45 citations · 144 across the 35 of their papers we have counts for
11 papers · 1 filter
HPC-Coder-V2: Studying Code LLMs Across Low-Resource Parallel Languages
Aman Chaturvedi, Daniel Nichols, Siddharth Singh +1
Large Language Model (LLM) based coding tools have been tremendously successful as software development assistants, yet they are often designed for general purpose programming task…
From Pixels to Prose: A Large Dataset of Dense Image Captions
Vasu Singla, Kaiyu Yue, Sukriti Paul +7
Training large vision-language models requires extensive, high-quality image-text pairs. Existing web-scraped datasets, however, are noisy and lack detailed image descriptions. To…
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs
Abhimanyu Hans, Yuxin Wen, Neel Jain +8
Large language models can memorize and repeat their training data, causing privacy and copyright risks. To mitigate memorization, we introduce a subtle modification to the next-tok…
Loki: Low-rank Keys for Efficient Sparse Attention
Prajwal Singhania, Siddharth Singh, Shwai He +2
Inference on large language models (LLMs) can be expensive in terms of the compute and memory costs involved, especially when long sequence lengths are used. In particular, the sel…
Transformers Can Do Arithmetic with the Right Embeddings
Sean McLeish, Arpit Bansal, Alex Stein +8
The poor performance of transformers on arithmetic tasks seems to stem in large part from their inability to keep track of the exact position of each digit inside of a large span o…
Performance-Aligned LLMs for Generating Fast Code
Daniel Nichols, Pranav Polasam, Harshitha Menon +3
Optimizing scientific software is a difficult task because codebases are often large and complex, and performance can depend upon several factors including the algorithm, its imple…
Taking GPU Programming Models to Task for Performance Portability
Joshua H. Davis, Pranav Sivaraman, Joy Kitson +5
Portability is critical to ensuring high productivity in developing and maintaining scientific software as the diversity in on-node hardware architectures increases. While several…
Automated Programmatic Performance Analysis of Parallel Programs
Onur Cankur, Aditya Tomar, Daniel Nichols +3
Developing efficient parallel applications is critical to advancing scientific development but requires significant performance analysis and optimization. Performance analysis tool…
ML-based Modeling to Predict I/O Performance on Different Storage Sub-systems
Yiheng Xu, Pranav Sivaraman, Hariharan Devarajan +2
Parallel applications can spend a significant amount of time performing I/O on large-scale supercomputers. Fast near-compute storage accelerators called burst buffers can reduce th…
Can Large Language Models Write Parallel Code?
Daniel Nichols, Joshua H. Davis, Zhaojun Xie +2
Large language models are increasingly becoming a popular tool for software development. Their ability to model and generate source code has been demonstrated in a variety of conte…
Pandemics In Silico: Scaling an Agent-Based Simulation on Realistic Social Contact Networks
Joy Kitson, Ian Costello, Jiangzhuo Chen +7
Preventing the spread of infectious diseases requires implementing interventions at various levels of government and evaluating the potential impact and efficacy of those preemptiv…