Acceleration of spiking neural networks in emerging multi-core and GPU architectures. - Mohammad Ashraf Bhuiyan; Vivek K. Pallipuram; Melissa C. Smith (IPDPS Workshops, 2010)

Optimization and performance study of large-scale biological networks for reconfigurable computing. - Mohammad Ashraf Bhuiyan; Ananth Nallamuthu; Melissa C. Smith; Vivek K. Pallipuram (HPRCTA@SC, 2010)

Performance, optimization, and fitness: Connecting applications to architectures. - Mohammad Ashraf Bhuiyan; Melissa C. Smith; Vivek K. Pallipuram (Concurr. Comput. Pract. Exp., 2011)

A comparative study of GPU programming models and architectures using neural networks. - Vivek K. Pallipuram; Mohammad Ashraf Bhuiyan; Melissa C. Smith (J. Supercomput., 2012)

Applying frequency analysis techniques to dag-based workflows to benchmark and predict resource behavior on non-dedicated clusters. - Vivek K. Pallipuram; Jeffrey DiMarco; Michela Taufer (CLUSTER, 2014)

A regression-based performance prediction framework for synchronous iterative algorithms on general purpose graphical processing unit clusters. - Vivek K. Pallipuram; Melissa C. Smith; Nimisha Raut; Xiaoyu Ren (Concurr. Comput. Pract. Exp., 2014)

From HPC Performance to Climate Modeling: Transforming Methods for HPC Predictions into Models of Extreme Climate Conditions. - Ryan McKinney; Vivek K. Pallipuram; Rodrigo Vargas; Michela Taufer (e-Science, 2015)

A Testing Engine for High-Performance and Cost-Effective Workflow Execution in the Cloud. - Vivek K. Pallipuram; Trilce Estrada; Michela Taufer (ICPP, 2015)

Subjective versus objective: classifying analytical models for productive heterogeneous performance prediction. - Vivek K. Pallipuram; Melissa C. Smith; Nilim Sarma; Ranajeet Anand; Edwin Weill; Karan Sapra (J. Supercomput., 2015)

A best-features based digital rotoscope. - Iain Murphy; Tyler Norlund; Vivek K. Pallipuram (ACSSC, 2017)

Data migration algorithms in heterogeneous storage systems: A comparative performance evaluation. - Gary Roberts; Sixia Chen; Chadi Kari; Vivek K. Pallipuram (NCA, 2017)

The Realm of Graphical Processing Unit (GPU) Computing. - Vivek K. Pallipuram; Jinzhu Gao (Topics in Parallel and Distributed Computing, 2018)

A2Cloud: An Analytical Model for Application-to-Cloud Matching to Empower Scientific Computing. - Cody J. Balos; David de la Vega; Zachariah Abuelhaj; Chadi Kari; David Mueller; Vivek K. Pallipuram (IEEE CLOUD, 2018)

Data Migration in Large Scale Heterogeneous Storage Systems with Nodes to Spare. - Chadi Kari; Sixia Chen; Sepehr Amir-Mohammadian; Vivek K. Pallipuram (ICNC, 2019)

A2Cloud-cc: A Machine Learning Council to Guide Cloud Resource Selection for Scientific Applications. - Lisa Her; Syeduzzaman Khan; David Samuel; Xusheng Ai; Sixia Chen; Vivek K. Pallipuram (NCA, 2020)

A2Cloud-RF: A random forest based statistical framework to guide resource selection for high-performance scientific computing on the cloud. - David Samuel; Syeduzzaman Khan; Cody J. Balos; Zachariah Abuelhaj; Anthony D. Dutoi; Chadi Kari; David Mueller; Vivek K. Pallipuram (Concurr. Comput. Pract. Exp., 2020)

True-Ed Select Enters Social Computing: A Machine Learning Based University Selection Framework. - Jerry Cearley; Vivek K. Pallipuram (FTC (3), 2022)