Raviteja Vangara, Erik Skau, Gopinath Chennupati, Hristo Djidjev, Thomas Tierney, James P. Smith, Manish Bhattarai, Valentin G. Stanev, Boian S. Alexandrov
(2020).
Semantic Nonnegative Matrix Factorization with Automatic Model Determination for Topic Modeling.
In: Proceedings of the 19th {IEEE} International Conference on Machine Learning and Applications, {ICMLA}, IEEE, pp. 328–335.
Yehia Arafa, Ammar ElWazir, Abdelrahman Elkanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel-Hameed A. Badawy, Gopinath Chennupati, Stephan J. Eidenbenz, Nandakishore Santhi
(2020).
NVIDIA GPGPUs Instructions Energy Consumption.
In Proceedings of the International Symposium on Performance Analysis of Systems and Software, {ISPASS}, 2020, IEEE, pp. 110–112.
Manish Bhattarai, Gopinath Chennupati, Erik Skau, Raviteja Vangara, Hristo Djidjev, Boian S. Alexandrov
(2020).
Distributed Non-Negative Tensor Train Decomposition.
In: Proceedings of the High Performance Extreme Computing Conference, {HPEC}, IEEE, pp. 1–10.
Hector Carrillo-Cabada, Erik Skau, Gopinath Chennupati, Boian S. Alexandrov, Hristo Djidjev
(2020).
An Out of Memory tSVD for Big-Data Factorization.
In: IEEE Access, IEEE, 2020, vol. 8 pp. 107749–107759.
Yehia Arafa, Ammar ElWazir, Abdelrahman ElKanishy, Youssef Aly, Ayatelrahman Elsayed, Abdel{-}Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
(2020).
Verified Instruction-Level Energy Consumption Measurement for NVIDIA GPUs.
In Proceedings of the 17th ACM International Conference on Computing Frontiers, ACM, pp. 60–70.
Sunil Thulasidasan, Tanmoy Bhattacharya, Jeffrey Bilmes, Gopinath Chennupati, Jamal Mohd-Yusof
(2019).
Combating Label Noise in Deep Learning Using Abstention.
In: International Conference on Machine Learning (ICML) pp. 6234–6243.
Yehia Arafa, Abdel{-}Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
(2019).
{POSTER:} GPUs Pipeline Latency Analysis.
In: 30th {IEEE} International Conference on Application-specific Systems, Architectures and Processors, {ASAP}, IEEE, pp. 139.
Y. Arafa, A. Badawy, G. Chennupati, N. Santhi, S. Eidenbenz
(2019).
PPT-GPU: Scalable GPU Performance Modeling.
In: IEEE Computer Architecture Letters, (18), 1, pp. 55–58.
Yehia Arafa, Abdel{-}Hameed A. Badawy, Gopinath Chennupati, Nandakishore Santhi, Stephan J. Eidenbenz
(2019).
GPUs Cache Performance Estimation using Reuse Distance Analysis.
In: 38th {IEEE} International Performance Computing and Communications Conference, {IPCCC}, IEEE, pp. 1–8.
Gopinath Chennupati, R.M.Atif Azad, Conor Ryan, Stephan Eidenbenz, Nandakumar Santhi
(2018).
Synthesis of Parallel Programs on Multi-Cores.
In: Handbook on Grammatical Evolution, Springer, pp. 289–315.
Patrick J Coles, Stephan Eidenbenz, Scott Pakin, Adetokunbo Adedoyin, John Ambrosiano, Petr Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo Djidjev, {others}
(2018).
Quantum Algorithm Implementations for Beginners.
In: arXiv preprint arXiv:1804.03719.
Nasrin Akhter, Gopinath Chennupati, Hristo Djidjev, Amarda Shehu
(2018).
Improved Decoy Selection via Machine Learning and Ranking.
In: Proceedings of the 8th International Conference on Computational Advances in Bio and Medical Sciences (ICCABS), pp. 1–1.
Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A Badawy, Gopinath Chennupati, Stephan Eidenbenz
(2017).
Probabilistic Monte Carlo simulations for static branch prediction.
In: IEEE International Performance Computing and Communications Conference (IPCCC), pp. 1–4.
Gopinath Chennupati, Nanadakishore Santhi, Stephen Eidenbenz, Robert Joseph Zerr, Massimiliano Rosa, Richard James Zamora, Eun Jung Park, Balasubramanya T Nadiga, Jason Liu, Kishwar Ahmed, {others}
(2017).
Performance prediction toolkit.
Gopinath Chennupati, Nandakishore Santhi, Robert Bird, Sunil Thulasidasan, Abdel-Hameed A Badawy, Satyajayant Misra, Stephan Eidenbenz
(2017).
A scalable analytical memory model for cpu performance prediction.
In: International Workshop on Performance Modeling, Benchmarking and Simulation of High Performance Computer Systems, pp. 114–135.
Bhargava Kalla, Nandakishore Santhi, Abdel-Hameed A Badawy, Gopinath Chennupati, Stephan Eidenbenz
(2017).
A probabilistic monte carlo framework for branch prediction.
In: IEEE International Conference on Cluster Computing (CLUSTER), pp. 651–652.