Patent classifications
G06F7/4833
Methods and Apparatuses for Performing Multiplication
In a novel computation device, a plurality of partial product generators is communicatively coupled to a binary number multiplier. The binary number is partitioned in the computation device into non-overlapping subsets of binary bits and each subset is coupled to one of the plurality of partial product generators. Each partial product generator, upon receiving, a subset of binary bits representing a number, generates a multiplication product of the number and a predetermined constant. The multiplication products from all partial product generators are summed to generate the final, product between the predetermined constant and the binary number. The partial product generators are constructed by logic gates and wires connected the logic gates including a AND gate. The partial product generators are free of memory elements.
ARITHMETIC PROCESSING DEVICE AND METHOD OF CONTROLLING ARITHMETIC PROCESSING DEVICE
An arithmetic processing device includes: a first memory configured to store values of a first coefficient of a logarithmic function, where the logarithmic function is decomposed into a series operation term and the coefficient term, depending on respective values of a first bit group included in operand data of a first instruction to calculate the value of the first coefficient; a second memory configured to store values of a second coefficient included in the series operation term depending on the respective values of the first bit group included in operand data of a second instruction to calculate the value of the second coefficient; and a selector configured to select the value of the first coefficient read from the first memory based on the execution of the first instruction and select the value of the second coefficient read from the second memory based on the execution of the second instruction.
Processing with compact arithmetic processing element
A processor or other device, such as a programmable and/or massively parallel processor or other device, includes processing elements designed to perform arithmetic operations (possibly but not necessarily including, for example, one or more of addition, multiplication, subtraction, and division) on numerical values of low precision but high dynamic range (LPHDR arithmetic). Such a processor or other device may, for example, be implemented on a single chip. Whether or not implemented on a single chip, the number of LPHDR arithmetic elements in the processor or other device in certain embodiments of the present invention significantly exceeds (e.g., by at least 20 more than three times) the number of arithmetic elements, if any, in the processor or other device which are designed to perform high dynamic range arithmetic of traditional precision (such as 32 bit or 64 bit floating point arithmetic).
PROCESSING WITH COMPACT ARITHMETIC PROCESSING ELEMENT
A processor or other device, such as a programmable and/or massively parallel processor or other device, includes processing elements designed to perform arithmetic operations (possibly but not necessarily including, for example, one or more of addition, multiplication, subtraction, and division) on numerical values of low precision but high dynamic range (LPHDR arithmetic). Such a processor or other device may, for example, be implemented on a single chip. Whether or not implemented on a single chip, the number of LPHDR arithmetic elements in the processor or other device in certain embodiments of the present invention significantly exceeds (e.g., by at least 20 more than three times) the number of arithmetic elements, if any, in the processor or other device which are designed to perform high dynamic range arithmetic of traditional precision (such as 32 bit or 64 bit floating point arithmetic).
PROCESSING WITH COMPACT ARITHMETIC PROCESSING ELEMENT
A processor or other device, such as a programmable and/or massively parallel processor or other device, includes processing elements designed to perform arithmetic operations (possibly but not necessarily including, for example, one or more of addition, multiplication, subtraction, and division) on numerical values of low precision but high dynamic range (LPHDR arithmetic). Such a processor or other device may, for example, be implemented on a single chip. Whether or not implemented on a single chip, the number of LPHDR arithmetic elements in the processor or other device in certain embodiments of the present invention significantly exceeds (e.g., by at least 20 more than three times) the number of arithmetic elements, if any, in the processor or other device which are designed to perform high dynamic range arithmetic of traditional precision (such as 32 bit or 64 bit floating point arithmetic).
Processing unit, method and computer program for multiplication
A processing unit for multiplying a first value by a first multiplicand, or for multiplying the first value by, in each instance, a second and third multiplicand. The processing unit receives the multiplicands in a logarithmic number format, so that the multiplicands are each present in the form of at least one exponent at a specifiable base. The processing unit includes a first register, in which either two exponents of the first multiplicand or the exponent of the second and the exponent of the third multiplicand are stored. A set configuration bit indicates whether either the two exponents of the first multiplicand or the exponent of the second and the exponent of the third multiplicand are stored in the first register. The processing unit includes at least two bitshift operators. A method and a computer program for multiplying the value by the multiplicand are also described.
FLOATING-POINT LOGARITHMIC NUMBER SYSTEM SCALING SYSTEM FOR MACHINE LEARNING
An integrated circuit includes a hardware inexact floating-point logarithmic number system (FPLNS) multiplier. The integrated circuit access registers containing a first floating-point binary value and its first logarithmic binary value and a second floating-point binary value and its second logarithmic binary value, each being in an FPLNS data format. The FPLNS multiplier configured to multiply the first and second floating-point binary values by adding the first logarithmic binary value to the second logarithmic binary value to form a first logarithmic sum, shifting a bias constant by a number of bits of the mantissa of the first floating-point binary value to form a first shifted bias value, subtracting a correction factor from the first shifted bias value to form a first corrected bias value, and subtracting the first corrected bias value from the first logarithmic sum to form a first result.
FLOATING-POINT LOGARITHMIC NUMBER SYSTEM SCALING SYSTEM FOR MACHINE LEARNING
An integrated circuit includes a hardware inexact floating-point logarithmic number system (FPLNS) multiplier. The integrated circuit access registers containing a first floating-point binary value and its first logarithmic binary value and a second floating-point binary value and its second logarithmic binary value, each being in an FPLNS data format. The FPLNS multiplier configured to multiply the first and second floating-point binary values by adding the first logarithmic binary value to the second logarithmic binary value to form a first logarithmic sum, shifting a bias constant by a number of bits of the mantissa of the first floating-point binary value to form a first shifted bias value, subtracting a correction factor from the first shifted bias value to form a first corrected bias value, and subtracting the first corrected bias value from the first logarithmic sum to form a first result.
FLOATING-POINT LOGARITHMIC NUMBER SYSTEM SCALING SYSTEM FOR MACHINE LEARNING
An integrated circuit includes a hardware inexact floating-point logarithmic number system (FPLNS) multiplier. The integrated circuit access registers containing a first floating-point binary value and its first logarithmic binary value and a second floating-point binary value and its second logarithmic binary value, each being in an FPLNS data format. The FPLNS multiplier configured to multiply the first and second floating-point binary values by adding the first logarithmic binary value to the second logarithmic binary value to form a first logarithmic sum, shifting a bias constant by a number of bits of the mantissa of the first floating-point binary value to form a first shifted bias value, subtracting a correction factor from the first shifted bias value to form a first corrected bias value, and subtracting the first corrected bias value from the first logarithmic sum to form a first result.
FLOATING-POINT LOGARITHMIC NUMBER SYSTEM SCALING SYSTEM FOR MACHINE LEARNING
An integrated circuit includes a hardware inexact floating-point logarithmic number system (FPLNS) multiplier. The integrated circuit access registers containing a first floating-point binary value and its first logarithmic binary value and a second floating-point binary value and its second logarithmic binary value, each being in an FPLNS data format. The FPLNS multiplier configured to multiply the first and second floating-point binary values by adding the first logarithmic binary value to the second logarithmic binary value to form a first logarithmic sum, shifting a bias constant by a number of bits of the mantissa of the first floating-point binary value to form a first shifted bias value, subtracting a correction factor from the first shifted bias value to form a first corrected bias value, and subtracting the first corrected bias value from the first logarithmic sum to form a first result.