64 citations · 121 across the 10 of their papers we have counts for
12 papers
RESOLVE: Language-Agnostic Validation of GPU Kernels Through Testing, Reduction, and Proof
Ashkan Vedadi Gargary, Guido Martínez, Sebastian Burckhardt +4
AI systems can now write and optimize production GPU kernels, but validating them remains an important challenge. Evaluating the kernel on a few random inputs and checking that its…
Towards Generating Functionally Correct Code Edits from Natural Language Issue Descriptions
Sarah Fakhoury, Saikat Chakraborty, Madan Musuvathi +1
Large language models (LLMs), such as OpenAI's Codex, have demonstrated their potential to generate code from natural language descriptions across a wide range of programming tasks…
Interactive Code Generation via Test-Driven User-Intent Formalization
Shuvendu K. Lahiri, Sarah Fakhoury, Aaditya Naik +8
Large language models (LLMs) have shown great potential in automating significant aspects of coding by producing natural code from informal natural language (NL) intent. However, w…
GC3: An Optimizing Compiler for GPU Collective Communication
Meghan Cowan, Saeed Maleki, Madanlal Musuvathi +2
Machine learning models made up of millions or billions of parameters are trained and served on large multi-GPU systems. As models grow in size and execute on more GPUs, the collec…
Breaking the Computation and Communication Abstraction Barrier in Distributed Machine Learning Workloads
Abhinav Jangda, Jun Huang, Guodong Liu +6
Recent trend towards increasing large machine learning models require both training and inference tasks to be distributed. Considering the huge cost of training these models, it is…
GenderRobustness: Robustness of Gender Detection in Facial Recognition Systems with variation in Image Properties
Sharadha Srinivasan, Madan Musuvathi
In recent times, there have been increasing accusations on artificial intelligence systems and algorithms of computer vision of possessing implicit biases. Even though these conver…