Abstract: Efficiently synthesizing an entire application that consists of multiple algorithms for hardware implementation is a very difficult and unsolved problem. One of the main challenges is the ...

Abstract: Graph convolutional networks (GCNs) are emerging neural network models designed to process graph-structured data. Due to massively parallel computations using irregular data structures by ...

Sparse general matrix-matrix multiplication (SpGEMM) is fundamental to numerous scientific applications. Traditional hash-based approaches fail to strike a trade-off between reducing hash collisions ...