21 citations · 117 across the 15 of their papers we have counts for
15 papers
Kronecker Products, Polarity Quotients and Large Graph Constructions
Kelly Isham, Kartik Lakhotia, Laura Monroe +1
In this paper, we establish a structural compatibility between the Kronecker product of bipartite graphs that admit polarity and their polarity quotients, and provide a sharp upper…
PCCL: Process Group-Aware Scalable and Generic Collective Algorithm Synthesizer
William Won, Kartik Lakhotia, Madhu Kumar +2
Distributed machine learning has become increasingly important due to the massive scale of large-scale generative models. Both model parameters and data are distributed across many…
Edge-Disjoint Spanning Trees on Star-Product Networks
Kelly Isham, Laura Monroe, Kartik Lakhotia +3
A star-product operation may be used to create large graphs from smaller factor graphs. Network topologies based on star-products demonstrate several advantages including low-diame…
A High-Performance Design, Implementation, Deployment, and Evaluation of The Slim Fly Network
Nils Blach, Maciej Besta, Daniele De Sensi +10
Novel low-diameter network topologies such as Slim Fly (SF) offer significant cost and power advantages over the established Fat Tree, Clos, or Dragonfly. To spearhead the adoption…
PolarStar: Expanding the Scalability Horizon of Diameter-3 Networks
Kartik Lakhotia, Laura Monroe, Kelly Isham +4
We present PolarStar, a novel family of diameter-3 network topologies derived from the star product of low-diameter factor graphs. PolarStar gives the largest known diameter-3 netw…
PolarFly: A Cost-Effective and Flexible Low-Diameter Topology
Kartik Lakhotia, Maciej Besta, Laura Monroe +4
In this paper we present PolarFly, a diameter-2 network topology based on the Erdos-Renyi family of polarity graphs from finite geometry. This is a highly scalable low-diameter top…
Design and Implementation of Knowledge Base for Runtime Management of Software Defined Hardware
Hongkuan Zhou, Ajitesh Srivastava, Rajgopal Kannan +1
Runtime-reconfigurable software coupled with reconfigurable hardware is highly desirable as a means towards maximizing runtime efficiency without compromising programmability. Comp…
Parallel Peeling of Bipartite Networks for Hierarchical Dense Subgraph Discovery
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna
Wing and Tip decomposition construct a hierarchy of butterfly-dense edge and vertex induced bipartite subgraphs, respectively. They have applications in several domains including e…
EvalNet: A Practical Toolchain for Generation and Analysis of Extreme-Scale Interconnects
Maciej Besta, Patrick Iff, Marcel Schneider +10
The diversity of communication paths in a network, especially non-minimal paths, is a key enabler of performance at extreme scales. We present EvalNet, a toolchain for scalable gen…
RECEIPT: REfine CoarsE-grained IndePendent Tasks for Parallel Tip decomposition of Bipartite Graphs
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna +1
Tip decomposition is a crucial kernel for mining dense subgraphs in bipartite networks, with applications in spam detection, analysis of affiliation networks etc. It creates a hier…
SPEC2: SPECtral SParsE CNN Accelerator on FPGAs
Yue Niu, Hanqing Zeng, Ajitesh Srivastava +4
To accelerate inference of Convolutional Neural Networks (CNNs), various techniques have been proposed to reduce computation redundancy. Converting convolutional layers into freque…
Approximation Algorithms for Coordinating Ad Campaigns on Social Networks
Kartik Lakhotia, David Kempe
We study a natural model of coordinated social ad campaigns over a social network, based on models of Datta et al. and Aslay et al. Multiple advertisers are willing to pay the host…
Planting Trees for scalable and efficient Canonical Hub Labeling
Kartik Lakhotia, Qing Dong, Rajgopal Kannan +1
Point-to-Point Shortest Distance (PPSD) query is a crucial primitive in graph database applications. Hub labeling algorithms compute a labeling that converts a PPSD query into a li…
GPOP: A cache- and work-efficient framework for Graph Processing Over Partitions
Kartik Lakhotia, Sourav Pati, Rajgopal Kannan +1
Past decade has seen the development of many shared-memory graph processing frameworks, intended to reduce the effort of developing high performance parallel applications. However…
Accelerating PageRank using Partition-Centric Processing
Kartik Lakhotia, Rajgopal Kannan, Viktor Prasanna
PageRank is a fundamental link analysis algorithm that also functions as a key representative of the performance of Sparse Matrix-Vector (SpMV) multiplication. The traditional Page…