Gsi Technology, Inc.

Moshe Lazer

Eli Ehrman

Eyal Amiel

Avidan Akerib

Samuel Lifsches

A method for selecting items one by one from a set of items elected from a large dataset of items includes determining whether or not a density of the set is sparse. If the density is sparse, the method includes repeatedly performing an extreme item select (EIS) method to select a next one of the elected items from the set and removing the next one from the set to create a next set. If the density is not sparse, the method includes performing a next index select (NIS) method to create a linked list of the elected items and to repeatedly select a next elected item from the set.

One by one selection of items of a set

A method for calculating a square root B having N bits of a number X having 2N bits includes iterating on bits bof square root B starting from the most significant bit until the least significant bit of square root B. For each iteration, the method includes locating a 1 at the squared location of bit bin a CHECK variable, determining the value of bit bfrom the result of a comparison of number X with a function of all previously found bits and a previous comparison outcome, shifting all previously found bits right 1 location in a CHECK variable, and adding the determined value of bit binto its squared location in the CHECK variable.

Square root calculations on an associative processing unit

An associative memory array includes a plurality of associative memory cells arranged in rows and columns where each first cell in a first row and in a first column has access to a content of a second cell in a second row in an adjacent column.

A method for an associative memory device includes storing a plurality of pairs of multi-bit operands X and Y in rows of a memory array of the associative memory device, each pair in a different column of the memory array. Cells in a column are connected by a first bit-line providing a value of activated cells and a second bit-line providing an inverse value of the activated cells. The bits of X are stored in first rows and the bits of Y are stored in second rows. The method includes reading an inverse value of a bit stored in each of the second rows using the second bit-line, writing it to third rows and concurrently, on all columns, performing multi-bit add operations between a value of X, an inverse value of Y and a carry-in bit initiated to 1, providing the difference between X and Y in each of the columns.

Concurrent multi-bit subtraction in associative memory

A method for an associative memory device includes storing a plurality of pairs of N-bit numbers A and B to be added together in columns of a memory array of the associative memory device, each pair in a column, each bit in a row of the column, and dividing each N-bit number A and B into groups containing M bits each, having group carry-out predictions for every group except a first group, the group carry-out predictions calculated for any possible group carry-in value, and, once the carry-out value for a first group is calculated, selecting the next group carry out value from the group carry-out predictions. The method also includes repeating the ripple selecting group carry-out values, until all group carry out values have been selected.

Concurrent multi-bit adder

A method and a system for selecting items one by one from a set of items in an associative memory array includes determining a density of the set, if the density is sparse, repeatedly performing an extreme item select (EIS) method to select a next one of the elected items from the set and removing the next one from the set to create a next set, and if the density is not sparse, performing a next index select (NIS) method to create a linked list of the elected items and to repeatedly select a next elected item from the set. An associative memory array includes a plurality of associative memory cells arranged in rows and columns where each first cell in a first row and in a first column has access to a content of a second cell in a second row in an adjacent column.

A method for finding an extreme value among a plurality of numbers in an associative memory includes creating a spread-out representation (SOR) for each number of the plurality of numbers, storing each SOR in a column of the associative memory array and performing a horizontal bit-wise Boolean operation on rows of the associative memory array to produce an extreme SOR (ESOR) having the extreme value. A system for finding an extreme value includes an associative memory array to store the plurality of numbers, each number storable in a column; a spread-out representation (SOR) creator to create a SOR for each number of the plurality of numbers and to store each SOR in a column of the associative memory array, and an extreme SOR (ESOR) finder to find an extreme value using a horizontal bit-wise Boolean operation on rows of the associative memory array storing bits of the SORs.

Method for min-max computation in associative memory

A method includes determining a set of k extreme values of a dataset of elements in a constant time irrespective of the size of the dataset. A method creates a set of k indicators, each indicator associated with one multi-bit binary number in a large dataset of multi-bit binary numbers. The method includes arranging the multi-bit binary numbers such that each bit n of each said multi-bit binary number is located in a different row n of an associative memory array, starting from a row storing a most significant bit (MSB), adding an indicator to the set for each multi-bit binary number having a bit with an extreme value in the row and continuing the adding until said set contains k indicators.

Finding K extreme values in constant processing time

A system includes an associative memory array and a concurrent adder. The memory array includes a plurality of sections, where each section includes cells arranged in rows and columns. The memory array stores bit j from a first multi-bit number and bit j from a second multi-bit number in a same column in section j. The concurrent adder performs, in parallel, multi-bit add operations of P pairs of multi-bit operands stored in columns of a memory array. Each pair of the P pairs is stored in a different column of the array and each add operation occurs in its associated different column.

A method for an associative memory device includes replacing a set of three multi-bit binary numbers P, Q and R, stored in the associative memory device, with two multi-bit binary numbers X and Y, also stored in the associative memory device, wherein a sum of the binary numbers P, Q and R is equal to a sum of the binary numbers X and Y. A system includes an associative memory array having rows and columns and a multi-bit multiplier. Each column of the array stores two multi-bit binary numbers to be multiplied. The multi-bit multiplier multiplies, in parallel, the two multi-bit binary numbers per column by concurrently processing all bits of partial products generated by the multiplier. The multiplier performs the processing without any carry propagation delay when adding all but the last two partial products.

System and method for long addition and long multiplication in associative memory

A system includes a non-destructive associative memory array and a predictor, a selector and a summer. The memory array includes a plurality of sections, each section includes cells arranged in rows and columns, to store bit j from a first multi-bit number and bit j from a second multi-bit number in a same column in section j. The predictor generally concurrently predicts a plurality of carry out values in each of the sections and the selector selects one of the predicted carry out values for all bits. The summer generally concurrently, for all bits, calculates a sum of the multi-bit numbers using the selected carry-out values.

Growing community of inventors

Binyamina, Israel

Moshe Lazer