2 citations · 4 across the 3 of their papers we have counts for
3 papers
NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator
Kaustubh Shivdikar, Nicolas Bohm Agostini, Malith Jayaweera +5
Graph Neural Networks (GNNs) are emerging as a formidable tool for processing non-euclidean data across various domains, ranging from social network analysis to bioinformatics. Des…
Flexagon: A Multi-Dataflow Sparse-Sparse Matrix Multiplication Accelerator for Efficient DNN Processing
Francisco Muñoz-Martínez, Raveesh Garg, José L. Abellán +3
Sparsity is a growing trend in modern DNN models. Existing Sparse-Sparse Matrix Multiplication (SpMSpM) accelerators are tailored to a particular SpMSpM dataflow (i.e., Inner Produ…
Accelerating Polynomial Multiplication for Homomorphic Encryption on GPUs
Kaustubh Shivdikar, Gilbert Jonatan, Evelio Mora +6
Homomorphic Encryption (HE) enables users to securely outsource both the storage and computation of sensitive data to untrusted servers. Not only does HE offer an attractive soluti…