Abstract: A data protection system is provided to detect data and execute security actions on the detected data using multiple tiers of parallel processing and incremental processing. For example, the data protection system can employ parallel job-submission and parallel-job execution to cataloging, scanning, searching, and other processes. Only source data that has not already been processed or has modified may be loaded to a cataloging data queue and a scanning data queue to reduce processing time. Scan results can include different data groups and can be used to search for specific data sets.

Abstract: The present disclosure relates to a processor that includes one or more processing elements associated with one or more instruction set architectures. The processor is configured to receive a request from an application executed by a first processing element of the one or more processing elements to enable a feature associated with an instruction set architecture. Additionally, the processor is configured to enable the application to utilize the feature without a system call occurring when the feature is associated with an instruction set architecture associated with the first processing element.

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: 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 at least a form of decode circuitry to decode an instruction having fields for an opcode, a source matrix operand identifier, and destination memory information, and execution circuitry to execute the decoded instruction to store each data element of configured rows of the identified source matrix operand to memory based on the destination memory information.

Abstract: 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.

Abstract: 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.

Abstract: An apparatus is described that includes an execution unit to execute a first instruction and a second instruction. The execution unit includes input register space to store a first data structure to be replicated when executing the first instruction and to store a second data structure to be replicated when executing the second instruction. The first and second data structures are both packed data structures. Data values of the first packed data structure are twice as large as data values of the second packed data structure. The execution unit also includes replication logic circuitry to replicate the first data structure when executing the first instruction to create a first replication data structure, and, to replicate the second data structure when executing the second data instruction to create a second replication data structure.

Abstract: 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.

Abstract: Disclosed embodiments relate to executing a vector multiplication instruction. In one example, a processor includes fetch circuitry to fetch the vector multiplication instruction having fields for an opcode, first and second source identifiers, and a destination identifier, decode circuitry to decode the fetched instruction, execution circuitry to, on each of a plurality of corresponding pairs of fixed-sized elements of the identified first and second sources, execute the decoded instruction to generate a double-sized product of each pair of fixed-sized elements, the double-sized product being represented by at least twice a number of bits of the fixed size, and generate an unsigned fixed-sized result by rounding the most significant fixed-sized portion of the double-sized product to fit into the identified destination.

Abstract: A processor of an aspect includes a decode unit to decode a matrix multiplication instruction. The matrix multiplication instruction is to indicate a first memory location of a first source matrix, is to indicate a second memory location of a second source matrix, and is to indicate a third memory location where a result matrix is to be stored. The processor also includes an execution unit coupled with the decode unit. The execution unit, in response to the matrix multiplication instruction, is to multiply a portion of the first and second source matrices prior to an interruption, and store a completion progress indicator in response to the interruption. The completion progress indicator to indicate an amount of progress in multiplying the first and second source matrices, and storing corresponding result data to the third memory location, that is to have been completed prior to the interruption.

Abstract: Embodiments of systems, methods, and apparatuses for heterogeneous computing are described. In some embodiments, a hardware heterogeneous scheduler dispatches instructions for execution on one or more plurality of heterogeneous processing elements, the instructions corresponding to a code fragment to be processed by the one or more of the plurality of heterogeneous processing elements, wherein the instructions are native instructions to at least one of the one or more of the plurality of heterogeneous processing elements.

Abstract: Techniques for data type conversion using an instruction are described. An exemplary instruction includes fields for an opcode, an identification of source operands, and an identification of destination operand, wherein the opcode is to indicate execution circuitry and/or memory access circuitry is to convert 32-bit floating point values from the identified source operands into 16-bit floating point values and store 16-bit floating point values in data element positions of the identified destination operand.

Abstract: Techniques for data type conversion via instruction are described. An exemplary instruction is to include fields for an opcode, an identification of a source operand, and an identification of destination operand, wherein the opcode is to indicate instruction processing circuitry is to convert odd 16-bit floating point values from the identified source operand into 32-bit floating point values and store the 32-bit floating point values in data element positions of the identified destination operand.

Abstract: Techniques for data type conversion are described. An example uses an instruction that is to include fields for an opcode, an identification of source operand location, and an identification of destination operand location, wherein the opcode is to indicate instruction processing circuitry is to convert a 16-bit floating-point value from the identified source operand location into a 32-bit floating point value and store that 32-bit floating point value in one or more data element positions of the identified destination operand.

Abstract: Disclosed embodiments relate to systems and methods for performing instructions to transform matrices into a row-interleaved format. In one example, a processor includes fetch and decode circuitry to fetch and decode an instruction having fields to specify an opcode and locations of source and destination matrices, wherein the opcode indicates that the processor is to transform the specified source matrix into the specified destination matrix having the row-interleaved format; and execution circuitry to respond to the decoded instruction by transforming the specified source matrix into the specified RowInt-formatted destination matrix by interleaving J elements of each J-element sub-column of the specified source matrix in either row-major or column-major order into a K-wide submatrix of the specified destination matrix, the K-wide submatrix having K columns and enough rows to hold the J elements.

Abstract: 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 quadword data elements of a matrix pair. Additionally, in some instances, non-accumulating quadword data elements of the matrix pair are set to zero.

Abstract: Embodiments of systems, apparatuses, and methods for dual complex number multiplication and addition in a processor are described. For example, execution circuitry executes a decoded instruction to multiplex data values from positions in source operands to a multiplier, the source operands including pairs complex numbers, calculate a real part of a product of each pair of complex numbers, add the real part of the product of a first pair of complex numbers to the real part of the product of a second pair of complex numbers to calculate a first real result, and add the real part of the product of a third pair of complex numbers to the real part of the product of a fourth pair of complex numbers to calculate a second real result, and store the results to corresponding positions in the destination operand.

Abstract: A method of an aspect includes receiving an instruction indicating a destination storage location. A result is stored in the destination storage location in response to the instruction. The result includes a sequence of at least four non-negative integers in numerical order with all integers in consecutive positions differing by a constant stride of at least two. In an aspect, storing the result including the sequence of the at least four integers is performed without calculating the at least four integers using a result of a preceding instruction. Other methods, apparatus, systems, and instructions are disclosed.

Abstract: Embodiments detailed herein relate to systems and methods to zero a tile register pair. In one example, a processor includes decode circuitry to decode a matrix pair zeroing instruction having fields for an opcode and an identifier to identify a destination matrix having a PAIR parameter equal to TRUE; and execution circuitry to execute the decoded matrix pair zeroing instruction to zero every element of a left matrix and a right matrix of the identified destination matrix.

Abstract: Systems, methods, and apparatuses relating to instructions to reset software thread runtime property histories in a hardware processor are described. In one embodiment, a hardware processor includes a hardware guide scheduler comprising a plurality of software thread runtime property histories; a decoder to decode a single instruction into a decoded single instruction, the single instruction having a field that identifies a model-specific register; and an execution circuit to execute the decoded single instruction to check that an enable bit of the model-specific register is set, and when the enable bit is set, to reset the plurality of software thread runtime property histories of the hardware guide scheduler.