Abstract: Systems, methods, and apparatuses relating to performing hashing operations on packed data elements are described.

Abstract: In one embodiment, a processor includes a fetch logic to fetch instructions, a decode logic to decode the fetched instructions, and an execution logic to execute at least some of the instructions. The decode logic may determine whether a flag portion of a first instruction to be folded is to be performed, and if not, accumulate a first immediate value of the first instruction with a folded immediate value obtained from an entry of an immediate buffer. Other embodiments are described and claimed.

Abstract: Disclosed embodiments relate to performing floating-point addition with selected rounding. In one example, a processor includes circuitry to decode and execute an instruction specifying locations of first and second floating-point (FP) sources, and an opcode indicating the processor is to: bring the FP sources into alignment by shifting a mantissa of the smaller source FP operand to the right by a difference between their exponents, generating rounding controls based on any bits that escape; simultaneously generate a sum of the FP sources and of the FP sources plus one, the sums having a fuzzy-Jbit format having an additional Jbit into which a carry-out, if any, select one of the sums based on the rounding controls, and generate a result comprising a mantissa-wide number of most-significant bits of the selected sum, starting with the most significant non-zero Jbit.

Abstract: Integrated circuits to compute a result of summing m values, rotating the sum by k bits, and adding a summation of n values Bi to Bn to the rotated sum. An embodiment includes: a first carry save adder to add up the m values to generate a first carry and a first sum; rotator circuitry to rotate both the first carry and the first sum by k bits to generate a second carry and a second sum; a second carry save adder to add up the second carry, the second sum, and the summation of values Bi to Bn to generate a third carry and a third sum; two parallel adders to generate a first intermediate result and a second intermediary result based on the third carry and the third sum; and a multiplexer to generate the result utilizing various portions of the first and second intermediate results.

Abstract: In some embodiments, packed data elements of first and second packed data source operands are of a first, different size than a second size of packed data elements of a third packed data operand. Execution circuitry executes decoded single instruction to perform, for each packed data element position of a destination operand, a multiplication of a M N-sized packed data elements from the first and second packed data sources that correspond to a packed data element position of the third packed data source, add of results from these multiplications to a full-sized packed data element of a packed data element position of the third packed data source, and storage of the addition result in a packed data element position destination corresponding to the packed data element position of the third packed data source, wherein M is equal to the full-sized packed data element divided by N.

Abstract: In one embodiment, a processor includes a fetch logic to fetch instructions, a decode logic to decode the instructions, an execution logic to execute at least some of the instructions, and a reconstruction logic. The decode logic may identify a first instruction having a first immediate value, accumulate the first immediate value with a folded immediate value associated with a first operand of the first instruction, and prevent the first instruction from provision to the execution logic, such that the first instruction is not to be executed within the execution logic. The reconstruction logic may reconstruct one or more flags associated with a result of the first instruction. Other embodiments are described and claimed.

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: Disclosed embodiments relate to performing floating-point (FP) arithmetic. In one example, a processor is to decode an instruction specifying locations of first, second, and third floating-point (FP) operands and an opcode calling for accumulating a FP product of the first and second FP operands with the third FP operand, and execution circuitry to, in a first cycle, generate the FP product having a Fuzzy-Jbit format comprising a sign bit, a 9-bit exponent, and a 25-bit mantissa having two possible positions for a JBit and, in a second cycle, to accumulate the FP product with the third FP operand, while concurrently, based on Jbit positions of the FP product and the third FP operand, determining an exponent adjustment and a mantissa shift control of a result of the accumulation, wherein performing the exponent adjustment concurrently enhances an ability to perform the accumulation in one cycle.

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 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 systems and methods for performing instructions to convert to 16-bit floating-point format. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode and locations of a first source vector comprising N single-precision elements, and a destination vector comprising at least N 16-bit floating-point elements, the opcode to indicate execution circuitry is to convert each of the elements of the specified source vector to 16-bit floating-point, the conversion to include truncation and rounding, as necessary, and to store each converted element into a corresponding location of the specified destination vector, decode circuitry to decode the fetched instruction, and execution circuitry to respond to the decoded instruction as specified by the opcode.

Abstract: Disclosed embodiments relate to systems and methods for performing instructions to convert to 16-bit floating-point format. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode and locations of a first source vector comprising N single-precision elements, and a destination vector comprising at least N 16-bit floating-point elements, the opcode to indicate execution circuitry is to convert each of the elements of the specified source vector to 16-bit floating-point, the conversion to include truncation and rounding, as necessary, and to store each converted element into a corresponding location of the specified destination vector, decode circuitry to decode the fetched instruction, and execution circuitry to respond to the decoded instruction as specified by the opcode.

Abstract: Disclosed embodiments relate to systems and methods for performing 16-bit floating-point vector dot product instructions. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode and locations of first source, second source, and destination vectors, the opcode to indicate execution circuitry is to multiply N pairs of 16-bit floating-point formatted elements of the specified first and second sources, and accumulate the resulting products with previous contents of a corresponding single-precision element of the specified destination, decode circuitry to decode the fetched instruction, and execution circuitry to respond to the decoded instruction as specified by the opcode.

Abstract: In one embodiment, a processor includes a fetch logic to fetch instructions, a decode logic to decode the fetched instructions, and an execution logic to execute at least some of the instructions. The decode logic may determine whether a flag portion of a first instruction to be folded is to be performed, and if not, accumulate a first immediate value of the first instruction with a folded immediate value obtained from an entry of an immediate buffer. Other embodiments are described and claimed.

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: Disclosed embodiments relate to systems and methods for performing 16-bit floating-point vector dot product instructions. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode and locations of first source, second source, and destination vectors, the opcode to indicate execution circuitry is to multiply N pairs of 16-bit floating-point formatted elements of the specified first and second sources, and accumulate the resulting products with previous contents of a corresponding single-precision element of the specified destination, decode circuitry to decode the fetched instruction, and execution circuitry to respond to the decoded instruction as specified by the opcode.

Abstract: Disclosed embodiments relate to performing floating-point (FP) arithmetic. In one example, a processor is to decode an instruction specifying locations of first, second, and third floating-point (FP) operands and an opcode calling for accumulating a FP product of the first and second FP operands with the third FP operand, and execution circuitry to, in a first cycle, generate the FP product having a Fuzzy-Jbit format comprising a sign bit, a 9-bit exponent, and a 25-bit mantissa having two possible positions for a JBit and, in a second cycle, to accumulate the FP product with the third FP operand, while concurrently, based on Jbit positions of the FP product and the third FP operand, determining an exponent adjustment and a mantissa shift control of a result of the accumulation, wherein performing the exponent adjustment concurrently enhances an ability to perform the accumulation in one cycle.

Abstract: Disclosed embodiments relate to systems and methods for performing instructions to convert to 16-bit floating-point format. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode and locations of a first source vector comprising N single-precision elements, and a destination vector comprising at least N 16-bit floating-point elements, the opcode to indicate execution circuitry is to convert each of the elements of the specified source vector to 16-bit floating-point, the conversion to include truncation and rounding, as necessary, and to store each converted element into a corresponding location of the specified destination vector, decode circuitry to decode the fetched instruction, and execution circuitry to respond to the decoded instruction as specified by the opcode.

Abstract: Disclosed embodiments relate to systems and methods for performing instructions to convert to 16-bit floating-point format. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode and locations of a first source vector comprising N single-precision elements, and a destination vector comprising at least N 16-bit floating-point elements, the opcode to indicate execution circuitry is to convert each of the elements of the specified source vector to 16-bit floating-point, the conversion to include truncation and rounding, as necessary, and to store each converted element into a corresponding location of the specified destination vector, decode circuitry to decode the fetched instruction, and execution circuitry to respond to the decoded instruction as specified by the opcode.

Abstract: Systems, methods, and apparatuses relating to a matrix operations accelerator are described. In one embodiment, a processor includes a matrix operations accelerator circuit that includes a two-dimensional grid of fused multiply accumulate circuits; a first plurality of registers that represents an input two-dimensional matrix coupled to the matrix operations accelerator circuit; a decoder, of a core coupled to the matrix operations accelerator circuit, to decode an instruction into a decoded instruction; and an execution circuit of the core to execute the decoded instruction to cause the two-dimensional grid of fused multiply accumulate circuits to form a transpose of the input two-dimensional matrix when the matrix operations accelerator circuit is in a transpose mode.