Abstract: Embodiments detailed herein relate to matrix operations. In particular, embodiment of broadcasting elements are described. For example, some embodiments describe broadcasting a scalar to all configured data element positons of a destination matrix (tile). For example, some embodiments describe broadcasting a row to all configured data element positons of a destination matrix (tile). For example, some embodiments describe broadcasting a column to all configured data element positons of a destination matrix (tile).

Abstract: Embodiments detailed herein relate to matrix (tile) operations. For example, decode circuitry to decode an instruction having fields for an opcode and a memory address; and execution circuitry to execute the decoded instruction to set a tile configuration for the processor to utilize tiles in matrix operations based on a description retrieved from the memory address, wherein a tile a set of 2-dimensional registers are discussed.

Abstract: Embodiments detailed herein relate to matrix operations. In particular, matrix (tile) multiply accumulate and negated matrix (tile) multiply accumulate are discussed. For example, in some embodiments decode circuitry to decode an instruction having fields for an opcode, an identifier for a first source matrix operand, an identifier of a second source matrix operand, and an identifier for a source/destination matrix operand; and execution circuitry to execute the decoded instruction to multiply the identified first source matrix operand by the identified second source matrix operand, add a result of the multiplication to the identified source/destination matrix operand, and store a result of the addition in the identified source/destination matrix operand and zero unconfigured columns of identified source/destination matrix operand are detailed.

Abstract: Embodiments detailed herein relate to matrix operations. In particular, the loading of a matrix (tile) from memory.

Abstract: Detailed herein are embodiment systems, processors, and methods for matrix move. For example, a processor comprising decode circuitry to decode an instruction having fields for an opcode, a source matrix operand identifier, and a destination matrix operand identifier; and execution circuitry to execute the decoded instruction to move each data element of the identified source matrix operand to corresponding data element position of the identified destination matrix operand is described.

Abstract: Disclosed embodiments relate to matrix compress/decompress instructions. In one example, a processor includes fetch circuitry to fetch a compress instruction having a format with fields to specify an opcode and locations of decompressed source and compressed destination matrices, decode circuitry to decode the fetched compress instructions, and execution circuitry, responsive to the decoded compress instruction, to: generate a compressed result according to a compress algorithm by compressing the specified decompressed source matrix by either packing non-zero-valued elements together and storing the matrix position of each non-zero-valued element in a header, or using fewer bits to represent one or more elements and using the header to identify matrix elements being represented by fewer bits; and store the compressed result to the specified compressed destination matrix.

Abstract: Disclosed embodiments relate to systems and methods for performing duplicate detection instructions on two-dimensional (2D) data. In one example, a processor includes fetch circuitry to fetch an instruction, decode circuitry to decode the fetched instruction having fields to specify an opcode and locations of a source matrix comprising M×N elements and a destination, the opcode to indicate execution circuitry is to use a plurality of comparators to discover duplicates in the source matrix, and store indications of locations of discovered duplicates in the destination. The execution circuitry to execute the decoded instruction as per the opcode.

Abstract: Disclosed embodiments relate to systems and methods for performing nibble-sized operations on matrix elements. In one example, a processor includes fetch circuitry to fetch an instruction, decode circuitry to decode the fetched instruction the fetched instruction having fields to specify an opcode and locations of first source, second source, and destination matrices, the opcode to indicate the processor is to, for each pair of corresponding elements of the first and second source matrices, logically partition each element into nibble-sized partitions, perform an operation indicated by the instruction on each partition, and store execution results to a corresponding nibble-sized partition of a corresponding element of the destination matrix. The exemplary processor includes execution circuitry to execute the decoded instruction as per the opcode.

Abstract: Disclosed embodiments relate to accelerating multiplication of sparse matrices. In one example, a processor is to fetch and decode an instruction having fields to specify locations of first, second, and third matrices, and an opcode indicating the processor is to multiply and accumulate matching non-zero (NZ) elements of the first and second matrices with corresponding elements of the third matrix, and executing the decoded instruction as per the opcode to generate NZ bitmasks for the first and second matrices, broadcast up to two NZ elements at a time from each row of the first matrix and each column of the second matrix to a processing engine (PE) grid, each PE to multiply and accumulate matching NZ elements of the first and second matrices with corresponding elements of the third matrix. Each PE further to store an NZ element for use in a subsequent multiplications.

Abstract: Disclosed embodiments relate to systems and methods for performing matrix row-wise and column-wise permute instructions. In one example, a processor includes fetch circuitry to fetch an instruction, decoding, using decode circuitry, the fetched instruction having fields to specify an opcode and locations of a source matrix and a destination matrix, the opcode indicating the processor is to perform a permutation by copying, into each of a plurality of equal-sized logical partitions of the destination matrix, a selected logical partition of a same size from the source matrix, the selection being indicated by a permute control, and execution circuitry to execute the decoded instruction as per the opcode.

Abstract: An apparatus and method for processing efficient multicast operation.

Abstract: Disclosed embodiments relate to systems for performing instructions to quickly convert and use matrices (tiles) as one-dimensional vectors. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode, locations of a two-dimensional (2D) matrix and a one-dimensional (1D) vector, and a group of elements comprising one of a row, part of a row, multiple rows, a column, part of a column, multiple columns, and a rectangular sub-tile of the specified 2D matrix, and wherein the opcode is to indicate a move of the specified group between the 2D matrix and the 1D vector, decode circuitry to decode the fetched instruction; and execution circuitry, responsive to the decoded instruction, when the opcode specifies a move from 1D, to move contents of the specified 1D vector to the specified group of elements.

Abstract: An apparatus and method for processing array of structures (AoS) and structure of arrays (SoA) data. For example, one embodiment of a processor comprises: a destination tile register to store data elements in a structure of arrays (SoA) format; a first source tile register to store indices associated with the data elements; instruction fetch circuitry to fetch an array of structures (AoS) gather instruction comprising operands identifying the first source tile register and the destination tile register; a decoder to decode the AoS gather instruction; and execution circuitry to determine a plurality of system memory addresses based on the indices from the first source tile register, to read data elements from the system memory addresses in an AoS format, and to load the data elements to the destination tile register in an SoA format.

Abstract: An apparatus and method for tile-based gather and scatter operations. For example, one embodiment of a processor comprises: a destination tile register to store a 2-D arrangement of data elements; a first source tile register to store indices associated with the data elements; instruction fetch circuitry to fetch a tile gather instruction comprising operands identifying the first source tile register and the destination tile register; a decoder to decode the tile gather instruction; and execution circuitry to determine a plurality of system memory addresses based on the indices from the first source tile register and to load the data elements from the system memory addresses to the destination tile register.

Abstract: Embodiments detailed herein relate to matrix (tile) operations. For example, decode circuitry to decode an instruction having fields for an opcode and a memory address; and execution circuitry to execute the decoded instruction to set a tile configuration for the processor to utilize tiles in matrix operations based on a description retrieved from the memory address, wherein a tile a set of 2-dimensional registers are discussed.

Abstract: Disclosed embodiments relate to apparatuses, systems, and methods for performing sort indexing and/or permutation using an index. An exemplary apparatus includes decode circuitry to decode an instruction, the instruction to include a first field to identify a location of a source vector, a second field to identify a location of a destination vector, and an opcode to indicate to execution circuitry to execute the decoded instruction to sort values of the source vector and store a result of the sort in the destination vector by generating, per each element of the source vector, an index value using one or more comparisons of the element itself and to other data elements of the source vector, and permuting the values of the elements of the source vector based upon the index values for the elements and execution circuitry to execute the decoded instruction as indicated by the opcode.

Abstract: An accelerator for increasing the processing speed of a processor. The accelerator operates in two distinct modes. In a first mode for dense layer processing, row data sets and column data sets are sent to a multiplier for multiplication. In a second mode for sparse layer processing compressed row data sets are received by a row multiplexer and compressed column data sets are received by a column multiplexer. Each multiplexer is configured to compare the indexes of data sets with one another to determine matching indexes. When indexes match, the matching data sets are selected and sent to the multiplier for multiplication. When indexes do not match, data sets are stored in memory devices for subsequent cycles.

Abstract: Embodiments detailed herein relate to matrix operations. In particular, support for matrix (tile) addition, subtraction, and multiplication is described. For example, circuitry to support instructions for element-by-element matrix (tile) addition, subtraction, and multiplication are detailed. In some embodiments, for matrix (tile) addition, decode circuitry is to decode an instruction having fields for an opcode, a first source matrix operand identifier, a second source matrix operand identifier, and a destination matrix operand identifier; and execution circuitry is to execute the decoded instruction to, for each data element position of the identified first source matrix operand: add a first data value at that data element position to a second data value at a corresponding data element position of the identified second source matrix operand, and store a result of the addition into a corresponding data element position of the identified destination matrix operand.

Abstract: Embodiments detailed herein relate to matrix operations. In particular, support for a matrix transpose instruction is detailed. In some embodiments, decode circuitry to decode an instruction having fields for an opcode, a source matrix operand identifier, and a destination matrix operand identifier; and execution circuitry to execute the decoded instruction to transpose each row of elements of the identified source matrix operand into a corresponding column of the identified destination matrix operand are detailed.

Abstract: Embodiments detailed herein relate to matrix operations. In particular, tile diagonal support is described. For example, a processor is detailed having decode circuitry to decode an instruction having fields for an opcode, a source operand identifier, and a destination matrix operand identifier; and execution circuitry to execute the decoded instruction to write the identified source operand to each element along a main diagonal of the identified destination matrix operand.