Intel Corporation

Menachem Adelman

Robert Valentine

Mark Jay Charney

Zeev Sperber

Alexander F Heinecke

Amit Gradstein

Simon Rubanovich

Raanan Sade

Elmoustapha Ould-Ahmed-Vall

Bret L Toll

Jesus Corbal

Dan Baum

Barukh Ziv

Rinat Rappoport

Yuri Gebil

Christopher J Hughes

Stanislav Shwartsman

Igor Yanover

Evangelos Georganas

Milind Baburao Girkar

Daniel Towner

Cristina S Anderson

Dhiraj D Kalamkar

Eyal Hadas

Rajesh Poornachandran

Ravishankar Iyer

Sara S Baghsorkhi

Naveen K Mellempudi

Nilesh K Jain

Binh Q Pham

Sagi Meller

Nikita A Shustrov

Guy Boudoukh

Uri Sherman

Dana Rip

Yash Akhauri

Shahar Mizrahi

Binh Pham

Methods, apparatus, systems, and articles of manufacture to perform weight and activation compression and decompression are disclosed. An example apparatus includes memory, instructions in the apparatus, and processor circuitry to execute the instructions to execute a compression operation to obtain compressed data corresponding to weights in a weight matrix, and determine meta-data associated with the weight matrix, a first portion of the meta-data indicative of whether the weight matrix is compressed, a second portion of the meta-data indicative of a cache size of the compressed data, and a third portion of the meta-data indicative of the compression operation executed to obtain the compressed data.

Methods and apparatus to perform weight and activation compression and decompression

Systems, methods, and apparatuses relating sparsity based FMA. In some examples, an instance of a single FMA instruction has one or more fields for an opcode, one or more fields to identify a source/destination matrix operand, one or more fields to identify a first plurality of source matrix operands, one or more fields to identify a second plurality of matrix operands, wherein the opcode is to indicate that execution circuitry is to select a proper subset of FP8 data elements from the first plurality of source matrix operands based on sparsity controls from a first matrix operand of the second plurality of matrix operands and perform a FMA.

Instructions for structured-sparse tile matrix FMA

Embodiments for a matrix transpose and multiply operation are disclosed. In an embodiment, a processor includes a decoder and execution circuitry. The decoder is to decode an instruction having a format including an opcode field to specify an opcode, a first destination operand field to specify a destination matrix location, a first source operand field to specify a first source matrix location, and a second source operand field to specify a second source matrix location. The execution circuitry is to, in response to the decoded instruction, transpose the first source matrix to generate a transposed first source matrix, perform a matrix multiplication using the transposed first source matrix and the second source matrix to generate a result, and store the result in a destination matrix location.

Matrix transpose and multiply

Techniques for scale and reduction of BF16 data elements are described. An exemplary instruction includes fields for an having fields for an opcode, an identification of a location of a first packed data source operand, an identification of a location of a second packed data source operand, and an identification of a packed data destination operand, wherein the opcode is to indicate that execution circuitry is to perform, for each data element position of the packed data source operands, a floating point scale operation of a BF16 data element of the first packed data source by multiplying the data element by a power of 2 value, wherein a value of the exponent of the power of 2 value is a floor value of a BF16 data element of the second packed data source, and store a result of the floating point scale operation into a corresponding data element position of the packed data destination operand.

BFLOAT16 scale and/or reduce instructions

Techniques for matrix multiplication are described. In some examples, decode circuitry is to decode a single instruction having fields for an opcode, an indication of a location of a first source operand, an indication of a location of a second source operand, and an indication of a location of a destination operand, wherein the opcode is to indicate that execution circuitry is to at least convert data elements of the first and second source operands from a first floating point representation to a second floating point representation, perform matrix multiplication with the converted data elements, and accumulate results of the matrix multiplication in the destination operand in the first floating point representation; and the execution circuitry is to execute to the decoded instruction as specified by the opcode.

Apparatuses, methods, and systems for instructions for matrix multiplication instructions

Embodiments detailed herein relate to matrix operations. For example, embodiments of instruction support for matrix (tile) dot product operations are detailed. Exemplary instructions including computing a dot product of signed words and accumulating in a double word with saturation; computing a dot product of bytes and accumulating in to a dword with saturation, where the input bytes can be signed or unsigned and the dword accumulation has output saturation; etc.

Systems, methods, and apparatuses for dot production operations

Disclosed embodiments relate to computing dot products of nibbles in tile operands. In one example, a processor includes decode circuitry to decode a tile dot product instruction having fields for an opcode, a destination identifier to identify a M by N destination matrix, a first source identifier to identify a M by K first source matrix, and a second source identifier to identify a K by N second source matrix, each of the matrices containing doubleword elements, and execution circuitry to execute the decoded instruction to perform a flow K times for each element (m, n) of the specified destination matrix to generate eight products by multiplying each nibble of a doubleword element (M,K) of the specified first source matrix by a corresponding nibble of a doubleword element (K,N) of the specified second source matrix, and to accumulate and saturate the eight products with previous contents of the doubleword element.

Systems and methods for performing 16-bit floating-point matrix dot product instructions

Embodiments detailed herein relate to systems and methods to store a tile register pair to memory. In one example, a processor includes: decode circuitry to decode a store matrix pair instruction having fields for an opcode and source and destination identifiers to identify source and destination matrices, respectively, each matrix having a PAIR parameter equal to TRUE; and execution circuitry to execute the decoded store matrix pair instruction to store every element of left and right tiles of the identified source matrix to corresponding element positions of left and right tiles of the identified destination matrix, respectively, wherein the executing stores a chunk of C elements of one row of the identified source matrix at a time.

Systems and methods to store a tile register pair to memory

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.

Systems, methods, and apparatus for tile configuration

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 store configuration information about usage of storage for two-dimensional data structures at the memory address.

Systems, methods, and apparatuses for matrix operations

Systems, methods, and apparatuses relating to instructions to convert 16-bit floating-point formats are described. In one embodiment, a processor includes fetch circuitry to fetch a single instruction having fields to specify an opcode and locations of a source vector comprising N plurality of 16-bit half-precision floating-point elements, and a destination vector to store N plurality of 16-bit bfloat floating-point elements, the opcode to indicate execution circuitry is to convert each of the elements of the source vector from 16-bit half-precision floating-point format to 16-bit bfloat floating-point format and store each converted element into a corresponding location of the destination vector, decode circuitry to decode the fetched single instruction into a decoded single instruction, and the execution circuitry to respond to the decoded single instruction as specified by the opcode.

Apparatuses, methods, and systems for instructions to convert 16-bit floating-point formats

Embodiments detailed herein relate to systems and methods to load a tile register pair. In one example, a processor includes: decode circuitry to decode a load matrix pair instruction having fields for an opcode and source and destination identifiers to identify source and destination matrices, respectively, each matrix having a PAIR parameter equal to TRUE; and execution circuitry to execute the decoded load matrix pair instruction to load every element of left and right tiles of the identified destination matrix from corresponding element positions of left and right tiles of the identified source matrix, respectively, wherein the executing operates on one row of the identified destination matrix at a time, starting with the first row.

Systems and methods to load a tile register pair

Techniques for performing BF16 FMA in response to an instruction are described. In some examples, an instruction has fields for an opcode, an identification of location of a packed data source/destination operand (a first source), an identification of a location of a second packed data source operand, an identification of a location of a third packed data source operand, and an identification of location of a packed data source/destination operand, wherein the opcode is to indicate operand ordering and that execution circuitry is to, per data element position, perform a BF16 value fused multiply-accumulate operation using the first, second, and third source operands and store a result in a corresponding data element position of the source/destination operand.

BFLOAT16 fused multiply instructions

An apparatus and method for complex matrix conjugation and multiplication. For example, one embodiment of a processor comprises: a decoder to decode a complex matrix conjugation and multiplication instruction including a first source operand to identify a first complex source matrix comprising a first plurality of complex values, a second source operand to identify a second complex source matrix comprising a second plurality of complex values, and a first destination operand to identify a result matrix; execution circuitry to execute the complex matrix conjugation and multiplication instruction, the execution circuitry comprising: matrix conjugation hardware logic to determine a plurality of complex conjugate values corresponding to the first plurality of complex values; transpose hardware logic to transpose the plurality of complex conjugate values to generate a conjugate transpose matrix comprising the complex conjugate values; parallel multiplication circuitry to: multiply real values from the plurality of complex conjugate values of the conjugate transpose matrix with corresponding imaginary values from the second plurality of complex values to generate a first plurality of imaginary products, and multiply imaginary values from the plurality of complex conjugate values of the conjugate transpose matrix with corresponding real values from the second plurality of complex values to generate a second plurality of imaginary products; and addition/subtraction circuitry to add each imaginary product in the first plurality of imaginary products to a corresponding imaginary product in the second plurality of imaginary products to produce a corresponding imaginary component in the result matrix.

Apparatus and method for conjugate transpose and multiply

Embodiments detailed herein relate to matrix operations. In particular, the loading of a matrix (tile) from memory. For example, support for a loading instruction is described in the form of decode circuitry to decode an instruction having fields for an opcode, a destination matrix operand identifier, and source memory information, and execution circuitry to execute the decoded instruction to load groups of strided data elements from memory into configured rows of the identified destination matrix operand to memory.

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Haifa, Israel

Menachem Adelman