Bayyapu Neelima

Orcid: 0000-0002-7201-2217

Affiliations:
  • NMAM Institute of Technology, Nitte, India


According to our database1, Bayyapu Neelima authored at least 13 papers between 2012 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
PDC Course Development and Assessment Process for the betterment of Teaching-Learning Process.
Proceedings of the 29th IEEE International Conference on High Performance Computing, 2022

Reinforcement Technique for Classifying Quasi and Non-quasi Attributes for Privacy Preservation and Data Protection.
Proceedings of the Applications and Techniques in Information Security, 2022

2018
Parallel computing for preserving privacy using k-anonymisation algorithms from big data.
Int. J. Big Data Intell., 2018

Privacy Preserving in Blockchain Based on Partial Homomorphic Encryption System for Ai Applications.
Proceedings of the 25th IEEE International Conference on High Performance Computing Workshops, 2018

Privacy preserving through aggregating wave equation as noise in differential privacy.
Proceedings of the 2018 International Conference on Data Science and Information Technology, 2018

2017
High Performance Computing education in an Indian engineering institute.
J. Parallel Distributed Comput., 2017

Kepler GPU accelerated recursive sorting using dynamic parallelism.
Concurr. Comput. Pract. Exp., 2017

2016
SWIFT-A Performance Accelerated Optimized String Matching Algorithm for Nvidia GPUs.
Proceedings of the 15th International Symposium on Parallel and Distributed Computing, 2016

2015
Communication and computation optimization of concurrent kernels using kernel coalesce on a GPU.
Concurr. Comput. Pract. Exp., 2015

Introducing high performance computing concepts into engineering undergraduate curriculum: a success story.
Proceedings of the Workshop on Education for High-Performance Computing, 2015

2014
A GPU Framework for Sparse Matrix Vector Multiplication.
Proceedings of the IEEE 13th International Symposium on Parallel and Distributed Computing, 2014

Predicting an Optimal Sparse Matrix Format for SpMV Computation on GPU.
Proceedings of the 2014 IEEE International Parallel & Distributed Processing Symposium Workshops, 2014

2012
New Sparse Matrix Storage Format to Improve The Performance of Total SPMV Time.
Scalable Comput. Pract. Exp., 2012


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