Abstract: The present disclosure relates to a method of storing, by a load and store circuit or other processing means, a variable precision floating point value to a memory address of a memory, the method comprising: reducing the bit length of the variable precision floating point value to no more than a size limit, and storing the variable precision floating point value to one of a plurality of storage zones in the memory, each of the plurality of storage zones having a storage space equal to or greater than the size limit (MBB).

Abstract: A sequence alignment method that may be performed by a vector processor is may include loading a sequence that is an instance of vector data including a plurality of elements, dividing the sequence into two groups, aligning respective elements of the groups to generate a sequence of sorted elements according to a single instruction multiple data mode, and iteratively performing an alignment operation based on a determination that each group in the sequence of sorted elements includes more than one element of the plurality of elements. Each iteration may include dividing each group to form new groups and aligning respective elements of each pair of adjacent new groups to generate a new sequence of sorted elements. The new sequence of a current iteration of the alignment operation may be transmitted as a data output, based on a determination that each new group does not include more than one element.

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, apparatuses and methods may provide for technology that in response to an identification that one or more hardware units are to execute on a first type of data format, decomposes a first original floating point number to a plurality of first segmented floating point numbers that are to be equivalent to the first original floating point number. The technology may further in response to the identification, decompose a second original floating point number to a plurality of second segmented floating point numbers that are to be equivalent to the second original floating point number. The technology may further execute a multiplication operation on the first and second segmented floating point numbers to multiply the first segmented floating point numbers with the second segmented floating point numbers.

Abstract: A sequence alignment method that may be performed by a vector processor is may include loading a sequence that is an instance of vector data including a plurality of elements, dividing the sequence into two groups, aligning respective elements of the groups to generate a sequence of sorted elements according to a single instruction multiple data mode, and iteratively performing an alignment operation based on a determination that each group in the sequence of sorted elements includes more than one element of the plurality of elements. Each iteration may include dividing each group to form new groups and aligning respective elements of each pair of adjacent new groups to generate a new sequence of sorted elements. The new sequence of a current iteration of the alignment operation may be transmitted as a data output, based on a determination that each new group does not include more than one element.

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: A vector processor includes: a temporary storage device configured to retain a plurality of elements representing data used at the time of performing an operation appropriate for an instruction; a data type determining part configured to determine what data type the elements retained by the temporary storage device are to be handled as among predetermined data types, in accordance with the instruction; and an output destination deciding part configured to decide an output destination of each of the elements stored by the temporary storage device, based on the result of determination by the data type determining part. The vector processor is configured to output each of the elements to the output destination decided by the output destination deciding part, thereby performing the operation.

Abstract: A processor including a physical register file with multiple physical registers, mapping logic, and a merge system. The mapping logic maps up to a first maximum number of the physical registers for each architectural register specified in received program instructions and stores corresponding mappings in a rename table. The merge system generates a merge instruction for each architectural register that needs to be merged, inserts each generated merge instruction into the program instructions to provide a modified set of instructions, and that issues the modified set of instructions in consecutive issue cycles based on a take rule. In one embodiment, the first maximum number may be two.

Abstract: A computing system includes computational memory and digital combinational circuitry operatively coupled with the computational memory. The computational memory is configured to perform computations at a prescribed precision. The digital combinational circuitry is configured to increase the precision of the computations performed by the computational memory. The computational memory and the digital combinational circuitry may be configured to iteratively perform a computation to a predefined precision. The computational memory may include circuitry configured to perform analog computation using values stored in the computational memory, and the digital combinational circuitry may include a central processing unit, a graphics processing unit and/or application specific circuitry. The computational memory may include an array of resistive memory elements having resistance or conductance values stored therein, the respective resistance or conductance values being programmable.

Abstract: A processor including a physical register file, a rename table, mapping logic, size tracking logic, and merge logic. The rename table maps an architectural register with a larger index and a smaller index. The mapping logic detects a partial write instruction that specifies an architectural register that is already identified by an entry of the rename table mapped to a second physical register allocated for a larger write operation, and includes an index for the allocated register for the partial write instruction into the smaller index location of the entry. The size tracking logic provides a merge indication for the partial write instruction if the write size of the previous write instruction is larger. The merge logic merges the result of the partial write instruction with the second physical register during retirement of the partial write instruction.

Abstract: A method of accumulating data by a processor in a nonvolatile memory to track use of a device. The method includes: retrieving by the processor a next datum for accumulation into a first accumulation stored in the memory, the next datum representing a next use of the device; generating by the processor a next dither offset; adding by the processor the next dither offset to the next datum to produce a first sum; dividing by the processor the first sum by a scale factor to produce a quantized datum; and adding by the processor the quantized datum to the first accumulation. The first accumulation tracks the use of the device.

Abstract: A control device includes: a first conversion unit that converts floating point data generated by an operation of a floating point operation command into a numeric string in first format; and a second conversion unit that converts the numeric string in first format into a numeric string in second format. A character string data generation unit generates a character string data including the numeric strings in first format and in second format and outputs the character string data to an external device or an external storage medium.

Abstract: A specialized processing block in a programmable integrated circuit device is configurable to perform floating-point arithmetic operations at selectable different precisions. The specialized processing block includes a plurality of different respective types of floating-point arithmetic operator structures. For each respective type of floating-point arithmetic operator structure, respective control circuitry for partitions the respective type of floating-point arithmetic operator structure to select between a first precision for which the respective type of floating-point arithmetic operator structure is not partitioned, and at least a second precision, less than the first precision, for which the respective type of floating-point arithmetic operator structure is partitioned into at least two smaller ones of the respective type of floating-point arithmetic operator structure.

Abstract: Apparatus for processing data includes processing circuitry 16, 18, 20, 22, 24, 26 and decoder circuitry 14 for decoding program instructions. The program instructions decoded include a floating point pre-conversion instruction which performs round-to-nearest ties to even rounding upon the mantissa field of an input floating number to generate an output floating point number with the same mantissa length but with the mantissa rounded to a position corresponding to a shorter mantissa field. The output mantissa field includes a suffix of zero values concatenated the rounded value. The decoder for circuitry 14 is also responsive to an integer pre-conversion instruction to quantize and input integer value using round-to-nearest ties to even rounding to form an output integer operand with a number of significant bits matched to the mantissa size of a floating point number to which the integer is later to be converted using an integer-to-floating point conversion instruction.

Abstract: A method of an aspect includes receiving a floating point round-off amount determination instruction. The instruction indicates a source of one or more floating point data elements, indicates a number of fraction bits after a radix point, and indicates a destination storage location. A result including one or more result floating point data elements is stored in the destination storage location in response to the floating point round-off amount determination instruction. Each of the one or more result floating point data elements includes a difference between a corresponding floating point data element of the source in a corresponding position, and a rounded version of the corresponding floating point data element of the source that has been rounded to the indicated number of the fraction bits. Other methods, apparatus, systems, and instructions are disclosed.

Abstract: The resources needed—particularly in a programmable device—when carrying out a mixed-precision multiplication-based floating-point operation (i.e., multiplication or division) is reduced by maintaining the mantissas of the operands in their native precisions instead of promoting the lower-precision number to the higher precision. Exponents and other elements can be handled by the higher-precision logic as they do not consume significant resources.

Abstract: A method and apparatus for performing a floating-point operation with a floating-point processor having a given precision is disclosed. A subprecision for the floating-point operation on one or more floating-point numbers is selected. The selection of the subprecision results in one or more excess bits for each of the one or more floating-point numbers. Power may be removed from one or more components in the floating-point processor that would otherwise be used to store or process the one or more excess bits, and the floating-point operation is performed with power removed from the one or more components.

Abstract: An embedded control system capable of ensuring precision in arithmetic with data in the floating-point format and also avoiding a shortage of the storage area of a memory is provided. According to an embedded control system in the present invention, when discrete data in the floating-point format is stored in a read-only memory, the discrete data in the floating-point format is converted into data in a significand-reduced floating-point format before being stored. Here, a significand-reduced floating-point number is a number obtained by deleting low-order bits of the significand of a floating-point number. Further, an interpolation search is performed using discrete data, the discrete data in the significand-reduced floating-point format stored in the read-only memory is brought back to the discrete data in the floating-point format before an interpolation search being performed.

Abstract: Systems and methods for multi-precision computation are disclosed. One embodiment of the present invention includes a plurality of multiply-add units (MADDs) configured to perform one or more single precision operations and an arrangement generator to generate one or more mantissa arrangements using a plurality of double precision numbers. Each MADD is configured to receive and load said mantissa arrangements from the arrangement generator. The MADDs compute a result of a multi-precision computation using the mantissa arrangements. In an embodiment, the MADDs are configured to simultaneously perform operations that include, single precision operations, double-precision additions and double-precision multiply and additions.

Abstract: A floating point multiplier includes a data path in which a plurality of partial products are calculated and then reduced to a first partial product and a second partial product. Shift amount determining circuitry 100 analyzes the exponents of the input operands A and B as well as counting the leading zeros in the fractional portions of these operands to determine an amount of left shift or right shift to be applied by shifting circuitry 200, 202 within the multiplier data path. This shift amount is applied so as to align the partial products so that when they are added they will produce the result C without requiring this to be further shifted. Furthermore, shifting the partial products to the correct alignment in this way in advance of adding these partial products permits injection rounding combined with the adding of the partial products to be employed for cases including subnormal values.

Abstract: The disclosure describes an adaptive multi-shader within a processor that uses one or more high-precision arithmetic logic units (ALUs) and low-precision ALUs to process data based on the type of the data. Upon receiving a stream of data, the adaptive multi-shader first determines the type of the data. For example, the adaptive multi-shader may determine whether the data is suitable for high-precision processing or low-precision processing. The adaptive multi-shader then processes the data using the high-precision ALUs when the data is suitable for high-precision processing, and processes the data using the high-precision ALUs and the low-precision ALUs when the data is suitable for low-precision processing. The adaptive multi-shader may substantially reduce power consumption and silicon size of the processor by implementing the low-precision ALUs while maintaining the ability to process data using high-precision processing by implementing the high-precision ALUs.

Abstract: A floating point execution unit is capable of selectively repurposing a subset of the significand bits in a floating point value for use as additional exponent bits to dynamically provide an extended range for floating point calculations. A significand field of a floating point operand may be considered to include first and second portions, with the first portion capable of being concatenated with the second portion to represent the significand for a floating point value, or, to provide an extended range, being concatenated with the exponent field of the floating point operand to represent the exponent for a floating point value.

Abstract: A single-precision floating-point data storing method for use in a processor including a register, which has a size that can store double-precision floating-point data, for storing double-precision floating-point data and single-precision floating-point data comprises writing input single-precision floating-point data to the high-order half of the register, and writing all zeros to the low-order half of the register if a single-precision floating-point data process is specified.

Abstract: A method of generating a private key for use in an authentication protocol comprises, at a client: receiving a user specific identifier; converting the identifier through a one-way function to a string of a pre-determined length; and mapping said string to a permutation ?priv of a pre-determined order, said permutation being operable with a first graph G1 to generate a second graph G2=?priv(G1).

Abstract: A method, computer program product and a system for identifying decimal floating point addition operations that guarantee operand alignment and do not require alignment, normalization or rounding are provided. The method includes: receiving an instruction to perform an addition of a first operand and a second operand; extracting a first exponent (EXP) and a first most significant digit (MSD) from the first operand; extracting a second EXP and a second MSD from the second operand; and determining whether alignment between the first operand and the second operand is guaranteed, based on the first EXP, the first MSD, the second EXP and the second MSD.

Abstract: Included are embodiments of a Multiply-Accumulate Unit to process multiple format floating point operands. For short format operands, embodiments of the Multiply Accumulate Unit are configured to process data with twice the throughput as long and mixed format data. At least one embodiment can include a short exponent calculation component configured to receive short format data, a long exponent calculation component configured to receive long format data, and a mixed exponent calculation component configured to receive short exponent data, the mixed exponent calculation component further configured to received long format data. Embodiments also include a mantissa datapath configured for implementation to accommodate processing of long, mixed, and short floating point operands.

Abstract: Systems and methods for encoding floating point numbers. A system can include encoding logic which encodes invalid floating point representations as valid data. Decoding logic can be used to recognize the invalid floating point representations and map can provide the invalid floating point representations to valid data values. The decoding logic then can provide the valid data values so that operations on the valid data values can be performed in accordance with instructions received from an associated program.

Abstract: In this invention we describe a new type of computer—infinity computer—that is able to operate with infinite, infinitesimal, and finite numbers in such a way that it becomes possible to execute the usual arithmetical operations with all of them. For the new computer it is shown how the memory for storage of these members is organized and how the new arithmetic logic unit (NALU) executing arithmetical operations with them works.

Abstract: Decimal calculation apparatus, which performs multidigit decimal calculation with the number of calculation digits set in calculation instruction, comprises multidigit memory section capable of storing values with greater numbers of digits than the number of digits of a predetermined digit unit in plurality of memory areas; calculation-instruction memory section which stores calculation instruction having the number of calculation digits and type of calculation set therein; and decimal calculation section which performs decimal calculation of sequentially calculating numerical values of corresponding digit units respectively stored in plurality of memory areas of the multidigit memory section, digit unit by digit unit in the number of calculation digits set in calculation instruction stored in calculation-instruction memory section, in decimal calculation according to type of calculation set in calculation instruction stored in calculation-instruction memory section, and sequentially writing calculation resul

Abstract: Within a processor 2 providing single instruction multiple data (SIMD) type operation, single data processing instructions can serve to control processing logic 4, 6, 8, 10 to perform SIMD-type processing operations upon multiple independent input values to generate multiple independent result values having a greater data width than the corresponding input values. A repartitioner (FIG. 5) in the form of appropriately controlled multiplexers serves to partition these result data values into high order bit portions and low order bit portions that are stored into separate registers 38, 40. The required SIMD width preserved result values can be read from the desired high order 38 result register or low order result register 40 without further processing being required. Furthermore, the preservation of the full result facilitates improvements in accuracy, such as over extended accumulate operations and the like.

Abstract: A floating point execution unit is capable of selectively repurposing a subset of the significand bits in a floating point value for use as additional exponent bits to dynamically provide an extended range for floating point calculations. A significand field of a floating point operand may be considered to include first and second portions, with the first portion capable of being concatenated with the second portion to represent the significand for a floating point value, or, to provide an extended range, being concatenated with the exponent field of the floating point operand to represent the exponent for a floating point value.

Abstract: A single-precision floating-point data storing method for use in a processor including a register, which has a size that can store double-precision floating-point data, for storing double-precision floating-point data and single-precision floating-point data comprises writing input single-precision floating-point data to the high-order half of the register, and writing all zeros to the low-order half of the register if a single-precision floating-point data process is specified.

Abstract: A calculating unit including a number of bit slices which is less than the number of positions of the operand to be processed. Each bit slice has a logic element and a communication bus between the logic element and the plurality of register cells. The register cells are connected in parallel with respect to the slice-internal communication bus and are controlled by a controller so that only one register cell of the plurality of register cells is coupled to the communication bus at a time.

Abstract: A microcontroller comprising a central processing unit and a further fault processing unit suitable for performing validation of operations of said central processing unit. The further fault processing unit is external and different with respect to said central processing unit and said further fault processing unit comprises at least a module for performing validation of operations of said central processing unit and one or more modules suitable for performing validation of operations of other functional parts of said microcontroller. Validation of operations of said central processing unit is performed by using one or more of the following fault tolerance techniques: data shadowing; code&flow signature; data processing legality check; addressing legality check; ALU concurrent integrity checking; concurrent mode/interrupt check.

Abstract: The disclosure describes an adaptive multi-shader within a processor that uses one or more high-precision arithmetic logic units (ALUs) and low-precision ALUs to process data based on the type of the data. Upon receiving a stream of data, the adaptive multi-shader first determines the type of the data. For example, the adaptive multi-shader may determine whether the data is suitable for high-precision processing or low-precision processing. The adaptive multi-shader then processes the data using the high-precision ALUs when the data is suitable for high-precision processing, and processes the data using the high-precision ALUs and the low-precision ALUs when the data is suitable for low-precision processing. The adaptive multi-shader may substantially reduce power consumption and silicon size of the processor by implementing the low-precision ALUs while maintaining the ability to process data using high-precision processing by implementing the high-precision ALUs.

Abstract: The present invention concerns a method for transcoding a N bits word into a M bits word with M<N. The invention is applicable in various fields and more particularly in the display field. The method comprises the following steps:-breaking down the N bits word into an exponent part and a mantissa part having each a size which varies according to the value of said N bits word, the size of the mantissa part increasing with the value of said N bits word, and -encoding the exponent part of the N bits word into a variable number of bits A and removing, if need be, least significant bits of the mantissa part in order to obtain a mantissa with a variable number of bits B, with A+B=M.

Abstract: In one embodiment, a digital signal processor (DSP) processes both n-bit data and (n/2)-bit data. The DSP includes multiple processing paths. A first processing path processes n-bit data. A second processing path is processes (n/2)-bit data. The multiple processing paths may be established using multiple components or may share components. When the processing paths share components, only one of the processing paths may be used at a time.

Abstract: A multiply accumulate unit (“MAC”) that performs operations on packed integer data. In one embodiment, the MAC receives 2 32-bit data words which, depending on the specified mode of operation, each contain either four 8-bit operands, two 16-bit operands, or one 32-bit operand. Depending on the mode of operation, the MAC performs either sixteen 8×8 operations, four 16×16 operations, or one 32×32 operation. Results may be individually retrieved from registers and the corresponding accumulator cleared after the read cycle. In addition, the accumulators may be globally initialized. Two results from the 8×8 operations may be packed into a single 32-bit register. The MAC may also shift and saturate the products as required.

Abstract: A compiler for data processing outputs lower-level code for packing multiple signed data elements per register into a processor's registers using the rules set forth herein, and when executed, the code simultaneously operates on the elements in a register in a single cycle using the same operand. The elements can be independent of each other as defined by compiler directives, and the sizes of the elements in a register can differ from each other. Moreover, a relatively large element can be split across multiple registers. In an exemplary application, a data stream representing two images can be simultaneously processed using the same number of registers as have been required to process a single image. Or, a single image can be processed approaching N-times faster, where N is the number of elements per register. In any case, the present invention results in a significant increase in processing efficiency.

Abstract: A computing device (40) comprises an electrical circuit and a software application. A display screen (138) and an input device (140) are electrically coupled to the electrical circuit. The software application provides instructions to determine the number of significant figures for a number entered via the input device, and simultaneously display on the display screen the entered number along with the number of significant figures for the entered number, and/or the software application provides instructions to calculate a floating point answer for a mathematical operation entered for one or more numbers entered into the computing device, round the floating point answer to the proper precision or to the proper number of significant figures, determine the number of significant figures for the rounded answer, and simultaneously display on the display the rounded answer and its number of significant figures.

Abstract: A programmable processor and system for improving the performance of processors by incorporating an execution unit operable to decode and execute single instructions specifying three registers each containing a plurality of data elements, the execution unit operable to multiply the first and second registers and add the third register to produce a catenated result containing a plurality of data elements. Additional instructions provide group floating-point subtract, add, multiply, set less, and set greater equal operations. The set less and set greater equal operations produce alternatively zero or an identity element for each element of a catenated result, the result facilitating alternative selection of individual data elements using bitwise Boolean operations and without requiring conditional branch operations.

Abstract: The process for performing operations with a variable arithmetic does not call for any shifting of the data in the different registers that come into play in the operation. The input registers can have empty parts which are completed by appropriate bit sequences to ensure a propagation of a possible outgoing carry over in order to recover that carry over from a result register.

Abstract: There is disclosed a pipelined floating point unit comprising: a) a first plurality of pipelined functional units for processing operands conforming to a single instruction-multiple data stream (SIMD) instruction set architecture (ISA); b) a second plurality of pipelined functional units for processing operands conforming to a scalar instruction set architecture (ISA); and c) a first format fault detection circuit associated with at least one of the first plurality of pipelined functional units for determining whether a first operand is a denormal number and, in response to the determination, generating a first fault signal. The first fault signal causes a number conversion circuit associated with the pipelined floating point unit to modify a significand and an exponent of at least one operand in a data register associated with the pipelined floating point unit to thereby convert the at least one operand to a denormal number.

Abstract: Logic for calculating a sum of numbers using an overflow counter in an environment exceeded by the numbers in bit-size accesses a least significant portion of a first number, accesses a least significant portion of a second number, and adds the least significant portion of the first number to the least significant portion of the second number. The resulting sum includes a first intermediate number. If a carry is generated by the addition of the least significant portion of the first number to the least significant portion of the second number, the logic increments an overflow counter to record the generated carry. The logic accesses least significant portions of the remaining numbers, adds the least significant portions to the first intermediate number, and increments the overflow counter each time a carry is generated to record the generated carry. After each of the least significant portions has been added to the first intermediate number, the logic stores the first intermediate number.

Abstract: Logic for performing 64-bit scaled sum-of-product operations in a 32-bit environment accesses a first 32-bit number, a second 32-bit number, and a shift number in a first operation. The logic multiplies the first 32-bit number by the second 32-bit number. The resulting product includes a first 64-bit number that includes a most and least significant 32-bit portions. The logic right-shifts the least significant 32-bit portion of the first 64-bit number according to the shift number, accesses a least significant 32-bit portion of a second 64-bit number, and adds the right-shifted least significant 32-bit portion of the first 64-bit number to the least significant 32-bit portion of the second 64-bit number. The resulting sum includes a least significant 32-bit portion of a final result of a 64-bit scaled sum-of-product operation and a carry bit. In a second operation, the logic multiplies the first 32-bit number by the second 32-bit number. The resulting product includes the first 64-bit number.

Abstract: In one embodiment of the present invention, logic for limiting the value of a 64-bit number to a maximum limit in a 32-bit environment allocates one or more bit flags in a first operation. The logic accesses a most significant 32-bit portion of a first 64-bit number including a first value. The logic accesses a most significant 32-bit portion of a second 64-bit number including a maximum limit and a second value. The logic compares the first value with the second value and, if the first value is greater than the second value, sets the bit flags accordingly and changes the most significant 32-bit portion of the first 64-bit number to match the same of the second 64-bit number. If the first value is equal to the second value, the logic sets the one or more allocated bit flags accordingly. In a second operation following the first operation, the logic accesses the bit flags.

Abstract: A digital signal processing system performs different word-length arithmetic operations (e.g., 24-bit arithmetic and 16-bit arithmetic) using the same hardware. The digital signal processing system includes internal buses, a host processor coupled to the internal buses, a DSP coprocessor coupled to the internal buses for performing a digital signal processing under control of the host processor, and first and second data memories coupled to the internal buses. The DSP coprocessor further includes a random access memory (RAM) pointer for generating addresses to access the first and second data memories, a multiply and accumulate (MAC) unit for performing a multiply and accumulate operation, an arithmetic unit, a shift and exponent unit for shifting operands and for evaluating exponents, and a local decoder for decoding DSP commands from the host processor and controlling the RAM pointer, the arithmetic unit, and the shift and exponent unit.

Abstract: A signal processor with an instruction set architecture (ISA) for flexible data typing, permutation, and type matching of operands. The signal processor includes a data typer and aligner to support flexible data typing, permutation and type matching of operands of the instruction set architecture. The data typer and aligner is selectively configued to align and select one of more sets of data bits from one or more data buses as operands for functional blocks of the signal processor in response to fields of an instruction.

Abstract: A high-speed, wide dynamic range, digital accumulator includes a first adder stage in which an input addend is added to a value of a least significant part of an output of an accumulator from a preceding clock period. The accumulator also includes at least one second stage having incrementer/decrementer means for performing an increment, decrement or identity operation on a most significant part of the output of the accumulator. The incrementer/decrementer means includes logic means for triggering the increment, a decrement or identity operation on the most significant part of the accumulator output based on a decision made on results obtained at the previous clock period.