Malith Jayaweera

Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search

Though recent years have witnessed remarkable progress in single image super-resolution (SISR) tasks with the prosperous development of deep neural networks (DNNs), the deep learning methods are...

AXI4MLIR: User-Driven Automatic Host Code Generation for Custom AXI-Based Accelerators

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 important workload in...

Achieving on-Mobile Real-Time Super-Resolution with Neural Architecture and Pruning Search

DEFCON: Deformable Convolutions Leveraging Interval Search and GPU Texture Hardware

NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator

Energy-Aware Tile Size Selection for Affine Programs on GPUs

Reducing Unfairness in Distributed Community Detection

Unfairness in Distributed Graph Frameworks

Enhanced Real-Time Machine Inspection with Mobile Augmented Reality for Maintenance and Repair: Demo Abstract

JAXED: Reverse Engineering DNN Architectures Leveraging JIT GEMM Libraries

NeuraChip: Accelerating GNN Computations with a Hash-based Decoupled Spatial Accelerator

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. Despite their...