438 citations · 912 across the 6 of their papers we have counts for
9 papers
Coloring Big Graphs with AlphaGoZero
Jiayi Huang, Mostofa Patwary, Gregory Diamos
We show that recent innovations in deep reinforcement learning can effectively color very large graphs -- a well-known NP-hard problem with clear commercial applications. Because t…
Language Modeling at Scale
Mostofa Patwary, Milind Chabbi, Heewoo Jun +3
We show how Zipf's Law can be used to scale up language modeling (LM) to take advantage of more training data and more GPUs. LM plays a key role in many important natural language…
Deep Learning Scaling is Predictable, Empirically
Joel Hestness, Sharan Narang, Newsha Ardalani +6
Deep learning (DL) creates impactful advances following a virtuous recipe: model architecture search, creating large training data sets, and scaling computation. It is widely belie…
Galactos: Computing the Anisotropic 3-Point Correlation Function for 2 Billion Galaxies
Brian Friesen, Md. Mostofa Ali Patwary, Brian Austin +8
The nature of dark energy and the complete theory of gravity are two central questions currently facing cosmology. A vital tool for addressing them is the 3-point correlation funct…
A New Parallel Algorithm for Two-Pass Connected Component Labeling
Siddharth Gupta, Diana Palsetia, Md. Mostofa Ali Patwary +2
Connected Component Labeling (CCL) is an important step in pattern recognition and image processing. It assigns labels to the pixels such that adjacent pixels sharing the same feat…
GraphMat: High performance graph analytics made productive
Narayanan Sundaram, Nadathur Rajagopalan Satish, Md Mostofa Ali Patwary +4
Given the growing importance of large-scale graph analytics, there is a need to improve the performance of graph analysis frameworks without compromising on productivity. GraphMat…