18 citations · 22 across the 2 of their papers we have counts for
8 papers
Delayed Asynchronous Iterative Graph Algorithms
Mark P. Blanco, Scott McMillan, Tze Meng Low
Iterative graph algorithms often compute intermediate values and update them as computation progresses. Updated output values are used as inputs for computations in current or subs…
Exploration of Fine-Grained Parallelism for Load Balancing Eager K-truss on GPU and CPU
Mark Blanco, Tze Meng Low, Kyungjoo Kim
In this work we present a performance exploration on Eager K-truss, a linear-algebraic formulation of the K-truss graph algorithm. We address performance issues related to load imb…
Delta-stepping SSSP: from Vertices and Edges to GraphBLAS Implementations
Upasana Sridhar, Mark Blanco, Rahul Mayuranath +3
GraphBLAS is an interface for implementing graph algorithms. Algorithms implemented using the GraphBLAS interface are cast in terms of linear algebra-like operations. However, many…
A Flexible Framework for Parallel Multi-Dimensional DFTs
Doru Thom Popovici, Martin D. Schatz, Franz Franchetti +1
Multi-dimensional discrete Fourier transforms (DFT) are typically decomposed into multiple 1D transforms. Hence, parallel implementations of any multi-dimensional DFT focus on para…
CodeNet: Training Large Scale Neural Networks in Presence of Soft-Errors
Sanghamitra Dutta, Ziqian Bai, Tze Meng Low +1
This work proposes the first strategy to make distributed training of neural networks resilient to computing errors, a problem that has remained unsolved despite being first posed…
A Unified Coded Deep Neural Network Training Strategy Based on Generalized PolyDot Codes for Matrix Multiplication
Sanghamitra Dutta, Ziqian Bai, Haewon Jeong +2
This paper has two contributions. First, we propose a novel coded matrix multiplication technique called Generalized PolyDot codes that advances on existing methods for coded matri…