Systems and methods for end-to-end encryption and compression are described herein. A query is encrypted at a client using a homomorphic encryption scheme. The encrypted query is sent to a server where the encrypted query is evaluated over target data to generate encrypted response without decrypting the encrypted query. The result elements of the encrypted response are grouped, co-located, and compressed, without decrypting the encrypted query or the encrypted response. The compressed encrypted response is sent to the client where it is decrypted and decompressed to obtain the results of the query without revealing the query or results to the owner of the target data, an observer, or an attacker.

A curve function device and an operation method thereof are provided. The curve function device includes a lookup table, a weight calculation circuit, and a linear function circuit. According to first partial bits of an input value, a bias value of a current segment and a bias value of a next segment can be extracted from the lookup table. The weight calculation circuit can calculate a weight value of the current segment according to the bias value of the current segment and the bias value of the next segment. The linear function circuit can calculate a linear function value by using the bias value of the current segment, the weight value of the current segment, and second partial bits of the input value. This linear function value can be used as an approximate value of the curve function.

A method is provided for solving a computational problem that is reducible to a problem of counting solutions to an associated decision problem. The method includes estimating a number of the solutions to the decision problem using a quantum computer by determining if there is at least one simultaneous solution to both (i) the decision problem and (ii) an associated hashing problem. The method also includes increasing a precision of the estimated number of the solutions to the decision problem using the quantum computer by determining if there are multiple solutions to the decision problem that are simultaneously solutions to the associated hashing problem. The method further includes outputting or using the estimated number of the solutions to the decision problem as a solution to the computational problem.

An execution unit for a processor, the execution unit comprising: a look up table; a preparatory circuit configured to determine an index value in dependence upon the operand and search the look up table using the index value to locate an entry comprising a natural logarithm associated with the index value; control circuitry configured to provide a first value determined in dependence upon the operand and a second value determined in dependence upon the operand as inputs to at least one multiplier circuit of the execution unit so as to evaluate terms of a Taylor series expansion of a natural logarithm, wherein the control circuitry is configured to provide the natural logarithm associated with the index value and the terms of the Taylor series expansion as inputs to at least one addition circuit so as to generate a mantissa of a natural logarithm of the operand.

Embodiments of a telemetry device and methods to convert a binary floating point number to a compressed number is described herein. The binary floating point number may comprise a mantissa and an exponent. The telemetry device may determine a first number based on a product of the exponent and a constant, wherein the constant may be proportional to a logarithm of the number two. The telemetry device may determine a second number using one or more bits of the mantissa as an index into a predetermined lookup table. Values of the lookup table may be proportional to logarithms of candidate mantissa values. The telemetry device may determine the compressed number based on rounding of a sum. The sum may include the first and second numbers. The rounding may be based on a predetermined step size.

A method of multiplying together a series of factors includes representing a multiplication operation in terms of a summation of a series of natural logarithmic functions that undergo exponentiation to represent the multiplication of the factors. An optical signal is generated for each of the factors to be multiplied. Each optical signal has a power or energy level that represents its respective factor. Each of the optical signals is applied to a respective material that undergoes a two-photon absorption process to implement a natural logarithm function. Each optical output signal output by the materials is directed to an optical combiner to obtain a summed optical signal. The summed optical signal is directed to a saturable absorber to implement an exponential function. The power or energy of the resulting optical output signal from the saturable absorber represents the product of the factors to be multiplied.

Systems and methods for end-to-end encryption of a web browsing process are described herein. A web query is encrypted at a client using a homomorphic encryption scheme. The encrypted query is sent to a server where the encrypted query is evaluated over web content to generate an encrypted response without decrypting the encrypted query and without decrypting the response. The encrypted response is sent to the client where it is decrypted to obtain the results of the query without revealing the query or results to the owner of the web content, an observer, or an attacker.

A curve function device and an operation method thereof are provided. The curve function device includes a lookup table, a weight calculation circuit, and a linear function circuit. According to first partial bits of an input value, a bias value of a current segment and a bias value of a next segment can be extracted from the lookup table. The weight calculation circuit can calculate a weight value of the current segment according to the bias value of the current segment and the bias value of the next segment. The linear function circuit can calculate a linear function value by using the bias value of the current segment, the weight value of the current segment, and second partial bits of the input value. This linear function value can be used as an approximate value of the curve function.

A processing unit to support inference acceleration for machine learning (ML) comprises an inline post processing unit configured to accept and maintain one or more lookup tables for performing each of one or more non-linear mathematical operations. The inline post processing unit is further configured to accept data from a set of registers maintaining output from a processing block instead of streaming the data from an on-chip memory (OCM), perform the one or more non-linear mathematical operations on elements of the data from the processing block via their corresponding lookup tables, and stream post processing result of the one or more non-linear mathematical operations back to the OCM after the one or more non-linear mathematical operations are complete.

A processing unit to support inference acceleration for machine learning (ML) comprises an inline post processing unit configured to accept and maintain one or more lookup tables for performing each of one or more non-linear mathematical operations. The inline post processing unit is further configured to accept data from a set of registers maintaining output from a processing block instead of streaming the data from an on-chip memory (OCM), perform the one or more non-linear mathematical operations on elements of the data from the processing block via their corresponding lookup tables, and stream post processing result of the one or more non-linear mathematical operations back to the OCM after the one or more non-linear mathematical operations are complete.