16 citations · 41 across the 6 of their papers we have counts for
6 papers
Accelerating a Triton Fused Kernel for W4A16 Quantized Inference with SplitK work decomposition
Adnan Hoque, Less Wright, Chih-Chieh Yang +2
We propose an implementation of an efficient fused matrix multiplication kernel for W4A16 quantized inference, where we perform dequantization and GEMM in a fused kernel using a Sp…
SudokuSens: Enhancing Deep Learning Robustness for IoT Sensing Applications using a Generative Approach
Tianshi Wang, Jinyang Li, Ruijie Wang +7
This paper introduces SudokuSens, a generative framework for automated generation of training data in machine-learning-based Internet-of-Things (IoT) applications, such that the ge…
TP-Aware Dequantization
Adnan Hoque, Mudhakar Srivatsa, Chih-Chieh Yang +1
In this paper, we present a novel method that reduces model inference latency during distributed deployment of Large Language Models (LLMs). Our contribution is an optimized infere…
Foundation Models for Generalist Geospatial Artificial Intelligence
Johannes Jakubik, Sujit Roy, C. E. Phillips +30
Significant progress in the development of highly adaptable and reusable Artificial Intelligence (AI) models is expected to have a significant impact on Earth science and remote se…
AI Foundation Models for Weather and Climate: Applications, Design, and Implementation
S. Karthik Mukkavilli, Daniel Salles Civitarese, Johannes Schmude +12
Machine learning and deep learning methods have been widely explored in understanding the chaotic behavior of the atmosphere and furthering weather forecasting. There has been incr…
Beyond Spatial Auto-Regressive Models: Predicting Housing Prices with Satellite Imagery
Archith J. Bency, Swati Rallapalli, Raghu K. Ganti +2
When modeling geo-spatial data, it is critical to capture spatial correlations for achieving high accuracy. Spatial Auto-Regression (SAR) is a common tool used to model such data,…