3 citations · 3 across the 2 of their papers we have counts for
2 papers
cs.AR2024
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…
cs.PL2023★ 3 cited
AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators
Nicolas Bohm Agostini, Jude Haris, Perry Gibson +6
This paper addresses the need for automatic and efficient generation of host driver code for arbitrary custom AXI-based accelerators targeting linear algebra algorithms, an importa…