Abstract: A process for a floating point multiplier-accumulator (MAC) is operative on N pairs of floating point values using N MAC processes operating concurrently, each MAC process operating on a pair of values comprising an input value and a coefficient value. Each MAC process simultaneously generates: an integer form fraction at a first bitwidth and a second bitwidth greater than the first bitwidth, a sign bit, and an exponent difference computed by subtracting an exponent sum from a maximum exponent sum of all exponent sums. The integer form fractions of the first bitwidths are provided to an adder tree using the first bitwidth, and if the sum has an excess percentage of leading 0s, then the second bitwidth is used by an adder tree using the second bitwidth to form a great precision integer form fraction. The sign, integer form fraction, and maximum exponent are provided to an normalizer which generates a floating point result.

Abstract: A process for a floating point multiplier-accumulator (MAC) is operative on N pairs of floating point values using N MAC processes operating concurrently, each MAC process operating on a pair of values comprising an input value and a coefficient value. Each MAC process simultaneously generates an integer form fraction accompanied by a sign bit and an exponent difference computed by subtracting an exponent sum from a maximum exponent sum of all exponent sums. A range estimating process determines a possible range of values from the exponent differences and determines an adder precision. A summing process adds all of the integer form fractions using the determined adder precision, and converts the sum to a floating point value using the maximum exponent sum, sign bit of the summed integer form fractions, and optionally performs a 2's complement of the summed integer form fraction if the sign bit is negative.

Abstract: A floating point multiplier-accumulator (MAC) multiplies and accumulates N pairs of floating point values using N MAC processors operating simultaneously, each pair of values comprising an input value and a coefficient value to be multiplied and accumulated. The pairs of floating point values are simultaneously processed by the plurality of MAC processors, each of which outputs a signed integer form fraction and a maximum exponent. A range estimator forms a possible range of values from the exponent differences and determines an adder precision. The integer form fractions are summed using the adder precision, a sign bit is extracted, and a floating point value is output. Each MAC processor provides its integer form fraction with a precision determined by the MAC processor's exponent difference.

Abstract: A floating point multiplier-accumulator (MAC) multiplies and accumulates N pairs of floating point values using N MAC processors operating simultaneously, each pair of values comprising an input value and a coefficient value to be multiplied and accumulated. The pairs of floating point values are simultaneously processed by the plurality of MAC processors, each of which output a signed integer form fraction with a first bitwidth and a second bitwidth, along with a maximum exponent. The first bitwidth signed integer form fractions are summed by an adder tree using the first bitwidth to form a first sum, and when an excess leading 0 condition is detected, a second adder tree operative on the second bitwidth integer form fractions forms a second sum. The first sum or second sum, along with the maximum exponent, is converted into floating point result.

Abstract: A vector dot product multiplier receives a row vector and a column vector as floating point numbers in a format of sign plus exponent bits plus mantissa bits. The dot product multiplier generates a single dot product value by separately processing the sign bits, exponent bits, and mantissa bits in a few pipelined stages. A first pipeline stage generates a sign bit, a normalized mantissa formed by multiplying pairs multiplicand elements, and exponent information. A second pipeline stage receives the multiplied pairs of normalized mantissas, performs an adjustment, performs a padding, complement, and shift, and sums the results in an adder stage. The resulting integer is normalized to generate a sign bit, exponent, and mantissa of the floating point result.

Abstract: A process for performing vector dot products receives a row vector and a column vector as floating point numbers in a format of sign plus exponent bits plus mantissa bits. The process generates a single dot product value by separately processing the sign bits, exponent bits, and mantissa bits to form a sign bit, a normalized mantissa formed by multiplying pairs multiplicand elements, and exponent information including MAX_EXP and EXP_DIFF. A second pipeline stage receives the multiplied pairs of normalized mantissas, optionally performs an exponent adjustment, pads, complements and shifts the normalized mantissas, and the results are added in a series of stages until a single addition result remains, which is normalized using MAX_EXP to form the floating point output result.

Abstract: A floating point multiplier-accumulator (MAC) multiplies and accumulates N pairs of floating point values using N MAC processors operating simultaneously, each pair of values comprising an input value and a coefficient value to be multiplied and accumulated. The pairs of floating point values are simultaneously processed by the plurality of MAC processors, each of which outputs a signed integer form fraction and a maximum exponent. A range estimator forms a possible range of values from the exponent differences and determines an adder precision. The integer form fractions are summed using the adder precision, a sign bit is extracted, and a floating point value is output. Each MAC processor provides its integer form fraction with a precision determined by the MAC processor's exponent difference.

Abstract: A process for a floating point multiplier-accumulator (MAC) is operative on N pairs of floating point values using N MAC processes operating concurrently, each MAC process operating on a pair of values comprising an input value and a coefficient value. Each MAC process simultaneously generates: an integer form fraction at a first bitwidth and a second bitwidth greater than the first bitwidth, a sign bit, and an exponent difference computed by subtracting an exponent sum from a maximum exponent sum of all exponent sums. The integer form fractions of the first bitwidths are provided to an adder tree using the first bitwidth, and if the sum has an excess percentage of leading 0s, then the second bitwidth is used by an adder tree using the second bitwidth to form a great precision integer form fraction. The sign, integer form fraction, and maximum exponent are provided to an normalizer which generates a floating point result.

Abstract: A floating point multiplier-accumulator (MAC) multiplies and accumulates N pairs of floating point values using N MAC processors operating simultaneously, each pair of values comprising an input value and a coefficient value to be multiplied and accumulated. The pairs of floating point values are simultaneously processed by the plurality of MAC processors, each of which output a signed integer form fraction with a first bitwidth and a second bitwith, along with a maximum exponent. The first bitwidth signed integer form fractions are summed by an adder tree using the first bitwidth to form a first sum, and when an excess leading 0 condition is detected, a second adder tree operative on the second bitwidth integer form fractions forms a second sum. The first sum or second sum, along with the maximum exponent, is converted into floating point result.

Abstract: A process for a floating point multiplier-accumulator (MAC) is operative on N pairs of floating point values using N MAC processes operating concurrently, each MAC process operating on a pair of values comprising an input value and a coefficient value. Each MAC process simultaneously generates an integer form fraction accompanied by a sign bit and an exponent difference computed by subtracting an exponent sum from a maximum exponent sum of all exponent sums. A range estimating process determines a possible range of values from the exponent differences and determines an adder precision. A summing process adds all of the integer form fractions using the determined adder precision, and converts the sum to a floating point value using the maximum exponent sum, sign bit of the summed integer form fractions, and optionally performs a 2's complement of the summed integer form fraction if the sign bit is negative.

Abstract: A process for performing vector dot products receives a row vector and a column vector as floating point numbers in a format of sign plus exponent bits plus mantissa bits. The process generates a single dot product value by separately processing the sign bits, exponent bits, and mantissa bits to form a sign bit, a normalized mantissa formed by multiplying pairs multiplicand elements, and exponent information including MAX_EXP and EXP_DIFF. A second pipeline stage receives the multiplied pairs of normalized mantissas, optionally performs an exponent adjustment, pads, complements and shifts the normalized mantissas, and the results are added in a series of stages until a single addition result remains, which is normalized using MAX_EXP to form the floating point output result.

Abstract: A vector dot product multiplier receives a row vector and a column vector as floating point numbers in a format of sign plus exponent bits plus mantissa bits. The dot product multiplier generates a single dot product value by separately processing the sign bits, exponent bits, and mantissa bits in a few pipelined stages. A first pipeline stage generates a sign bit, a normalized mantissa formed by multiplying pairs multiplicand elements, and exponent information. A second pipeline stage receives the multiplied pairs of normalized mantissas, performs an adjustment, performs a padding, complement, and shift, and sums the results in an adder stage. The resulting integer is normalized to generate a sign bit, exponent, and mantissa of the floating point result.