number of constraints can be achieved by performing successive foldings instead. For the 20-variable case we get

develop:
r1cs: 2100657 constraints
scs : 4194301 constraints

opt1 (successive fold):
r1cs: 1048576 constraints 49%
scs: 3145726 constraints 75%

a 25% improvement for SCS.

A second optimization defers scaling of folding operations which is corrected at the end. My experiments suggest that this starts paying off at around the $2^{16}$ size. It doesn't help with R1CS at all, but doesn't hurt significantly either. With SCS we see significant additional gains:

ops 1&2 (successive fold + defer scaling for large sizes):

r1cs: 1048627 constraints 50%
scs: 2097226 constraints 50%

[ivokub]

Confirming @AlexandreBelling approval.