2 code implementations • 7 May 2020 • Alok Tripathy, Katherine Yelick, Aydin Buluc
Graph Neural Networks (GNNs) are powerful and flexible neural networks that use the naturally sparse connectivity information of the data.
1 code implementation • 12 Feb 2020 • Alberto Zeni, Giulia Guidi, Marquita Ellis, Nan Ding, Marco D. Santambrogio, Steven Hofmeyr, Aydın Buluç, Leonid Oliker, Katherine Yelick
To highlight the impact of our work on a real-world application, we couple LOGAN with a many-to-many long-read alignment software called BELLA, and demonstrate that our implementation improves the overall BELLA runtime by up to 10. 6x.
3 code implementations • 9 Mar 2020 • Ed Younis, Koushik Sen, Katherine Yelick, Costin Iancu
We present QFAST, a quantum synthesis tool designed to produce short circuits and to scale well in practice.
Quantum Physics
3 code implementations • 20 Oct 2020 • Giulia Guidi, Oguz Selvitopi, Marquita Ellis, Leonid Oliker, Katherine Yelick, Aydin Buluc
In this work, we introduce new distributed-memory parallel algorithms for overlap detection and layout simplification steps of de novo genome assembly, and implement them in the diBELLA 2D pipeline.
Distributed, Parallel, and Cluster Computing Genomics
1 code implementation • 30 Oct 2017 • Penporn Koanantakool, Alnur Ali, Ariful Azad, Aydin Buluc, Dmitriy Morozov, Leonid Oliker, Katherine Yelick, Sang-Yun Oh
Across a variety of scientific disciplines, sparse inverse covariance estimation is a popular tool for capturing the underlying dependency relationships in multivariate data.
no code implementations • 6 Apr 2016 • Vasant G. Honavar, Mark D. Hill, Katherine Yelick
The emergence of "big data" offers unprecedented opportunities for not only accelerating scientific advances but also enabling new modes of discovery.
no code implementations • 30 Oct 2020 • Nicolas Swenson, Aditi S. Krishnapriyan, Aydin Buluc, Dmitriy Morozov, Katherine Yelick
Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries.
Graph Representation Learning Protein Function Prediction +1
no code implementations • 6 Nov 2023 • Alok Tripathy, Katherine Yelick, Aydin Buluc
We provide experimental results on the largest Open Graph Benchmark (OGB) datasets on $128$ GPUs, and show that our pipeline is $2. 5\times$ faster than Quiver (a distributed extension to PyTorch-Geometric) on a $3$-layer GraphSAGE network.