Abstract: Described herein is a graphics processor including a processing resource including a multiplier configured to multiply input associated with the instruction at one of a first plurality of bit widths, an adder configured to add a product output from the multiplier with an accumulator value at one of a second plurality of bit widths, and circuitry to select a first bit width of the first plurality of bit widths for the multiplier and a second bit width of the second plurality of bit widths for the adder.

Abstract: An apparatus and method for performing a transform on complex data.

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: Embodiments detailed herein relate to matrix operations. In particular, performing a matrix operation of zeroing a matrix in response to a single instruction. For example, a processor detailed which includes decode circuitry to decode an instruction having fields for an opcode and a source/destination matrix operand identifier; and execution circuitry to execute the decoded instruction to zero each data element of the identified source/destination matrix.

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

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

Abstract: Disclosed embodiments relate to systems and methods for implementing chained tile operations. In one example, a processor includes fetch circuitry to fetch one or more instructions until a plurality of instructions has been fetched, each instruction to specify source and destination tile operands, decode circuitry to decode the fetched instructions, and execution circuitry, responsive to the decoded instructions, to: identify first and second decoded instructions belonging to a chain of instructions, dynamically select and configure a SIMD path comprising first and second processing engines (PE) to execute the first and second decoded instructions, and set aside the specified destination of the first decoded instruction, and instead route a result of the first decoded instruction from the first PE to be used by the second PE to perform the second decoded instruction.

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: Disclosed embodiments relate to systems and methods for performing instructions to transpose rectangular tiles. In one example, a processor includes fetch circuitry to fetch an instruction having fields to specify an opcode and locations of first destination, second destination, first source, and second source matrices, the specified opcode to cause the processor to process each of the specified source and destination matrices as a rectangular matrix, decode circuitry to decode the fetched rectangular matrix transpose instruction, and execution circuitry to respond to the decoded rectangular matrix transpose instruction by transposing each row of elements of the specified first source matrix into a corresponding column of the specified first destination matrix and transposing each row of elements of the specified second source matrix into a corresponding column of the specified second destination matrix.

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: Embodiments of an invention a processor architecture are disclosed. In an embodiment, a processor includes a decoder, an execution unit, a coherent cache, and an interconnect. The decoder is to decode an instruction to zero a cache line. The execution unit is to issue a write command to initiate a cache line sized write of zeros. The coherent cache is to receive the write command, to determine whether there is a hit in the coherent cache and whether a cache coherency protocol state of the hit cache line is a modified state or an exclusive state, to configure a cache line to indicate all zeros, and to issue the write command toward the interconnect. The interconnect is to, responsive to receipt of the write command, issue a snoop to each of a plurality of other coherent caches for which it must be determined if there is a hit.

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 a signed fixed-sized result by rounding the most significant fixed-sized portion of the double-sized product to fit into the identified destination.

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 matrix operations. In particular, performing a matrix operation of zeroing a matrix in response to a single instruction. For example, a processor detailed which includes decode circuitry to decode an instruction having fields for an opcode and a source/destination matrix operand identifier; and execution circuitry to execute the decoded instruction to zero each data element of the identified source/destination matrix.

Abstract: An apparatus is described having instruction execution logic circuitry to execute first, second, third and fourth instruction. Both the first instruction and the second instruction insert a first group of input vector elements to one of multiple first non overlapping sections of respective first and second resultant vectors. The first group has a first bit width. Each of the multiple first non overlapping sections have a same bit width as the first group. Both the third instruction and the fourth instruction insert a second group of input vector elements to one of multiple second non overlapping sections of respective third and fourth resultant vectors. The second group has a second bit width that is larger than said first bit width. Each of the multiple second non overlapping sections have a same bit width as the second group.

Abstract: An apparatus and method for multiplying packed real and imaginary components of complex numbers are described. A processor embodiment includes: a decoder to decode a first instruction to generate a decoded instruction; a first source register to store a first plurality of packed real and imaginary data elements; a second source register to store a second plurality of packed real and imaginary data elements; and execution circuitry to execute the decoded instruction.

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: An apparatus is described having instruction execution logic circuitry to execute first, second, third and fourth instruction. Both the first instruction and the second instruction insert a first group of input vector elements to one of multiple first non overlapping sections of respective first and second resultant vectors. The first group has a first bit width. Each of the multiple first non overlapping sections have a same bit width as the first group. Both the third instruction and the fourth instruction insert a second group of input vector elements to one of multiple second non overlapping sections of respective third and fourth resultant vectors. The second group has a second bit width that is larger than said first bit width. Each of the multiple second non overlapping sections have a same bit width as the second group.

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: A processing cluster of a processing cluster array comprises a plurality of registers to store input values of vector input operands, the input values of at least some of the vector input operands having different bit lengths than those of other input values of other vector input operands, and a compute unit to execute a dot-product instruction with the vector input operands to perform a number of parallel multiply operations and an accumulate operation per 32-bit lane based on a bit length of the smallest-sized input value of a first vector input operand relative to the 32-bit lane.