Abstract:
Systems, methods, and apparatuses relating to instructions to multiply floating-point values of about zero are described. In one embodiment, a hardware processor includes a decoder to decode a single instruction into a decoded single instruction, the single instruction having a first field that identifies a first floating-point number, a second field that identifies a second floating-point number, and a third field that indicates an about zero threshold; and an execution circuit to execute the decoded single instruction to: cause a first comparison of an exponent of the first floating-point number to the about zero threshold, cause a second comparison of an exponent of the second floating-point number to the about zero threshold, provide as a resultant of the single instruction a value of zero when the first comparison indicates the exponent of the first floating-point number does not exceed the about zero threshold, provide as the resultant of the single instruction the value of zero when the second comparison indicates the exponent of the second floating-point number does not exceed the about zero threshold, and provide as the resultant of the single instruction a product of a multiplication of the first floating-point number and the second floating-point number when the first comparison indicates the exponent of the first floating-point number exceeds the about zero threshold and the second comparison indicates the exponent of the second floating-point number exceeds the about zero threshold.
Abstract:
One embodiment provides for a compute apparatus to perform machine learning operations, the compute apparatus comprising instruction decode logic to decode a single instruction including multiple operands into a single decoded instruction, the multiple operands having differing precisions and a general-purpose graphics compute unit including a first logic unit and a second logic unit, the general-purpose graphics compute unit to execute the single decoded instruction, wherein to execute the single decoded instruction includes to perform a first instruction operation on a first set of operands of the multiple operands at a first precision and a simultaneously perform second instruction operation on a second set of operands of the multiple operands at a second precision.
Abstract:
One embodiment provides for a computing device within an autonomous vehicle, the compute device comprising a wireless network device to enable a wireless data connection with an autonomous vehicle network, a set of multiple processors including a general-purpose processor and a general-purpose graphics processor, the set of multiple processors to execute a compute manager to manage execution of compute workloads associated with the autonomous vehicle, the compute workload associated with autonomous operations of the autonomous vehicle, and offload logic configured to execute on the set of multiple processors, the offload logic to determine to offload one or more of the compute workloads to one or more autonomous vehicles within range of the wireless network device.
Abstract:
An apparatus is described that includes instruction execution circuitry to execute first, second, third, and fourth instructions, the first and second instructions select a first group of input vector elements from one of multiple first non-overlapping sections of respective first and second input vectors. Each of the multiple first non-overlapping sections have a same bit width as the first group. Both the third and fourth instructions select a second group of input vector elements from one of multiple second non-overlapping sections of respective third and fourth input vectors. The second group has a second bit width that is larger than the first bit width. Each of multiple second non-overlapping sections have a same bit width as the second group. The apparatus includes masking layer circuitry to mask the first and second groups at a first granularity and second granularity.
Abstract:
In an embodiment, the present invention is directed to a processor including a decode logic to receive a multi-dimensional loop counter update instruction and to decode the multi-dimensional loop counter update instruction into at least one decoded instruction, and an execution logic to execute the at least one decoded instruction to update at least one loop counter value of a first operand associated with the multi-dimensional loop counter update instruction by a first amount. Methods to collapse loops using such instructions are also disclosed. Other embodiments are described and claimed.
Abstract:
An apparatus is described having functional unit logic circuitry. The functional unit logic circuitry has a first register to store a first input vector operand having an element for each dimension of a multi-dimensional data structure. Each element of the first vector operand specifying the size of its respective dimension. The functional unit has a second register to store a second input vector operand specifying coordinates of a particular segment of the multi-dimensional structure. The functional unit also has logic circuitry to calculate an address offset for the particular segment relative to an address of an origin segment of the multi-dimensional structure.
Abstract:
An apparatus and method for performing a vector bit reversal and crossing. For example, one embodiment of a processor comprises: a first source vector register to store a first plurality of source bit groups, wherein a size for the bit groups is to be specified in an immediate of an instruction; a second source vector to store a second plurality of source bit groups; vector bit reversal and crossing logic to determine a bit group size from the immediate and to responsively reverse positions of contiguous bit groups within the first source vector register to generate a set of reversed bit groups, wherein the vector bit reversal and crossing logic is to additionally interleave the set of reversed bit groups with the second plurality of bit groups; and a destination vector register to store the reversed bit groups interleaved with the first plurality of bit groups.
Abstract:
An apparatus and method for performing vector index loads and stores. For example, one embodiment of a processor comprises: a vector index register to store a plurality of index values; a mask register to store a plurality of mask bits; a vector register to store a plurality of vector data elements loaded from memory; and vector index load logic to identify an index stored in the vector index register to be used for a load operation using an immediate value and to responsively combine the index with a base memory address to determine a memory address for the load operation, the vector index load logic to load vector data elements from the memory address to the vector register in accordance with the plurality of mask bits.
Abstract:
An apparatus and method for performing a mask expand. For example, one embodiment of a processor comprises: a source mask register to store a plurality of mask values; mask expand logic to identify a first mask bit in the source mask register to be expanded using an index value and to determine a number of bit positions within a destination mask register into which the first mask bit is to be expanded using a second value, the mask expand logic to responsively copy the first mask bit to each of the determined bit positions within the destination mask register.
Abstract:
Described herein is a general-purpose graphics processing unit including a multiprocessor having a single instruction, multiple thread, SIMT, architecture. The multiprocessor comprises multiple sets of compute units each having a first logic unit configured to perform floating-point operations and a second logic unit configured to perform integer operations, with a thread of the floating-point instruction being executed in parallel with a thread of the integer instruction.