Abstract: Machine instructions, referred to herein as a long Convert from Zoned instruction (CDZT) and extended Convert from Zoned instruction (CXZT), are provided that read EBCDIC or ASCII data from memory, convert it to the appropriate decimal floating point format, and write it to a target floating point register or floating point register pair. Further, machine instructions, referred to herein as a long Convert to Zoned instruction (CZDT) and extended Convert to Zoned instruction (CZXT), are provided that convert a decimal floating point (DFP) operand in a source floating point register or floating point register pair to EBCDIC or ASCII data and store it to a target memory location.

Abstract: A circuit arrangement, method, and program product for substituting a plurality of scalar instructions in an instruction stream with a functionally equivalent vector instruction for execution by a vector execution unit. Predecode logic is coupled to an instruction buffer which stores instructions in an instruction stream to be executed by the vector execution unit. The predecode logic analyzes the instructions passing through the instruction buffer to identify a plurality of scalar instructions that may be replaced by a vector instruction in the instruction stream. The predecode logic may generate the functionally equivalent vector instruction based on the plurality of scalar instructions, and the functionally equivalent vector instruction may be substituted into the instruction stream, such that the vector execution unit executes the vector instruction in lieu of the plurality of scalar instructions.

Abstract: A Vector Galois Field Multiply Sum and Accumulate instruction. Each element of a second operand of the instruction is multiplied in a Galois field with the corresponding element of the third operand to provide one or more products. The one or more products are exclusively ORed with each other and exclusively ORed with a corresponding element of a fourth operand of the instruction. The results are placed in a selected operand.

Abstract: Execution of instructions in a transactional environment is selectively controlled. A TRANSACTION BEGIN instruction initiates a transaction and includes controls that selectively indicate whether certain types of instructions are permitted to execute within the transaction. The controls include one or more of an allow access register modification control and an allow floating point operation control.

Abstract: Techniques are disclosed relating to floating-point operations in computer processors. In one embodiment, an apparatus includes a floating-point unit and circuitry configured to receive an initial value X for a floating-point operation. In this embodiment, X is between 0 and 1.0 inclusive. In this embodiment, the circuitry is configured to generate first and second floating-point values based on an exponent of X that sum to 1. In this embodiment, the floating-point unit is configured to perform an operation using the first and second floating-point values. The apparatus may reduce drift, in this embodiment, when a floating-point representation of X does not guarantee that the sum of X and (1?X) is 1. The apparatus may be configured to perform blending and/or interpolation operations using the first and second floating-point values.

Abstract: A family of computers is disclosed and claimed that supports simultaneous processes from the single core up to multi-chip Program Execution Systems (PES). The instruction processing of the instructed resources is local, dispensing with the need for large VLIW memories. The cores through the PES have maximum performance for Amdahl-compliant algorithms like matrix inversion, because the multiplications do not stall and the other circuitry keeps up. Cores with log based multiplication generators improve this performance by a factor of two for sine and cosine calculations in single precision floating point and have even greater performance for loge and ex calculations. Apparatus specifying, simulating, and/or layouts of the computer (components) are disclosed. Apparatus the computer and/or its components are disclosed.

Abstract: A new zSeries floating-point unit has a fused multiply-add dataflow capable of supporting two architectures and fused MULTIPLY and ADD and Multiply and SUBTRACT in both RRF and RXF formats for the fused functions. Both binary and hexadecimal floating-point instructions are supported for a total of 6 formats. The floating-point unit is capable of performing a multiply-add instruction for hexadecimal or binary every cycle with a latency of 5 cycles. This supports two architectures with two internal formats with their own biases. This has eliminated format conversion cycles and has optimized the width of the dataflow. The unit is optimized for both hexadecimal and binary floating-point architecture supporting a multiply-add/subtract per cycle.

Abstract: The described embodiments include a processor that executes vector instructions. While dispatching instructions at runtime, the processor encounters a predicate-generating instruction. Upon determining that a result of the predicate-generating instruction is predictable, the processor dispatches a prediction micro-operation associated with the predicate-generating instruction, wherein the prediction micro-operation generates a predicted result vector for the predicate-generating instruction. The processor then executes the prediction micro-operation to generate the predicted result vector. When executing the prediction micro-operation to generate the predicted result vector, if the predicate vector is received, for each element of the predicted result vector for which the predicate vector is active, otherwise, for each element of the predicted result vector, generating the predicted result vector comprises setting the element of the predicted result vector to true.

Abstract: A method and a device having a plurality of bit operations capability, the device includes: a first and a second registers and an instruction fetch circuit, and an arithmetic logic unit adapted to: calculate, during a first clock cycle, a position value representative of a position, within a first information vector, of a first bit of information that has a first value; and to multiply the position value by a multiplication factor to provide a first result and to alter the value of the first bit to a second value to provide an updated information vector, during the first clock cycle.

Abstract: A processor, which executes m number of arithmetic operations in parallel, executes a partial sum instruction which takes an i-th to (i+m?1)-th elements of an input data series as input elements, so as to obtain first vector data, executes the partial sum instruction which takes a (i+x)-th to (i+x+m?1)-th elements of the input data series as the input elements, so as to obtain second vector data, and performs operations to subtract the p-th element of the first vector data and add the p-th element of the second vector data from and to a sum of the i-th to (i+x?1)-th elements of the input data series in parallel for each of the 0-th to (m?1)-th elements, so as to calculate sums of elements for m sections different from each other in parallel, and moving average processing to calculate a moving average from the sums of elements of the sections.

Abstract: Systems and apparatuses are presented relating a programmable processor comprising an execution unit that is operable to decode and execute instructions received from an instruction path and partition data stored in registers in the register file into multiple data elements, the execution unit capable of executing group data handling operations that re-arrange data elements in different ways in response to data handling instructions, the execution unit further capable of executing a plurality of different group floating-point and group integer arithmetic operations that each arithmetically operates on the multiple data elements stored in registers in the register file to produce a catenated result that is returned to a register in the register file, wherein the catenated result comprises a plurality of individual results.

Abstract: Embodiments relate to simplifying large and complex networks and graphs using global connectivity information based on calculated node centralities. An aspect includes calculating node centralities of a graph until a designated number of central nodes are detected. A percentage of the central nodes are then selected as pivot nodes. The neighboring nodes to each of the pivot nodes are then collapsed until the graph shrinks to a predefined threshold of total nodes. Responsive to the number of total nodes reaching the predefined threshold, the simplified graph is outputted.

Abstract: A system, method and computer program product to compute latencies of a plurality of expression trees in a basic block and to select a first and a second expression tree from the plurality of expression trees based on the computed latencies. The first expression tree is isomorphic to the second expression tree and the first and second expression trees are selected in order of largest to smallest latency. This selection ensures that the largest isomorphic expression trees are vectorized first. By vectorizing the largest isomorphic expression trees first, a basic block containing hundreds of statements can be vectorized without significant compile time. Moreover, vectorization of the largest isomorphic expression trees results in a significant improvement in system performance on SIMD processors.

Abstract: A reconfigurable processor configured to include a constant storage register to store a constant is provided, thereby improving efficiency in the use of a memory space. Specifically, a reconfigurable processor includes a plurality of Functional Units (FUs), a configuration memory configured to store configuration information, and a constant storage register configured to store a constant that is used as an operand for an operation in the plurality of FUs.

Abstract: A processor includes a first and second execution unit each of which is arranged to execute multiply instructions of a first type upon fixed point operands and to execute multiply instructions of a second type upon floating point operands. A register file of the processor stores operands in registers that are each addressable by instructions for performing the first and second types of operations. An instruction decode unit is responsive to the at least one multiply instruction of the first type and the at least one multiply instruction of the second type to at the same time enable a first data path between the first set of registers and the first execution unit and to enable a second data path between a second set of registers and the second execution unit.

Abstract: A method for executing dual dispatch of blocks and half blocks. The method includes receiving an incoming instruction sequence using a global front end; grouping the instructions to form instruction blocks, wherein each of the instruction blocks comprise two half blocks; scheduling the instructions of the instruction block to execute in accordance with a scheduler; and performing a dual dispatch of the two half blocks for execution on an execution unit.

Abstract: Systems, apparatuses and methods for utilizing enhanced vector true/false instructions. The enhanced vector true/false instructions generate enhanced predicates to correspond to the request element width and/or vector size. A vector true instruction generates an enhanced predicate where all elements supported by the processing unit are active. A vector false instruction generates an enhanced predicate where all elements supported by the processing unit are inactive. The enhanced predicate specifies the requested element width in addition to designating the element selectors.

Abstract: An example method of updating an output data vector includes identifying a data value vector including element data values. The method also includes identifying an address value vector including a set of elements. The method further includes applying a conditional operator to each element of the set of elements in the address value vector. The method also includes for each element data value in the data value vector, determining whether to update an output data vector based on applying the conditional operator.

Abstract: An apparatus includes memory storing an instruction that identifies a first register, a second register, and a third register. Upon execution of the instruction by a processor, a vector addition operation is performed by the processor to add first values from the first register to second values from the second register. A vector subtraction operation is also performed upon execution of the instruction to subtract the second value from third values from the third register. A vector compare operation is also performed upon execution of the instruction to compare results of the vector addition operation to results of the vector subtraction operation.

Abstract: An error handling method includes identifying a code region eligible for cumulative multiply add (CMA) optimization and translating code region instructions into interpreter code instructions, which may include translating sequences of multiply add instructions in the code region instructions into fusion code including CMA instructions. Floating point (FP) exceptions generated by the fusion code may be monitored and at least a portion of the code region instructions may be re-translated to eliminate some or all fusion code if CMA intermediate rounding exceptions exceed a threshold.

Abstract: An apparatus includes an instruction decoder, first and second source registers and a circuit coupled to the decoder to receive packed data from the source registers and to unpack the packed data responsive to an unpack instruction received by the decoder. A first packed data element and a third packed data element are received from the first source register. A second packed data element and a fourth packed data element are received from the second source register. The circuit copies the packed data elements into a destination register resulting with the second packed data element adjacent to the first packed data element, the third packed data element adjacent to the second packed data element, and the fourth packed data element adjacent to the third packed data element.

Abstract: A new zSeries floating-point unit has a fused multiply-add dataflow capable of supporting two architectures and fused MULTIPLY and ADD and Multiply and SUBTRACT in both RRF and RXF formats for the fused functions. Both binary and hexadecimal floating-point instructions are supported for a total of 6 formats. The floating-point unit is capable of performing a multiply-add instruction for hexadecimal or binary every cycle with a latency of 5 cycles. This supports two architectures with two internal formats with their own biases. This has eliminated format conversion cycles and has optimized the width of the dataflow. The unit is optimized for both hexadecimal and binary floating-point architecture supporting a multiply-add/subtract per cycle.

Abstract: A multiply-and-accumulate (MAC) instruction allows efficient execution of unsigned integer multiplications. The MAC instruction indicates a first vector register as a first operand, a second vector register as a second operand, and a third vector register as a destination. The first vector register stores a first factor, and the second vector register stores a partial sum. The MAC instruction is executed to multiply the first factor with an implicit second factor to generate a product, and to add the partial sum to the product to generate a result. The first factor, the implicit second factor and the partial sum have a same data width and the product has twice the data width. The most significant half of the result is stored in the third vector register, and the least significant half of the result is stored in the second vector register.

Abstract: An optimizing compiler includes a vectorization mechanism that optimizes a computer program by substituting code that includes one or more vector instructions (vectorized code) for one or more scalar instructions. The cost of the vectorized code is compared to the cost of the code with only scalar instructions. When the cost of the vectorized code is less than the cost of the code with only scalar instructions, the vectorization mechanism determines whether the vectorized code will likely result in processor stalls. If not, the vectorization mechanism substitutes the vectorized code for the code with only scalar instructions. When the vectorized code will likely result in processor stalls, the vectorization mechanism does not substitute the vectorized code, and the code with only scalar instructions remains in the computer program.

Abstract: An embodiment includes a method for computing operations, such as modular exponentiation, using a mix of vector and scalar instructions to accelerate various applications such as encryption protocols that rely heavily on large number arithmetic operations. The embodiment requires far fewer instructions to execute the operations than more conventional practices. Other embodiments are described herein.

Abstract: The described embodiments include a processor that executes a vector instruction. The processor starts by receiving a start value and an increment value, and optionally receiving a predicate vector with N elements as inputs. The processor then executes the vector instruction. Executing the vector instruction causes the processor to generate a result vector. When generating the result vector, if the predicate vector is received, for each element in the result vector for which a corresponding element of the predicate vector is active, otherwise, for each element in the result vector, the processor sets the element in the result vector equal to the start value plus a product of the increment value multiplied by a specified number of elements to the left of the element in the result vector.

Abstract: A Vector Checksum instruction. Elements from a second operand are added together one-by-one to obtain a first result. The adding includes performing one or more end around carry add operations. The first result is placed in an element of a first operand of the instruction. After each addition of an element, a carry out of a chosen position of the sum, if any, is added to a selected position in an element of the first operand.

Abstract: A Vector Galois Field Multiply Sum and Accumulate instruction. Each element of a second operand of the instruction is multiplied in a Galois field with the corresponding element of the third operand to provide one or more products. The one or more products are exclusively ORed with each other and exclusively ORed with a corresponding element of a fourth operand of the instruction. The results are placed in a selected operand.

Abstract: A Vector Floating Point Test Data Class Immediate instruction is provided that determines whether one or more elements of a vector specified in the instruction are of one or more selected classes and signs. If a vector element is of a selected class and sign, an element in an operand of the instruction corresponding to the vector element is set to a first defined value, and if the vector element is not of the selected class and sign, the operand element corresponding to the vector element is set to a second defined value.

Abstract: A Reduced Instruction Set Computing (RISC) processor is capable of emulating operation of a floating-point register stack. The RISC processor may include a floating-point register file containing a plurality of floating-point registers, a decoding section for decoding operation instructions, and a floating-point operation section. The RISC processor may also include a control register for controlling status of floating-point registers, and for controlling the decoding section and the floating-point operation section, to thereby emulate a floating-point register stack using the floating-point register file. The decoding section may include a pointer register for maintaining a stack operation pointer, and for storing a value of the stack operation pointer.

Abstract: A processor including: a first and at least a second data processing channel with enable logic for selectively enabling the second channel; logic for generating first and second storage addresses having a variable offset therebetween based on the same one or more address operands of the same storage access instruction; and circuitry for transferring data between the first address and a register of the first data processing channel and between the second address and a corresponding register of the second channel based on a same one or more register specifier operands of the access instruction. The first data processing channel performs an operation using one or more registers of the first data processing channel, and on condition of being enabled the second channel performs the same operation using a corresponding one or more of its own registers based on the same one or more operands of the data processing instruction.

Abstract: A method of an aspect includes receiving a dot product instruction. The dot product instruction indicates a first source packed data including at least four data elements, indicates a second source packed data including at least eight data elements, and indicates a destination storage location. A result packed data is stored in the destination storage location in response to the dot product instruction. The result includes a plurality of data elements that each includes a dot product result. Each of the dot product results includes a sum of products of the at least four data elements of the first source packed data with corresponding data elements in a different subset of at least four data elements of the second source packed data. Other methods, apparatus, systems, and instructions are disclosed.

Abstract: Instructions and logic provide vectorization of conditional loops. A vector expand instruction has a parameter to specify a source vector, a parameter to specify a conditions mask register, and a destination parameter to specify a destination vector to hold n consecutive vector elements, each of the plurality of n consecutive vector elements having a same variable partition size of m bytes. In response to the processor instruction, data is copied from consecutive vector elements in the source vector, and expanded into unmasked vector elements of the specified destination vector, without copying data into masked vector elements of the destination vector, wherein n varies responsive to the processor instruction executed. The source vector may be a register and the destination vector may be in memory. Some embodiments store counts of the condition decisions. Alternative embodiments may store other data, for example such as target addresses, or table offsets, or indicators of processing directives, etc.

Abstract: A processor is described having a functional unit of an instruction execution pipeline. The functional unit has comparison bank circuitry and adder circuitry. The comparison bank circuitry is to compare one or more elements of a first input vector against an element of a second input vector. The adder circuitry is coupled to the comparison bank circuitry to add the number of elements of the second input vector that match a value of the first input vector on an element by element basis of the first input vector.

Abstract: Methods and apparatus relating to instructions with floating point control override are described. In an embodiment, a processor includes a first logic to receive an instruction having one or more bits corresponding to override control data. The override control data is to indicate one or more floating point operation settings that are to override one or more default settings. The processor also has a second logic to perform a floating point operation in response to the instruction and at least one of the one or more floating point operation settings.

Abstract: Systems and apparatuses are presented relating a programmable processor comprising an execution unit that is operable to decode and execute instructions received from an instruction path and partition data stored in registers in the register file into multiple data elements, the execution unit capable of executing group data handling operations that re-arrange data elements in different ways in response to data handling instructions, the execution unit further capable of executing a plurality of different group floating-point and group integer arithmetic operations that each arithmetically operates on the multiple data elements stored in registers in the register file to produce a catenated result that is returned to a register in the register file, wherein the catenated result comprises a plurality of individual results.

Abstract: A graphics processing unit 2 includes a texture pipeline 6 which performs filter operations upon texture values. If the texture values are integer texture values, then they may be processed by the texture pipeline in a variable order corresponding to the order in which they are retrieved from a memory 4. If the texture values are floating point texture values, then they are processed in a fixed order in order to ensure result invariants as the filter operation is non-associative for floating point values. The filter operation is not commenced until all of the floating point texture values have been retrieved from the memory 4 and other available for processing.

Abstract: Detection of whether a result of a floating point operation is safe. Characteristics of the result are examined to determine whether the result is safe or potentially unsafe, as defined by the user. An instruction is provided to facilitate detection of safe or potentially unsafe results.

Abstract: A method and circuit arrangement provide support for packed sum of absolute difference operations in a floating point execution unit, e.g., a scalar or vector floating point execution unit. Existing adders in a floating point execution unit may be utilized along with minimal additional logic in the floating point execution unit to support efficient execution of a fixed point packed sum of absolute differences instruction within the floating point execution unit, often eliminating the need for a separate vector fixed point execution unit in a processor architecture, and thereby leading to less logic and circuit area, lower power consumption and lower cost.

Abstract: A mechanism for recycling error bits in a floating point unit is disclosed. A system of the disclosure includes a memory and a processing device communicably coupled to the memory. In one embodiment, the processing device comprising a floating point unit (FPU) to generate a result value from applying an operation on floating point number inputs to the FPU and generate an error value using the result value. The FPU also writes the result value to a first register of the processing device dedicated to storing results from the operation of the FPU and writes the error value to a second register of the processing device dedicated to storing errors from the operation of the FPU.

Abstract: Systems, apparatuses, and methods of performing in a computer processor broadcasting data in response to a single vector packed broadcasting instruction that includes a source writemask register operand, a destination vector register operand, and an opcode. In some embodiments, the data of the source writemask register is zero extended prior to broadcasting.

Abstract: A vector reduction instruction is executed by a processor to provide efficient reduction operations on an array of data elements. The processor includes vector registers. Each vector register is divided into a plurality of lanes, and each lane stores the same number of data elements. The processor also includes execution circuitry that receives the vector reduction instruction to reduce the array of data elements stored in a source operand into a result in a destination operand using a reduction operator. Each of the source operand and the destination operand is one of the vector registers. Responsive to the vector reduction instruction, the execution circuitry applies the reduction operator to two of the data elements in each lane, and shifts one or more remaining data elements when there is at least one of the data elements remaining in each lane.

Abstract: A floating-point unit and a method of identifying exception cases in a floating-point unit. In one embodiment, the floating-point unit includes: (1) a floating-point computation circuit having a normal path and an exception path and operable to execute an operation on an operand and (2) a decision circuit associated with the normal path and the exception path and configured to employ a flush-to-zero mode of the floating-point unit to determine which one of the normal path and the exception path is appropriate for carrying out the operation on the operand.

Abstract: In one embodiment, the present invention includes a processor having multiple execution units, at least one of which includes a circuit having a multiply-accumulate (MAC) unit including multiple multipliers and adders, and to execute a user-level multiply-multiply-accumulate instruction to populate a destination storage with a plurality of elements each corresponding to an absolute value for a pixel of a pixel block. Other embodiments are described and claimed.

Abstract: Systems and apparatuses are presented relating a programmable processor comprising an execution unit that is operable to decode and execute instructions received from an instruction path and partition data stored in registers in the register file into multiple data elements, the execution unit capable of executing group data handling operations that re-arrange data elements in different ways in response to data handling instructions, the execution unit further capable of executing a plurality of different group floating-point and group integer arithmetic operations that each arithmetically operates on the multiple data elements stored in registers in the register file to produce a catenated result that is returned to a register in the register file, wherein the catenated result comprises a plurality of individual results.

Abstract: Embodiments of systems, apparatuses, and methods for performing in a computer processor absolute difference calculation in response to a single vector packed absolute difference instruction that includes a first and second source vector register operand, a destination vector register operand, and an opcode are described.

Abstract: A computer processor includes a decoder for decoding machine instructions and an execution unit for executing those instructions. The decoder and the execution unit are capable of decoding and executing vector instructions that include one or more format conversion indicators. For instance, the processor may be capable of executing a vector-load-convert-and-write (VLoadConWr) instruction that provides for loading data from memory to a vector register. The VLoadConWr instruction may include a format conversion indicator to indicate that the data from memory should be converted from a first format to a second format before the data is loaded into the vector register. Other embodiments are described and claimed.

Abstract: A mechanism for executing speculative predicated instructions may include execution of initiating execution of a vector instruction when one or more operands upon which the vector instruction depends are available for use, even if a predicate vector that the vector instruction also depends is not available. If the predicate vector was not available, the results of the execution of the vector instruction may be temporarily held until the predicate vector becomes available, at which time, a destination vector may be updated with the results.

Abstract: Methods, systems and computer program products are disclosed for measuring a performance of a program running on a processing unit of a processing system. In one embodiment, the method comprises informing a logic unit of each instruction in the program that is executed by the processing unit, assigning a weight to each instruction, assigning the instructions to a plurality of groups, and analyzing the plurality of groups to measure one or more metrics. In one embodiment, each instruction includes an operating code portion, and the assigning includes assigning the instructions to the groups based on the operating code portions of the instructions. In an embodiment, each type of instruction is assigned to a respective one of the plurality of groups. These groups may be combined into a plurality of sets of the groups.

Abstract: A processing core is described having execution unit logic circuitry having a first register to store a first vector input operand, a second register to a store a second vector input operand and a third register to store a packed data structure containing scalar input operands a, b, c. The execution unit logic circuitry further include a multiplier to perform the operation (a*(first vector input operand))+(b*(second vector operand))+c.