187 citations · 1k across the 59 of their papers we have counts for
10 papers · 1 filter
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…
Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale
Md Taufique Hussain, Oguz Selvitopi, Aydin Buluç +1
Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in various graph, scientific computing and machine learning algorithms. In this paper, we consider SpGEMMs perf…
Distributed Many-to-Many Protein Sequence Alignment using Sparse Matrices
Oguz Selvitopi, Saliya Ekanayake, Giulia Guidi +3
Identifying similar protein sequences is a core step in many computational biology pipelines such as detection of homologous protein sequences, generation of similarity protein gra…
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…