8 citations · 24 across the 5 of their papers we have counts for
5 papers
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies
Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang +89
In the upcoming decade, deep learning may revolutionize the natural sciences, enhancing our capacity to model and predict natural occurrences. This could herald a new era of scient…
A Comprehensive Performance Study of Large Language Models on Novel AI Accelerators
Murali Emani, Sam Foreman, Varuni Sastry +6
Artificial intelligence (AI) methods have become critical in scientific applications to help accelerate scientific discovery. Large language models (LLMs) are being considered as a…
Parallel Multi-Objective Hyperparameter Optimization with Uniform Normalization and Bounded Objectives
Romain Egele, Tyler Chang, Yixuan Sun +2
Machine learning (ML) methods offer a wide range of configurable hyperparameters that have a significant influence on their performance. While accuracy is a commonly used performan…
A Survey of Techniques for Optimizing Transformer Inference
Krishna Teja Chitty-Venkata, Sparsh Mittal, Murali Emani +2
Recent years have seen a phenomenal rise in performance and applications of transformer neural networks. The family of transformer networks, including Bidirectional Encoder Represe…
Operation-Level Performance Benchmarking of Graph Neural Networks for Scientific Applications
Ryien Hosseini, Filippo Simini, Venkatram Vishwanath
As Graph Neural Networks (GNNs) increase in popularity for scientific machine learning, their training and inference efficiency is becoming increasingly critical. Additionally, the…