Ariful Azad | DeepAI

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∙ 05/17/2023

A Scalable Method for Readable Tree Layouts

Large tree structures are ubiquitous and real-world relational datasets ...

0 Kathryn Gray, et al. ∙

∙ 03/03/2023

Extreme-scale many-against-many protein similarity search

Similarity search is one of the most fundamental computations that are r...

0 Oguz Selvitopi, et al. ∙

∙ 08/06/2022

Triple Sparsification of Graph Convolutional Networks without Sacrificing the Accuracy

Graph Neural Networks (GNNs) are widely used to perform different machin...

0 Md. Khaledur Rahman, et al. ∙

∙ 05/04/2022

Graphical Games for UAV Swarm Control Under Time-Varying Communication Networks

We propose a unified framework for coordinating Unmanned Aerial Vehicle ...

0 Malintha Fernando, et al. ∙

∙ 02/05/2022

MarkovGNN: Graph Neural Networks on Markov Diffusion

Most real-world networks contain well-defined community structures where...

0 Md. Khaledur Rahman, et al. ∙

∙ 12/20/2021

A Comprehensive Analytical Survey on Unsupervised and Semi-Supervised Graph Representation Learning Methods

Graph representation learning is a fast-growing field where one of the m...

0 Md. Khaledur Rahman, et al. ∙

∙ 12/19/2021

Parallel Algorithms for Adding a Collection of Sparse Matrices

We develop a family of parallel algorithms for the SpKAdd operation that...

0 Md Taufique Hussain, et al. ∙

∙ 06/28/2021

Combinatorial BLAS 2.0: Scaling combinatorial algorithms on distributed-memory systems

Combinatorial algorithms such as those that arise in graph analysis, mod...

0 Ariful Azad, et al. ∙

∙ 04/07/2021

Bootstrapping Your Own Positive Sample: Contrastive Learning With Electronic Health Record Data

Electronic Health Record (EHR) data has been of tremendous utility in Ar...

14 Tingyi Wanyan, et al. ∙

∙ 12/28/2020

Deep Learning with Heterogeneous Graph Embeddings for Mortality Prediction from Electronic Health Records

Computational prediction of in-hospital mortality in the setting of an i...

1 Tingyi Wanyan, et al. ∙

∙ 11/07/2020

FusedMM: A Unified SDDMM-SpMM Kernel for Graph Embedding and Graph Neural Networks

We develop a fused matrix multiplication kernel that unifies sampled den...

0 Md. Khaledur Rahman, et al. ∙

∙ 10/16/2020

Communication-Avoiding and Memory-Constrained Sparse Matrix-Matrix Multiplication at Extreme Scale

Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in ...

0 Md Taufique Hussain, et al. ∙

∙ 09/30/2020

Distributed Many-to-Many Protein Sequence Alignment using Sparse Matrices

Identifying similar protein sequences is a core step in many computation...

0 Oguz Selvitopi, et al. ∙

∙ 09/23/2020

SubGraph2Vec: Highly-Vectorized Tree-likeSubgraph Counting

Subgraph counting aims to count occurrences of a template T in a given n...

0 Langshi Chen, et al. ∙

∙ 09/17/2020

Force2Vec: Parallel force-directed graph embedding

A graph embedding algorithm embeds a graph into a low-dimensional space ...

0 Md. Khaledur Rahman, et al. ∙

∙ 04/03/2020

Attribute2vec: Deep Network Embedding Through Multi-Filtering GCN

We present a multi-filtering Graph Convolution Neural Network (GCN) fram...

0 Tingyi Wanyan, et al. ∙

∙ 02/26/2020

Bandwidth-Optimized Parallel Algorithms for Sparse Matrix-Matrix Multiplication using Propagation Blocking

Sparse matrix-matrix multiplication (SpGEMM) is a widely used kernel in ...

0 Zhixiang Gu, et al. ∙

∙ 02/24/2020

Optimizing High Performance Markov Clustering for Pre-Exascale Architectures

HipMCL is a high-performance distributed memory implementation of the po...

0 Oguz Selvitopi, et al. ∙

∙ 02/11/2020

BatchLayout: A Batch-Parallel Force-Directed Graph Layout Algorithm in Shared Memory

Force-directed algorithms are widely used to generate aesthetically plea...

0 Md. Khaledur Rahman, et al. ∙

∙ 01/20/2020

The Parallelism Motifs of Genomic Data Analysis

Genomic data sets are growing dramatically as the cost of sequencing con...

0 Katherine Yelick, et al. ∙

∙ 10/14/2019

FastSV: A Distributed-Memory Connected Component Algorithm with Fast Convergence

This paper presents a new distributed-memory algorithm called FastSV for...

0 Yongzhe Zhang, et al. ∙

∙ 03/11/2019

A GraphBLAS Approach for Subgraph Counting

Subgraph counting aims to count the occurrences of a subgraph template T...

0 Langshi Chen, et al. ∙

∙ 04/05/2018

High-performance sparse matrix-matrix products on Intel KNL and multicore architectures

Sparse matrix-matrix multiplication (SpGEMM) is a computational primitiv...

0 Yusuke Nagasaka, et al. ∙

∙ 01/30/2018

A distributed-memory approximation algorithm for maximum weight perfect bipartite matching

We design and implement an efficient parallel approximation algorithm fo...

0 Ariful Azad, et al. ∙

∙ 12/12/2017

Integrated Model, Batch and Domain Parallelism in Training Neural Networks

We propose a new integrated method of exploiting model, batch and domain...

0 Amir Gholami, et al. ∙

∙ 12/12/2017

Integrated Model and Data Parallelism in Training Neural Networks

We propose a new integrated method of exploiting both model and data par...

0 Amir Gholami, et al. ∙

∙ 10/30/2017

Communication-Avoiding Optimization Methods for Massive-Scale Graphical Model Structure Learning

Undirected graphical models compactly represent the structure of large, ...

0 Penporn Koanantakool, et al. ∙

∙ 10/26/2016

The Reverse Cuthill-McKee Algorithm in Distributed-Memory

Ordering vertices of a graph is key to minimize fill-in and data structu...

0 Ariful Azad, et al. ∙

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