bool ChooserEvaluator::select_parameters(const std::vector<ChooserPoly> &operands, double noise_standard_deviation, double noise_max_deviation, const std::map<int, BigUInt> ¶meter_options, EncryptionParameters &destination)
{
if (noise_standard_deviation < 0)
{
throw invalid_argument("noise_standard_deviation can not be negative");
}
if (noise_max_deviation < 0)
{
throw invalid_argument("noise_max_deviation can not be negative");
}
if (parameter_options.size() == 0)
{
throw invalid_argument("parameter_options must contain at least one entry");
}
if (operands.empty())
{
throw invalid_argument("operands cannot be empty");
}
int largest_bit_count = 0;
int largest_coeff_count = 0;
for (vector<ChooserPoly>::size_type i = 0; i < operands.size(); ++i)
{
if (operands[i].comp_ == nullptr)
{
throw logic_error("no operation history to simulate");
}
int current_bit_count = operands[i].max_abs_value_.significant_bit_count();
largest_bit_count = (current_bit_count > largest_bit_count) ? current_bit_count : largest_bit_count;
int current_coeff_count = operands[i].max_coeff_count_;
largest_coeff_count = (current_coeff_count > largest_coeff_count) ? current_coeff_count : largest_coeff_count;
}
// We restrict to plain moduli that are powers of two. Here largest_bit_count is the largest positive
// coefficient that we can expect to appear. Thus, we need one more bit.
destination.plain_modulus() = 1;
destination.plain_modulus() <<= largest_bit_count;
bool found_good_parms = false;
map<int, BigUInt>::const_iterator iter = parameter_options.begin();
while (iter != parameter_options.end() && !found_good_parms)
{
int dimension = iter->first;
if (dimension < 512 || (dimension & (dimension - 1)) != 0)
{
throw invalid_argument("parameter_options keys invalid");
}
if (dimension > largest_coeff_count && destination.plain_modulus() < iter->second)
{
// Set the polynomial
destination.coeff_modulus() = iter->second;
destination.poly_modulus().resize(dimension + 1, 1);
destination.poly_modulus().set_zero();
destination.poly_modulus()[0] = 1;
destination.poly_modulus()[dimension] = 1;
// The bound needed for GapSVP->search-LWE reduction
//parms.noise_standard_deviation() = round(sqrt(dimension / (2 * 3.1415)) + 0.5);
// Use constant (small) standard deviation.
destination.noise_standard_deviation() = noise_standard_deviation;
// We truncate the gaussian at noise_max_deviation.
destination.noise_max_deviation() = noise_max_deviation;
// Start initially with the maximum decomposition_bit_count, then decrement until decrypts().
destination.decomposition_bit_count() = destination.coeff_modulus().significant_bit_count();
// We bound the decomposition bit count value by 1/8 of the maximum. A too small
// decomposition bit count slows down multiplication significantly. This is not an
// issue when the user wants to use multiply_norelin() instead of multiply(), as it
// only affects the relinearization step. The fraction 1/8 is not an optimal choice
// in any sense, but was rather arbitrarily chosen. An expert user might want to tweak this
// value to be smaller or larger depending on their use case.
// To do: Figure out a somewhat optimal bound.
int min_decomposition_bit_count = destination.coeff_modulus().significant_bit_count() / 8;
while (!found_good_parms && destination.decomposition_bit_count() > min_decomposition_bit_count)
{
found_good_parms = true;
for (vector<ChooserPoly>::size_type i = 0; i < operands.size(); ++i)
{
// If one of the operands does not decrypt, set found_good_parms to false.
found_good_parms = operands[i].simulate(destination).decrypts() ? found_good_parms : false;
}
if (!found_good_parms)
{
--destination.decomposition_bit_count();
}
else
{
// We found some good parameters. But in fact we can still decrease the decomposition count
// a little bit without hurting performance at all.
int old_dbc = destination.decomposition_bit_count();
int num_parts = destination.coeff_modulus().significant_bit_count() / old_dbc + (destination.coeff_modulus().significant_bit_count() % old_dbc != 0);
destination.decomposition_bit_count() = destination.coeff_modulus().significant_bit_count() / num_parts + (destination.coeff_modulus().significant_bit_count() % num_parts != 0);
}
}
}
// This dimension/coeff_modulus are to small. Move on to the next pair.
++iter;
}
if (!found_good_parms)
{
destination = EncryptionParameters();
}
return found_good_parms;
}
bool ChooserEvaluator::select_parameters(
const std::vector<ChooserPoly> &operands,
int budget_gap, double noise_standard_deviation,
const map<int, vector<SmallModulus> > &coeff_modulus_options,
EncryptionParameters &destination)
{
if (budget_gap < 0)
{
throw std::invalid_argument("budget_gap cannot be negative");
}
if (noise_standard_deviation < 0)
{
throw invalid_argument("noise_standard_deviation can not be negative");
}
if (coeff_modulus_options.size() == 0)
{
throw invalid_argument("parameter_options must contain at least one entry");
}
if (operands.empty())
{
throw invalid_argument("operands cannot be empty");
}
int largest_bit_count = 0;
int largest_coeff_count = 0;
for (size_t i = 0; i < operands.size(); i++)
{
if (operands[i].comp_ == nullptr)
{
throw logic_error("no operation history to simulate");
}
int current_bit_count = get_significant_bit_count(operands[i].max_abs_value_);
largest_bit_count = (current_bit_count > largest_bit_count) ?
current_bit_count : largest_bit_count;
int current_coeff_count = operands[i].max_coeff_count_;
largest_coeff_count = (current_coeff_count > largest_coeff_count) ?
current_coeff_count : largest_coeff_count;
}
// We restrict to plain moduli that are powers of two. Here largest_bit_count
// is the largest positive coefficient that we can expect to appear. Thus, we
// need one more bit.
uint64_t new_plain_modulus;
if (largest_bit_count >= SEAL_USER_MODULO_BIT_BOUND)
{
// The plain_modulus needed is too big
return false;
}
new_plain_modulus = 1ULL << largest_bit_count;
destination.set_plain_modulus(new_plain_modulus);
bool found_good_parms = false;
map<int, vector<SmallModulus> >::const_iterator iter = coeff_modulus_options.begin();
while (iter != coeff_modulus_options.end() && !found_good_parms)
{
int dimension = iter->first;
if (dimension < 512 || (dimension & (dimension - 1)) != 0)
{
throw invalid_argument("coeff_modulus_options keys invalid");
}
int coeff_bit_count = 0;
for(auto mod : iter->second)
{
coeff_bit_count += mod.bit_count();
}
if (dimension > largest_coeff_count &&
coeff_bit_count > destination.plain_modulus().bit_count())
{
// Set the polynomial
destination.set_coeff_modulus(iter->second);
BigPoly new_poly_modulus(dimension + 1, 1);
new_poly_modulus.set_zero();
new_poly_modulus[0] = 1;
new_poly_modulus[dimension] = 1;
destination.set_poly_modulus(new_poly_modulus);
// The bound needed for GapSVP->search-LWE reduction
//parms.noise_standard_deviation() = round(sqrt(dimension / (2 * 3.1415)) + 0.5);
// Use constant (small) standard deviation.
destination.set_noise_standard_deviation(noise_standard_deviation);
found_good_parms = true;
for (size_t i = 0; i < operands.size(); i++)
{
// If one of the operands does not decrypt, set found_good_parms to false.
found_good_parms = operands[i].simulate(destination).decrypts(budget_gap) ?
found_good_parms : false;
}
}
// This dimension/coeff_modulus are to small. Move on to the next pair.
iter++;
}
if (!found_good_parms)
{
destination = EncryptionParameters();
}
return found_good_parms;
}
