133 lines
3.8 KiB
Nim

{.push raises:[].}
# import constantine/named/properties_fields
import taskpools
import groth16/bn128
import groth16/bn128/arrays
import groth16/misc
import groth16/math/domain
import groth16/math/group_fft
import groth16/math/poly
import groth16/math/convolution
import groth16/math/convert
# import groth16/math/ntt
import groth16/zkey_types
import groth16/dynamic/types
import groth16/dynamic/shared
#-------------------------------------------------------------------------------
# let deltaImgA = sparseMatrixImage( A , delta_mask )
# let deltaImgB = sparseMatrixImage( B , delta_mask )
# let deltaImgAB = orBoolSeqs( deltaImgA , deltaImgB )
#-------------------------------------------------------------------------------
# the points `delta^{-1} * phi_ii(tau) * (tau^N - 1) * g1` as in the Dynark paper
#
# where
#
# > phi_ii = - sum_j phi_ij = - sum_j ( W[j-i]*L[i] + W[i-j]*L[j] )
# > phi_ij = W[j-i]*L[i] + W[i-j]*L[j]
#
func calculateDiagPhiFFT*( wvec: seq[F], deltaLZ: seq[G1] ): seq[G1] =
let N = wvec.len
assert( N == deltaLZ.len )
let sumW = sumSeqFr( wvec )
var hs: seq[G1] = groupConvolution( wvec , deltaLZ )
for i in 0..<N:
hs[i] += (sumW ** deltaLZ[i])
hs[i] = negG1(hs[i])
return hs
# NOTE: this is EXTREMELY SLOW
proc calculateDiagPhiNaive*( wvec: seq[F], deltaLZ: seq[G1], pool: Taskpool ): seq[G1] =
let N = wvec.len
assert( N == deltaLZ.len )
let sumW = sumSeqFr( wvec )
var diagPhi: seq[G1] = newSeq[G1]( N )
for i in 0..<N:
var ws: seq[F] = newSeq[F]( N )
for j in 0..<N:
if i != j:
ws[j] = wvec[ safeMod(i-j , N) ]
else:
ws[j] = sumW
diagPhi[i] = negG1( msmMultiThreadedG1( ws, deltaLZ, pool ) )
return diagPhi
#-------------------------------------------------------------------------------
# does the setup from the ZKey (prover key)
proc dynaSetupV1FromZKey*(zkey: Zkey, pool: Taskpool ): DynaSetupV1 =
let N = zkey.header.domainSize
let D = createDomain(N)
var deltaZTau : seq[G1] # the points `delta^-1 * (tau^N-1) * tau^i * g1`
case zkey.header.flavour
of JensGroth:
deltaZTau = zkey.pPoints.pointsH1
of Snarkjs:
echo "Jordi-style .zkey detected; converting points! (slow...)"
withMeasureTime(true,"Jordi-to-Jens conversion"):
deltaZTau = convertPointsFromJordi(D , zkey.pPoints.pointsH1)
let sumW = sumOfWVec( N )
let wvec = calculateWVec( D )
let deltaLZ = inverseGroupFFT( deltaZTau , D )
let conv = groupConvolution( wvec , deltaLZ )
var diagPhi : seq[G1]
var diagPhi2 : seq[G1]
withMeasureTime(true,"phi diagonal took"):
diagPhi = calculateDiagPhiFFT( wvec , deltaLZ )
echo "agree = " & $isEqualG1Seq( diagPhi , diagPhi2 )
return DynaSetupV1( weightVec : wvec ,
pointsDeltaLZ : deltaLZ ,
wConvDeltaLZ : conv ,
diagPhiPoints : diagPhi )
#---------------------------------------
# simulates a setup (from the "toxic waste" values `tau` and `delta`), so that
# we can test components of the system
func simulateDynaSetupV1*( D: Domain, tau: F, delta: F ): DynaSetupV1 =
let N = D.domainSize
let ztau: F = smallPowFr(tau,N) - oneFr
let deltaZTau: F = ztau / delta
# compute `delta^-1 * L_i(tau) * (tau^N - 1) ** g1
var deltaLZ: seq[G1] = newSeq[G1]( N )
for i in 0..<N:
let y: F = deltaZTau * evalLagrangePolyAt( D, i, tau )
deltaLZ[i] = y ** gen1
let wvec = calculateWVec( D )
let conv = groupConvolution( wvec , deltaLZ )
let diagPhi = calculateDiagPhiFFT( wvec , deltaLZ )
return DynaSetupV1( weightVec : wvec ,
pointsDeltaLZ : deltaLZ ,
wConvDeltaLZ : conv ,
diagPhiPoints : diagPhi )
#-------------------------------------------------------------------------------