privateHLA/params.go at main · SNUCP/privateHLA · GitHub

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package hla

import (
	"math"

	"github.com/sp301415/tfhe-go/tfhe"
)

var (
	// FloatParamsLiteral is the parameters for floating-point operations.
	// It has much lower failure rate, around 2^-16.
	FloatParamsLiteral = tfhe.ParametersLiteral[uint64]{
		LWEDimension:    978,
		GLWERank:        1,
		PolyDegree:      2048,
		LookUpTableSize: 4096,

		LWEStdDev:  0.00000010240471256147537,
		GLWEStdDev: 0.00000000000000037036182440289164,

		BlockSize: 6,

		MessageModulus: 1 << 7,

		BlindRotateParameters: tfhe.GadgetParametersLiteral[uint64]{
			Base:  1 << 22,
			Level: 1,
		},
		KeySwitchParameters: tfhe.GadgetParametersLiteral[uint64]{
			Base:  1 << 6,
			Level: 3,
		},

		BootstrapOrder: tfhe.OrderKeySwitchBlindRotate,
	}

	// IntParamsLiteral is the parameters for integer operations.
	// This has standard failure rate, around 2^-64.
	IntParamsLiteral = tfhe.ParametersLiteral[uint64]{
		LWEDimension:    978,
		GLWERank:        1,
		PolyDegree:      2048,
		LookUpTableSize: 2048,

		LWEStdDev:  0.00000010240471256147537,
		GLWEStdDev: 0.00000000000000037036182440289164,

		BlockSize: 6,

		MessageModulus: 1 << 5,

		BlindRotateParameters: tfhe.GadgetParametersLiteral[uint64]{
			Base:  1 << 22,
			Level: 1,
		},
		KeySwitchParameters: tfhe.GadgetParametersLiteral[uint64]{
			Base:  1 << 6,
			Level: 3,
		},

		BootstrapOrder: tfhe.OrderKeySwitchBlindRotate,
	}

	// PredictionBound is a bound for the predicted values.
	// All predictions must be in the range (-PredictionBound, PredictionBound).
	PredictionBound = 40.0

	// ScaleSnip is the scale for the ciphertexts ("Snips").
	ScaleSnip = math.Exp2(40)

	// ScaleWeight is the scale for the plaintexts ("Weights").
	// Due to correctness, we require that 2*PredictionBound*ScaleSnip*ScaleWeight < Q/4,
	// i.e. has at least 1 bit of padding (on top of the usual negacyclic padding).
	ScaleWeight = math.Exp2(62) / (PredictionBound * ScaleSnip)

	// NormalizeBound is a bound for "Normalizing" the predictions.
	// We use a ReLU-like function.
	NormalizeBound = -13.0

	// CompareThreshold is a threshold for comparing the predictions.
	CompareThreshold = 15.0
)