12 papers
Unstructured Hydrodynamics on Spatial Dataflow Architectures: A Joint Code and Data Decomposition Approach
Piotr Luczynski, Tal Ben-Nun, Leighton Wilson +1
Spatial Dataflow Architectures are an emerging hardware pattern in high-performance computing, whose mesh-connected fixed-memory processing elements are tailored for structured gri…
SpaDA: A Spatial Dataflow Architecture Programming Language
Lukas Gianinazzi, Tal Ben-Nun, Torsten Hoefler
Spatial dataflow architectures like the Cerebras Wafer-Scale Engine deliver exceptional performance in AI and scientific computing by distributing scratchpad memory across hundreds…
LongCoT: Benchmarking Long-Horizon Chain-of-Thought Reasoning
Sumeet Ramesh Motwani, Daniel Nichols, Charles London +17
As language models are increasingly deployed for complex autonomous tasks, their ability to reason accurately over longer horizons becomes critical. An essential component of this…
Record-Remix-Replay: Hierarchical GPU Kernel Optimization using Evolutionary Search
Daniel Nichols, Konstantinos Parasyris, Caetano Melone +3
As high-performance computing and AI workloads become increasingly dependent on GPUs, maintaining high performance across rapidly evolving hardware generations has become a major c…
BOOM: Benchmarking Out-Of-distribution Molecular Property Predictions of Machine Learning Models
Evan R. Antoniuk, Shehtab Zaman, Tal Ben-Nun +9
Data-driven molecular discovery leverages artificial intelligence/machine learning (AI/ML) and generative modeling to filter and design novel molecules. Discovering novel molecules…
Trajectory Balance with Asynchrony: Decoupling Exploration and Learning for Fast, Scalable LLM Post-Training
Brian Bartoldson, Siddarth Venkatraman, James Diffenderfer +7
Reinforcement learning (RL) is a critical component of large language model (LLM) post-training. However, on-policy algorithms used for post-training are not naturally robust to a…