Search Results for author: Katherine Yelick

Found 7 papers, 4 papers with code

PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction

no code implementations30 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

Parallel String Graph Construction and Transitive Reduction for De Novo Genome Assembly

2 code implementations20 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

Reducing Communication in Graph Neural Network Training

2 code implementations7 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.

QFAST: Quantum Synthesis Using a Hierarchical Continuous Circuit Space

3 code implementations9 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

LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment

1 code implementation12 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.

Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation

no code implementations30 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.

Accelerating Science: A Computing Research Agenda

no code implementations6 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.

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