27 citations · 150 across the 20 of their papers we have counts for
25 papers
Distributed Matrix-Based Sampling for Graph Neural Network Training
Alok Tripathy, Katherine Yelick, Aydin Buluc
Graph Neural Networks (GNNs) offer a compact and computationally efficient way to learn embeddings and classifications on graph data. GNN models are frequently large, making distri…
Extreme-scale many-against-many protein similarity search
Oguz Selvitopi, Saliya Ekanayake, Giulia Guidi +7
Similarity search is one of the most fundamental computations that are regularly performed on ever-increasing protein datasets. Scalability is of paramount importance for uncoverin…
High-Performance Filters For GPUs
Hunter McCoy, Steven Hofmeyr, Katherine Yelick +1
Filters approximately store a set of items while trading off accuracy for space-efficiency and can address the limited memory on accelerators, such as GPUs. However, there is a lac…
Distributed-Memory Parallel Contig Generation for De Novo Long-Read Genome Assembly
Giulia Guidi, Gabriel Raulet, Daniel Rokhsar +3
De novo genome assembly, i.e., rebuilding the sequence of an unknown genome from redundant and erroneous short sequences, is a key but computationally intensive step in many genomi…
Atos: A Task-Parallel GPU Dynamic Scheduling Framework for Dynamic Irregular Computations
Yuxin Chen, Benjamin Brock, Serban Porumbescu +3
We present Atos, a task-parallel GPU dynamic scheduling framework that is especially suited to dynamic irregular applications. Compared to the dominant Bulk Synchronous Parallel (B…
QFAST: Conflating Search and Numerical Optimization for Scalable Quantum Circuit Synthesis
Ed Younis, Koushik Sen, Katherine Yelick +1
We present a quantum synthesis algorithm designed to produce short circuits and to scale well in practice. The main contribution is a novel representation of circuits able to encod…
10 Years Later: Cloud Computing is Closing the Performance Gap
Giulia Guidi, Marquita Ellis, Aydin Buluc +2
Can cloud computing infrastructures provide HPC-competitive performance for scientific applications broadly? Despite prolific related literature, this question remains open. Answer…
PersGNN: Applying Topological Data Analysis and Geometric Deep Learning to Structure-Based Protein Function Prediction
Nicolas Swenson, Aditi S. Krishnapriyan, Aydin Buluc +2
Understanding protein structure-function relationships is a key challenge in computational biology, with applications across the biotechnology and pharmaceutical industries. While…
Parallel String Graph Construction and Transitive Reduction for De Novo Genome Assembly
Giulia Guidi, Oguz Selvitopi, Marquita Ellis +3
One of the most computationally intensive tasks in computational biology is de novo genome assembly, the decoding of the sequence of an unknown genome from redundant and erroneous…
Opportunities and Challenges for Next Generation Computing
Gregory D. Hager, Mark D. Hill, Katherine Yelick
Computing has dramatically changed nearly every aspect of our lives, from business and agriculture to communication and entertainment. As a nation, we rely on computing in the desi…
Reducing Communication in Graph Neural Network Training
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. GNNs represent this connectivity as spars…
QFAST: Quantum Synthesis Using a Hierarchical Continuous Circuit Space
Ed Younis, Koushik Sen, Katherine Yelick +1
We present QFAST, a quantum synthesis tool designed to produce short circuits and to scale well in practice. Our contributions are: 1) a novel representation of circuits able to en…
LOGAN: High-Performance GPU-Based X-Drop Long-Read Alignment
Alberto Zeni, Giulia Guidi, Marquita Ellis +6
Pairwise sequence alignment is one of the most computationally intensive kernels in genomic data analysis, accounting for more than 90% of the runtime for key bioinformatics applic…
diBELLA: Distributed Long Read to Long Read Alignment
Marquita Ellis, Giulia Guidi, Aydın Buluç +2
We present a parallel algorithm and scalable implementation for genome analysis, specifically the problem of finding overlaps and alignments for data from "third generation" long r…
The Parallelism Motifs of Genomic Data Analysis
Katherine Yelick, Aydin Buluc, Muaaz Awan +11
Genomic data sets are growing dramatically as the cost of sequencing continues to decline and small sequencing devices become available. Enormous community databases store and shar…
RDMA vs. RPC for Implementing Distributed Data Structures
Benjamin Brock, Yuxin Chen, Jiakun Yan +3
Distributed data structures are key to implementing scalable applications for scientific simulations and data analysis. In this paper we look at two implementation styles for distr…
BCL: A Cross-Platform Distributed Container Library
Benjamin Brock, Aydın Buluç, Katherine Yelick
One-sided communication is a useful paradigm for irregular parallel applications, but most one-sided programming environments, including MPI's one-sided interface and PGAS programm…
Extreme Scale De Novo Metagenome Assembly
Evangelos Georganas, Rob Egan, Steven Hofmeyr +6
Metagenome assembly is the process of transforming a set of short, overlapping, and potentially erroneous DNA segments from environmental samples into the accurate representation o…
Communication-Avoiding Optimization Methods for Distributed Massive-Scale Sparse Inverse Covariance Estimation
Penporn Koanantakool, Alnur Ali, Ariful Azad +5
Across a variety of scientific disciplines, sparse inverse covariance estimation is a popular tool for capturing the underlying dependency relationships in multivariate data. Unfor…
Advanced Cyberinfrastructure for Science, Engineering, and Public Policy
Vasant G. Honavar, Katherine Yelick, Klara Nahrstedt +5
Progress in many domains increasingly benefits from our ability to view the systems through a computational lens, i.e., using computational abstractions of the domains; and our abi…
Extreme-Scale De Novo Genome Assembly
Evangelos Georganas, Steven Hofmeyr, Rob Egan +4
De novo whole genome assembly reconstructs genomic sequence from short, overlapping, and potentially erroneous DNA segments and is one of the most important computations in modern…
An Asynchronous Task-based Fan-Both Sparse Cholesky Solver
Mathias Jacquelin, Yili Zheng, Esmond Ng +1
Systems of linear equations arise at the heart of many scientific and engineering applications. Many of these linear systems are sparse; i.e., most of the elements in the coefficie…
Accelerating Science: A Computing Research Agenda
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. Scientific progress in many d…
On Holder-Brascamp-Lieb inequalities for torsion-free discrete Abelian groups
Michael Christ, James Demmel, Nicholas Knight +2
Hölder-Brascamp-Lieb inequalities provide upper bounds for a class of multilinear expressions, in terms of norms of the functions involved. They have been extensively studied…