24 citations · 58 across the 50 of their papers we have counts for
10 papers · 1 filter
MassiveGNN: Efficient Training via Prefetching for Massively Connected Distributed Graphs
Aishwarya Sarkar, Sayan Ghosh, Nathan R. Tallent +1
Graph Neural Networks (GNN) are indispensable in learning from graph-structured data, yet their rising computational costs, especially on massively connected graphs, pose significa…
CodeRosetta: Pushing the Boundaries of Unsupervised Code Translation for Parallel Programming
Ali TehraniJamsaz, Arijit Bhattacharjee, Le Chen +3
Recent advancements in Large Language Models (LLMs) have renewed interest in automatic programming language translation. Encoder-decoder transformer models, in particular, have sho…
MIREncoder: Multi-modal IR-based Pretrained Embeddings for Performance Optimizations
Akash Dutta, Ali Jannesari
One of the primary areas of interest in High Performance Computing is the improvement of performance of parallel workloads. Nowadays, compilable source code-based optimization task…
PipeInfer: Accelerating LLM Inference using Asynchronous Pipelined Speculation
Branden Butler, Sixing Yu, Arya Mazaheri +1
Inference of Large Language Models (LLMs) across computer clusters has become a focal point of research in recent times, with many acceleration techniques taking inspiration from C…
Benchmarking LLMs for Environmental Review and Permitting
Rounak Meyur, Hung Phan, Koby Hayashi +12
The National Environment Policy Act (NEPA) stands as a foundational piece of environmental legislation in the United States, requiring federal agencies to consider the environmenta…
Static Generation of Efficient OpenMP Offload Data Mappings
Luke Marzen, Akash Dutta, Ali Jannesari
Increasing heterogeneity in HPC architectures and compiler advancements have led to OpenMP being frequently used to enable computations on heterogeneous devices. However, the effic…
SAM-I-Am: Semantic Boosting for Zero-shot Atomic-Scale Electron Micrograph Segmentation
Waqwoya Abebe, Jan Strube, Luanzheng Guo +5
Image segmentation is a critical enabler for tasks ranging from medical diagnostics to autonomous driving. However, the correct segmentation semantics - where are boundaries locate…
FLoRA: Enhancing Vision-Language Models with Parameter-Efficient Federated Learning
Duy Phuong Nguyen, J. Pablo Munoz, Ali Jannesari
In the rapidly evolving field of artificial intelligence, multimodal models, e.g., integrating vision and language into visual-language models (VLMs), have become pivotal for many…
The Landscape and Challenges of HPC Research and LLMs
Le Chen, Nesreen K. Ahmed, Akash Dutta +14
Recently, language models (LMs), especially large language models (LLMs), have revolutionized the field of deep learning. Both encoder-decoder models and prompt-based techniques ha…
OMPGPT: A Generative Pre-trained Transformer Model for OpenMP
Le Chen, Arijit Bhattacharjee, Nesreen Ahmed +4
Large language models (LLMs)such as ChatGPT have significantly advanced the field of Natural Language Processing (NLP). This trend led to the development of code-based large langua…