7 papers
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…
Efficient Dynamic MaxFlow Computation on GPUs
Shruthi Kannappan, Ashwina Kumar, Rupesh Nasre
Maxflow is a fundamental problem in graph theory and combinatorial optimisation, used to determine the maximum flow from a source node to a sink node in a flow network. It finds ap…
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…
Host-Based Allocators for Device Memory
Oren Bell, Ashwin Kumar, Chris Gill
Memory allocation is a fairly mature field of computer science. However, we challenge a prevailing assumption in the literature over the last 50 years which, if reconsidered, neces…
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…
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…