4 citations · 6 across the 13 of their papers we have counts for
10 papers · 1 filter
HARP-ME: Closure-Driven Exact Induced Motif Enumeration on GPUs
Ashwina Kumar, Rupesh Nasre
Exact induced motif enumeration is a fundamental operation in graph mining, but it remains challenging on GPUs because candidate expansion is irregular, repeated set intersections…
StarDist: A Code Generator for Distributed Graph Algorithms
Barenya Kumar Nandy, Rupesh Nasre
We introduce StarDist, a Domain Specific Language for generating high-performant distributed graph algorithms in the message passing model. Our analysis-transformation framework op…
Scalable Maxflow Processing for Dynamic Graphs
Shruthi Kannappan, Ashwina Kumar, Rupesh Nasre
The Maximum Flow (Max-Flow) problem is a cornerstone in graph theory and combinatorial optimization, aiming to determine the largest possible flow from a designated source node to…
Generating Dynamic Graph Algorithms for Multiple Backends for a Graph DSL
Nibedita Behera, Ashwina Kumar, Atharva Chougule +3
With the rapid growth of unstructured and semistructured data, parallelizing graph algorithms has become essential for efficiency. However, due to the inherent irregularity in comp…
Code Generation for a Variety of Accelerators for a Graph DSL
Ashwina Kumar, M. Venkata Krishna, Prasanna Bartakke +4
Sparse graphs are ubiquitous in real and virtual worlds. With the phenomenal growth in semi-structured and unstructured data, sizes of the underlying graphs have witnessed a rapid…
Meerkat: A framework for Dynamic Graph Algorithms on GPUs
Kevin Jude Concessao, Unnikrishnan Cheramangalath, MJ Ricky Dev +1
Graph algorithms are challenging to implement due to their varying topology and irregular access patterns. Real-world graphs are dynamic in nature and routinely undergo edge and ve…
StarPlat: A Versatile DSL for Graph Analytics
Nibedita Behera, Ashwina Kumar, Ebenezer Rajadurai T +3
Graphs model several real-world phenomena. With the growth of unstructured and semi-structured data, parallelization of graph algorithms is inevitable. Unfortunately, due to inhere…
A Fine-Grained Hybrid CPU-GPU Algorithm for Betweenness Centrality Computations
Ashirbad Mishra, Sathish Vadhiyar, Rupesh Nasre +1
Betweenness centrality (BC) is an important graph analytical application for large-scale graphs. While there are many efforts for parallelizing betweenness centrality algorithms on…
GPU Algorithm for Earliest Arrival Time Problem in Public Transport Networks
Chirayu Anant Haryan, G. Ramakrishna, Rupesh Nasre +1
Given a temporal graph G, a source vertex s, and a departure time at source vertex t_s, the earliest arrival time problem EAT is to start from s on or after t_s and reach all the v…
Dynamic Load Balancing Strategies for Graph Applications on GPUs
Ananya Raval, Rupesh Nasre, Vivek Kumar +3
Acceleration of graph applications on GPUs has found large interest due to the ubiquitous use of graph processing in various domains. The inherent \textit{irregularity} in graph ap…