3 papers
cs.DC2024
Distributed Convolutional Neural Network Training on Mobile and Edge Clusters
Pranav Rama, Madison Threadgill, Andreas Gerstlauer
The training of deep and/or convolutional neural networks (DNNs/CNNs) is traditionally done on servers with powerful CPUs and GPUs. Recent efforts have emerged to localize machine…
cs.LG2024
A Survey of Distributed Learning in Cloud, Mobile, and Edge Settings
Madison Threadgill, Andreas Gerstlauer
In the era of deep learning (DL), convolutional neural networks (CNNs), and large language models (LLMs), machine learning (ML) models are becoming increasingly complex, demanding…
cs.AR2024
Efficient Approaches for GEMM Acceleration on Leading AI-Optimized FPGAs
Endri Taka, Dimitrios Gourounas, Andreas Gerstlauer +2
FPGAs are a promising platform for accelerating Deep Learning (DL) applications, due to their high performance, low power consumption, and reconfigurability. Recently, the leading…