A binary logic circuit for determining the ratio x/d where x is a variable integer input, the binary logic circuit comprising: a logarithmic tree of modulo units each configured to calculate x[a: b]mod d for respective block positions a and b in x where b>a with the numbering of block positions increasing from the most significant bit of x up to the least significant bit of x, the modulo units being arranged such that a subset of M?1 modulo units of the logarithmic tree provide x[0: m]mod d for all m?{1, M}, and, on the basis that any given modulo unit introduces a delay of 1: all of the modulo units are arranged in the logarithmic tree within a delay envelope of [log.sub.2 M]; and more than M?2.sup.u of the subset of modulo units are arranged at the maximal delay of [log.sub.2 M], where 2.sup.u is the power of 2 immediately smaller than M.

Disclosed are apparatuses, systems, and techniques to perform and facilitate fast and efficient modular computational operations, such as modular division and modular inversion, using shared platforms, including hardware accelerator engines.

Subject matter disclosed herein may relate to arithmetic units of processors, and may relate more particularly to configurable arithmetic units. Configurable arithmetic units may comprise a plurality of basic units, and may further comprise a programmable fabric to selectively connect the plurality of basic units at least in part to process one or more sets of parameters in accordance with one or more specified arithmetic operations.

An integrated photonics computing system implements a residue number system (RNS) to achieve orders of magnitude improvements in computational speed per watt over the current state-of-the-art. RNS and nanophotonics have a natural affinity where most operations can be achieved as spatial routing using electrically controlled directional coupler switches, thereby giving rise to an innovative processing-in-network (PIN) paradigm. The system provides a path for attojoule-per-bit efficient and fast electro-optic switching devices, and uses them to develop optical compute engines based on residue arithmetic leading to multi-purpose nanophotonic computing.

Methods and compression units for compressing a block of image data, the block of image data comprising a plurality of image element values, the image element values being divisible into at least a first value and a second value such that the block of image data comprises a two-dimensional block of first values, the method comprising: compressing a first data set comprising all or a portion of the two-dimensional block of first values in accordance with a first fixed-length compression algorithm to generate a first compressed block by: identifying common base information for the first data set; and identifying a fixed-length parameter for each first value in the first data set, the fixed-length parameter being zero, one or more than one bits in length; and forming a compressed block for the block of image data based on the first compressed block.

Various implementations relate to a data processing system comprising instructions embodied in a non-transitory computer readable medium, the instructions for a cryptographic operation including a masked decomposition of a polynomial a having n.sub.s arithmetic shares into a high part a.sub.1 and a low part a.sub.0 for lattice-based cryptography in a processor, the instructions, including: performing a rounded Euclidian division of the polynomial a by a base ? to compute t.sup.(?)A; extracting Boolean shares a.sub.1.sup.(?)B from n low bits of t by performing an arithmetic share to Boolean share (A2B) conversion on t.sup.(?)A and performing an AND with ??1, where ?=??.sup.?1 is a power of 2; unmasking a.sub.1 by combining Boolean shares of a.sub.1.sup.(?)B; calculating arithmetic shares a.sub.0.sup.(?)A of the low part a.sub.0; and performing a cryptographic function using a.sub.1 and a.sub.0.sup.(?)A.

Parameters defining a matrix multiply operation to be implemented in a data processing array can be received. A formulation of the matrix multiply operation is generated based on the parameters. A matrix multiply solution is determined for performing the matrix multiply operation in the data processing array. The matrix multiply solution specifies a spatial and temporal partitioning of the matrix multiply operation for implementation in the data processing array. Synthesizable program code is generated that defines an interface for the data processing array based on the matrix multiply solution. The interface is configured to partition and transfer input data to the data processing array from an external memory and convey output data from the data processing array to the external memory.

A routing circuit for an integrated circuit configured to access a set of resources that are organized according to a topology with a plurality of dimensions. The routing receives a request for a particular resource of the set of resources that includes an address that includes first and second sets of bits, the topology having a first dimension with n routing options (where n is not a power of two) and a second dimension with m routing options. The routing circuit determines first and second routing selections for the first and second dimensions by performing respective modulo-n and div-n operations on values formed from the address that include the first and second set of bits. The routing circuit then activates one or more selection signals in accordance with the first and second routing selections that are usable to cause the particular resource to be selected in response to the request.

In some applications, such as randomization and cryptography, remainder computation for a number is required. The remainder computation is also used in modulo arithmetic. The remainder computation can be simplified when the divisor belongs to a certain class of numbers. A method and apparatus are disclosed that enable low complexity implementation of remainder computation of any number when the divisor belongs to a type of numbers that can be represented as 2.sup.k+1.

Subject matter disclosed herein may relate to arithmetic units of processors, and may relate more particularly to configurable arithmetic units. Configurable arithmetic units may comprise a plurality of basic units, and may further comprise a programmable fabric to selectively connect the plurality of basic units at least in part to process one or more sets of parameters in accordance with one or more specified arithmetic operations.