research
∙
08/16/2023
Accelerating Generic Graph Neural Networks via Architecture, Compiler, Partition Method Co-Design
Graph neural networks (GNNs) have shown significant accuracy improvement...
share
research
∙
05/27/2023
AdaptGear: Accelerating GNN Training via Adaptive Subgraph-Level Kernels on GPUs
Graph neural networks (GNNs) are powerful tools for exploring and learni...
research
∙
08/25/2022
Efficient Activation Quantization via Adaptive Rounding Border for Post-Training Quantization
Post-training quantization (PTQ) attracts increasing attention due to it...
research
∙
10/08/2021
Characterizing and Demystifying the Implicit Convolution Algorithm on Commercial Matrix-Multiplication Accelerators
Many of today's deep neural network accelerators, e.g., Google's TPU and...
research
∙
02/18/2020
