Compute in memory architecture that allows flexible floating-point operations
AssigneeOpenAI OpCo, LLC
InventorMohammed Elneanaei Abdelmoneem Fouda
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AssigneeOpenAI OpCo, LLC
InventorMohammed Elneanaei Abdelmoneem Fouda
Estimating the term…
The disclosure describes systems and methods for mixed-mode, mixed-precision computation using a configurable compute engine for vector–matrix operations. A processing system selects an operating mode including at least a floating-point mode or an integer mode for the compute engine. Operand storage and format preprocessing route differently sized element representations through shared lanes. In floating-point mode, compute circuitry generates a mantissa product and a product exponent, and alignment applies power-of-two control through a selection network, including as part of a fused multiply-accumulate path. Parallel adder trees feed a hierarchical output accumulator sized to the selected precision. Normalization operates at a wider intermediate precision, applies block-level scaling with dequantization, and, in lower-precision operation, performs groupwise normalization with an intermediate-precision combine to preserve a constant compute-block size. Implementations integrate the compute engine within a memory macro with double buffering or deploy the compute engine as a standalone accelerator.
A computing system, comprising:
A method of operating a compute engine of a computing system, comprising:
An apparatus for processing operand values in multiple numeric formats, including:
Dependencies are inferred from the claim text.