US 2025/0224922 A1 · MANTISSA ALIGNMENT

Abstract

In some embodiments, a computing method includes, for a set of products, each of a respective pair of a first and a second floating-point operands, each having a respective mantissa and exponent, aligning the mantissas of the first operands based on a maximum exponent of the first operands to generate a shared exponent; modifying the mantissas of the first operands based on the shared exponent to generate respective adjusted mantissas of the first operands; generating mantissa products, each based on the mantissa of a respective one of the second operands and a respective one of the adjusted first mantissas retrieved from the memory device; summing the mantissas products to generate a mantissa product partial sum; and combining the shared exponent and the product mantissa partial sum. The adjusted mantissas of the first operands can be saved in, and retrieved from, a memory device for the mantissa product generation.

Claims20

Dependent claims

A computing method, comprising:

for a first plurality of floating-point numbers and second plurality of floating-point numbers, each having a respective mantissa and exponent, aligning the mantissas of the first plurality of floating-point numbers based on a maximum exponent of the first plurality of floating-point numbers to generate a first common exponent;
storing the first plurality of post-alignment mantissas in a memory device;
generating a first plurality of mantissa products, each based on the mantissa of a respective one of the second plurality of floating-point numbers and a respective one of the post-alignment first mantissas retrieved from the memory device;
an accumulation step, comprising summing the first mantissa products to generate a first mantissa product partial sum and to generate a first product partial sum exponent based on the first common exponent and the exponents of the second plurality of floating-point numbers;
and
combining the first product partial sum exponent and the first mantissa product partial sum to form an output floating-point number.

3 more elements

A computing method, comprising:

for a first plurality of weight values, each having a respective weight mantissa and weight exponent, aligning the weight mantissas based on a maximum weight exponent of the first plurality of weight values to generate a first common weight exponent;
storing the post-alignment weight mantissas in a respective first plurality of memory units in an artificial neural network;
providing a first plurality of input activations to respective inputs of a first multiply circuit in the artificial neural network, each of the first plurality of input activations having a respective input mantissa and input exponent;
generating, using the first multiply circuit, first plurality of mantissa products, each based on respective weight mantissa and respective input mantissa;
an accumulation step, comprising summing the first mantissa products to generate a first mantissa product partial sum and to generate a first product partial sum exponent based on the common weight exponent and the exponents of the first plurality of input activation;
and
combining the first product partial sum exponent and the first mantissa product partial sum to form a first output floating-point number.

4 more elements

A computing device, comprising:

a memory array comprising a plurality of memory units, each configured to store a respective mantissa of a respective weight value having a common exponent;
a first storage configured to store the common exponent;
a first digital circuit configured to receive a plurality of input activations, each having a respective mantissa and exponent, and;
a multiply circuit configured to retrieve from the memory array the mantissas of the respective weight values and generate products of the retrieved mantissas and the mantissas of the respective received input activations;
a summing circuit configured to add the products to generate a product sum mantissa and generate a product sum exponent based on the exponents of the received input activations and the common exponent stored in the first storage;
and
a second storage having a mantissa portion configured to store the product sum mantissa and an exponent portion configured to store the exponent of the product exponent.

4 more elements

Dependencies are inferred from the claim text.

Mantissa alignment

Life of this patent

Mantissa alignment

Life of this patent

Abstract

Claims20