Evangelos Georganas

According to our database, Evangelos Georganas authored at least 34 papers between 2012 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of three.

2023

Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures.

Evangelos Georganas, Dhiraj D. Kalamkar, Kirill Voronin, Antonio Noack, Hans Pabst, Alexander Breuer, Alexander Heinecke

CoRR, 2023

2022

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning and HPC Workloads.

Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Deepti Aggarwal, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Brian Retford, Barukh Ziv, Alexander Heinecke

Frontiers Appl. Math. Stat., 2022

FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems.

Rui Ma, Evangelos Georganas, Alexander Heinecke, Andrew Boutros, Eriko Nurvitadhi

CoRR, 2022

FPGA-Based AI Smart NICs for Scalable Distributed AI Training Systems.

Rui Ma, Evangelos Georganas, Alexander Heinecke, Sergey Gribok, Andrew Boutros, Eriko Nurvitadhi

IEEE Comput. Archit. Lett., 2022

Accelerating Deep Learning based Identification of Chromatin Accessibility from noisy ATAC-seq Data.

Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul

Proceedings of the IEEE International Parallel and Distributed Processing Symposium, 2022

2021

Efficient and Generic 1D Dilated Convolution Layer for Deep Learning.

Narendra Chaudhary, Sanchit Misra, Dhiraj D. Kalamkar, Alexander Heinecke, Evangelos Georganas, Barukh Ziv, Menachem Adelman, Bharat Kaul

CoRR, 2021

Tensor Processing Primitives: A Programming Abstraction for Efficiency and Portability in Deep Learning Workloads.

Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Narendra Chaudhary, Abhisek Kundu, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke

CoRR, 2021

DistGNN: scalable distributed training for large-scale graph neural networks.

Md. Vasimuddin, Sanchit Misra, Guixiang Ma, Ramanarayan Mohanty, Evangelos Georganas, Alexander Heinecke, Dhiraj D. Kalamkar, Nesreen K. Ahmed, Sasikanth Avancha

Proceedings of the International Conference for High Performance Computing, 2021

Tensor processing primitives: a programming abstraction for efficiency and portability in deep learning workloads.

Evangelos Georganas, Dhiraj D. Kalamkar, Sasikanth Avancha, Menachem Adelman, Cristina Anderson, Alexander Breuer, Jeremy Bruestle, Narendra Chaudhary, Abhisek Kundu, Denise Kutnick, Frank Laub, Md. Vasimuddin, Sanchit Misra, Ramanarayan Mohanty, Hans Pabst, Barukh Ziv, Alexander Heinecke

Proceedings of the International Conference for High Performance Computing, 2021

Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs.

Zhongyi Lin, Evangelos Georganas, John D. Owens

Proceedings of the Euro-Par 2021: Parallel Processing, 2021

2020

The Parallelism Motifs of Genomic Data Analysis.

Katherine A. Yelick, Aydin Buluç, Muaaz G. Awan, Ariful Azad, Benjamin Brock, Rob Egan, Saliya Ekanayake, Marquita Ellis, Evangelos Georganas, Giulia Guidi, Steven A. Hofmeyr, Oguz Selvitopi, Cristina Teodoropol, Leonid Oliker

CoRR, 2020

Optimizing deep learning recommender systems training on CPU cluster architectures.

Dhiraj D. Kalamkar, Evangelos Georganas, Sudarshan Srinivasan, Jianping Chen, Mikhail Shiryaev, Alexander Heinecke

Proceedings of the International Conference for High Performance Computing, 2020

Harnessing Deep Learning via a Single Building Block.

Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke

Proceedings of the 2020 IEEE International Parallel and Distributed Processing Symposium (IPDPS), 2020

2019

Optimizing Deep Learning RNN Topologies on Intel Architecture.

Kunal Banerjee, Evangelos Georganas, Dhiraj D. Kalamkar, Barukh Ziv, Eden Segal, Cristina Anderson, Alexander Heinecke

Supercomput. Front. Innov., 2019

High-Performance Deep Learning via a Single Building Block.

Evangelos Georganas, Kunal Banerjee, Dhiraj D. Kalamkar, Sasikanth Avancha, Anand Venkat, Michael J. Anderson, Greg Henry, Hans Pabst, Alexander Heinecke

CoRR, 2019

A Study of BFLOAT16 for Deep Learning Training.

Dhiraj D. Kalamkar, Dheevatsa Mudigere, Naveen Mellempudi, Dipankar Das, Kunal Banerjee, Sasikanth Avancha, Dharma Teja Vooturi, Nataraj Jammalamadaka, Jianyu Huang, Hector Yuen, Jiyan Yang, Jongsoo Park, Alexander Heinecke, Evangelos Georganas, Sudarshan Srinivasan, Abhisek Kundu, Misha Smelyanskiy, Bharat Kaul, Pradeep Dubey

CoRR, 2019

Training Google Neural Machine Translation on an Intel CPU Cluster.

Dhiraj D. Kalamkar, Kunal Banerjee, Sudarshan Srinivasan, Srinivas Sridharan, Evangelos Georganas, Mikhail E. Smorkalov, Cong Xu, Alexander Heinecke

Proceedings of the 2019 IEEE International Conference on Cluster Computing, 2019

ISA mapper: a compute and hardware agnostic deep learning compiler.

Matthew Sotoudeh, Anand Venkat, Michael J. Anderson, Evangelos Georganas, Alexander Heinecke, Jason Knight

Proceedings of the 16th ACM International Conference on Computing Frontiers, 2019

2018

Extreme scale de novo metagenome assembly.

Evangelos Georganas, Rob Egan, Steven A. Hofmeyr, Eugene Goltsman, Bill Arndt, Andrew Tritt, Aydin Buluç, Leonid Oliker, Katherine A. Yelick

Proceedings of the International Conference for High Performance Computing, 2018

Anatomy of high-performance deep learning convolutions on SIMD architectures.

Evangelos Georganas, Sasikanth Avancha, Kunal Banerjee, Dhiraj D. Kalamkar, Greg Henry, Hans Pabst, Alexander Heinecke

Proceedings of the International Conference for High Performance Computing, 2018

Mixed Precision Training of Convolutional Neural Networks using Integer Operations.

Dipankar Das, Naveen Mellempudi, Dheevatsa Mudigere, Dhiraj D. Kalamkar, Sasikanth Avancha, Kunal Banerjee, Srinivas Sridharan, Karthik Vaidyanathan, Bharat Kaul, Evangelos Georganas, Alexander Heinecke, Pradeep Dubey, Jesús Corbal, Nikita Shustrov, Roman Dubtsov, Evarist Fomenko, Vadim O. Pirogov

Proceedings of the 6th International Conference on Learning Representations, 2018

2017

Extreme-Scale De Novo Genome Assembly.

Evangelos Georganas, Steven A. Hofmeyr, Rob Egan, Aydin Buluç, Leonid Oliker, Daniel Rokhsar, Katherine A. Yelick

CoRR, 2017

A New Parallel Research Kernel to Expand Research on Dynamic Load-Balancing Capabilities.

Rob F. Van der Wijngaart, Evangelos Georganas, Timothy G. Mattson, Andrew M. Wissink

Proceedings of the High Performance Computing - 32nd International Conference, 2017

MerBench: PGAS Benchmarks for High Performance Genome Assembly.

Evangelos Georganas, Marquita Ellis, Rob Egan, Steven A. Hofmeyr, Aydin Buluç, Brandon Cook, Leonid Oliker, Katherine A. Yelick

Proceedings of PAW@SC 2017: Second Annual PGAS Applications Workshop, 2017

Performance Characterization of De Novo Genome Assembly on Leading Parallel Systems.

Marquita Ellis, Evangelos Georganas, Rob Egan, Steven A. Hofmeyr, Aydin Buluç, Brandon Cook, Leonid Oliker, Katherine A. Yelick

Proceedings of the Euro-Par 2017: Parallel Processing - 23rd International Conference on Parallel and Distributed Computing, Santiago de Compostela, Spain, August 28, 2017

2016

Scalable Parallel Algorithms for Genome Analysis.

Evangelos Georganas

PhD thesis, 2016

Design and Implementation of a Parallel Research Kernel for Assessing Dynamic Load-Balancing Capabilities.

Evangelos Georganas, Rob F. Van der Wijngaart, Timothy G. Mattson

Proceedings of the 2016 IEEE International Parallel and Distributed Processing Symposium, 2016

2015

HipMer: an extreme-scale de novo genome assembler.

Evangelos Georganas, Aydin Buluç, Jarrod Chapman, Steven A. Hofmeyr, Chaitanya Aluru, Rob Egan, Leonid Oliker, Daniel Rokhsar, Katherine A. Yelick

Proceedings of the International Conference for High Performance Computing, 2015

merAligner: A Fully Parallel Sequence Aligner.

Evangelos Georganas, Aydin Buluç, Jarrod Chapman, Leonid Oliker, Daniel Rokhsar, Katherine A. Yelick

Proceedings of the 2015 IEEE International Parallel and Distributed Processing Symposium, 2015

2014

Scalable multimedia content analysis on parallel platforms using python.

Ekaterina Gonina, Gerald Friedland, Eric Battenberg, Penporn Koanantakool, Michael B. Driscoll, Evangelos Georganas, Kurt Keutzer

ACM Trans. Multim. Comput. Commun. Appl., 2014

Constructing Performance Models for Dense Linear Algebra Algorithms on Cray XE Systems.

Jorge González-Domínguez, Evangelos Georganas, Yili Zheng, María J. Martín

CoRR, 2014

Parallel De Bruijn Graph Construction and Traversal for De Novo Genome Assembly.

Evangelos Georganas, Aydin Buluç, Jarrod Chapman, Leonid Oliker, Daniel Rokhsar, Katherine A. Yelick

Proceedings of the International Conference for High Performance Computing, 2014

2013

A Communication-Optimal N-Body Algorithm for Direct Interactions.

Michael B. Driscoll, Evangelos Georganas, Penporn Koanantakool, Edgar Solomonik, Katherine A. Yelick

Proceedings of the 27th IEEE International Symposium on Parallel and Distributed Processing, 2013

2012

Communication avoiding and overlapping for numerical linear algebra.

Evangelos Georganas, Jorge González-Domínguez, Edgar Solomonik, Yili Zheng, Juan Touriño, Katherine A. Yelick

Proceedings of the SC Conference on High Performance Computing Networking, 2012