16 citations · 18 across the 5 of their papers we have counts for
5 papers
MPIrigen: MPI Code Generation through Domain-Specific Language Models
Nadav Schneider, Niranjan Hasabnis, Vy A. Vo +9
The imperative need to scale computation across numerous nodes highlights the significance of efficient parallel computing, particularly in the realm of Message Passing Interface (…
MonoCoder: Domain-Specific Code Language Model for HPC Codes and Tasks
Tal Kadosh, Niranjan Hasabnis, Vy A. Vo +10
With easier access to powerful compute resources, there is a growing trend in AI for software development to develop large language models (LLMs) to address a variety of programmin…
Scope is all you need: Transforming LLMs for HPC Code
Tal Kadosh, Niranjan Hasabnis, Vy A. Vo +9
With easier access to powerful compute resources, there is a growing trend in the field of AI for software development to develop larger and larger language models (LLMs) to addres…
Silhouette: Toward Performance-Conscious and Transferable CPU Embeddings
Tarikul Islam Papon, Abdul Wasay
Learned embeddings are widely used to obtain concise data representation and enable transfer learning between different data sets and tasks. In this paper, we present Silhouette, o…
MotherNets: Rapid Deep Ensemble Learning
Abdul Wasay, Brian Hentschel, Yuze Liao +2
Ensembles of deep neural networks significantly improve generalization accuracy. However, training neural network ensembles requires a large amount of computational resources and t…