Abstract: A computing device to implement fast floating-point adder tree for the neural network applications is disclosed. The fast float-point adder tree comprises a data preparation module, a fast fixed-point Carry-Save Adder (CSA) tree, and a normalization module. The floating-point input data comprises a sign bit, exponent part and fraction part. The data preparation module aligns the fraction part of the input data and prepares the input data for subsequent processing. The fast adder uses a signed fixed-point CSA tree to quickly add a large number of fixed-point data into 2 output values and then uses a normal adder to add the 2 output values into one output value. The fast adder uses for a large number of operands is based on multiple levels of fast adders for a small number of operands. The output from the signed fixed-point Carry-Save Adder tree is converted to a selected floating-point format.

Abstract: Embodiments described herein provide a mission-critical artificial intelligence (AI) processor (MAIP), which includes an instruction buffer, processing circuitry, a data buffer, command circuitry, and communication circuitry. During operation, the instruction buffer stores a first hardware instruction and a second hardware instruction. The processing circuitry executes the first hardware instruction, which computes an intermediate stage of an AI model. The data buffer stores data generated from executing the first hardware instruction. The command circuitry determines that the second hardware instruction is a hardware-initiated store instruction for transferring the data from the data buffer. Based on the hardware-initiated store instruction, the communication circuitry transfers the data from the data buffer to a memory device of a computing system, which includes the mission-critical processor, via a communication interface.

Abstract: Embodiments described herein provide a mission-critical artificial intelligence (AI) processor (MAIP), which includes an instruction buffer, processing circuitry, a data buffer, command circuitry, and communication circuitry. During operation, the instruction buffer stores a first hardware instruction and a second hardware instruction. The processing circuitry executes the first hardware instruction, which computes an intermediate stage of an AI model. The data buffer stores data generated from executing the first hardware instruction. The command circuitry determines that the second hardware instruction is a hardware-initiated store instruction for transferring the data from the data buffer. Based on the hardware-initiated store instruction, the communication circuitry transfers the data from the data buffer to a memory device of a computing system, which includes the mission-critical processor, via a communication interface.