3 citations · 5 across the 6 of their papers we have counts for
7 papers
GTrans: Spatiotemporal Autoregressive Transformer with Graph Embeddings for Nowcasting Extreme Events
Bo Feng, Geoffrey Fox
Spatiotemporal time series nowcasting should preserve temporal and spatial dynamics in the sense that generated new sequences from models respect the covariance relationship from h…
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems
Steven Farrell, Murali Emani, Jacob Balma +40
Scientific communities are increasingly adopting machine learning and deep learning models in their applications to accelerate scientific insights. High performance computing syste…
Scientific Machine Learning Benchmarks
Jeyan Thiyagalingam, Mallikarjun Shankar, Geoffrey Fox +1
The breakthrough in Deep Learning neural networks has transformed the use of AI and machine learning technologies for the analysis of very large experimental datasets. These datase…
HPTMT Parallel Operators for High Performance Data Science & Data Engineering
Vibhatha Abeykoon, Supun Kamburugamuve, Chathura Widanage +5
Data-intensive applications are becoming commonplace in all science disciplines. They are comprised of a rich set of sub-domains such as data engineering, deep learning, and machin…
HPTMT: Operator-Based Architecture for Scalable High-Performance Data-Intensive Frameworks
Supun Kamburugamuve, Chathura Widanage, Niranda Perera +5
Data-intensive applications impact many domains, and their steadily increasing size and complexity demands high-performance, highly usable environments. We integrate a set of ideas…
Understanding ML driven HPC: Applications and Infrastructure
Geoffrey Fox, Shantenu Jha
We recently outlined the vision of "Learning Everywhere" which captures the possibility and impact of how learning methods and traditional HPC methods can be coupled together. A pr…