11 citations · 26 across the 18 of their papers we have counts for
4 papers · 1 filter
pyGinkgo: A Sparse Linear Algebra Operator Framework for Python
Keshvi Tuteja, Gregor Olenik, Roman Mishchuk +5
Sparse linear algebra is a cornerstone of many scientific computing and machine learning applications. Python has become a popular choice for these applications due to its simplici…
Energy Consumption in Parallel Neural Network Training
Philipp Huber, David Li, Juan Pedro Gutiérrez Hermosillo Muriedas +4
The increasing demand for computational resources of training neural networks leads to a concerning growth in energy consumption. While parallelization has enabled upscaling model…
Jigsaw: Training Multi-Billion-Parameter AI Weather Models with Optimized Model Parallelism
Deifilia Kieckhefen, Markus Götz, Lars H. Heyen +2
AI-based methods have revolutionized atmospheric forecasting, with recent successes in medium-range forecasting spurring the development of climate foundation models. Accurate mode…
Model Fusion via Neuron Transplantation
Muhammed Öz, Nicholas Kiefer, Charlotte Debus +3
Ensemble learning is a widespread technique to improve the prediction performance of neural networks. However, it comes at the price of increased memory and inference time. In this…