Abstract: The present disclosure discloses a processor and a multi-core processor. The processor includes a processor core and a memory. The processor core includes a homomorphic encryption instruction execution module and a general-purpose instruction execution module; the homomorphic encryption instruction execution module is configured to perform homomorphic encryption operation and includes a plurality of instruction set architecture extension components, wherein the plurality of instruction set architecture extension components are respectively configured to perform a sub-operation related to the homomorphic encryption; the general-purpose instruction execution module is configured to perform non-homomorphic encryption operation. The memory is vertically stacked with the processor core and is used as a cache or scratchpad memory of the processor core.

Abstract: This application describes an hardware and a software design for quantization in GNN computation. An exemplary method may include: receiving a graph comprising a plurality of nodes respectively represented by a plurality of feature vectors; segmenting the plurality of feature vectors into a plurality of sub-vectors and grouping the plurality of sub-vectors into a plurality of groups of sub-vectors; performing vector clustering on each of the plurality of groups of sub-vectors to generate a plurality of centroids as a codebook; encoding each of the plurality of feature vectors to obtain a plurality of index maps by quantizing sub-vectors within the each feature vector based on the codebook, wherein each index map occupies a smaller storage space than the each feature vector does; and storing the plurality of index maps as an assignment table instead of the plurality of feature vectors to represent the plurality of nodes for GNN computation.

Abstract: The present disclosure provides an accelerator for processing a vector or matrix operation. The accelerator comprises a vector processing unit comprising a plurality of computation units having circuitry configured to process a vector operation in parallel; a matrix multiplication unit comprising a first matrix multiplication operator, a second matrix multiplication operator, and an accumulator, the first matrix multiplication operator and the second matrix multiplication operator having circuitry configured to process a matrix operation and the accumulator having circuitry configured to accumulate output results of the first matrix multiplication operator and the second matrix multiplication operator; and a memory storing input data for the vector operation or the matrix operation and being configured to communicate with the vector processing unit and the matrix multiplication unit.