Communication avoiding and overlapping for numerical linear algebra. - Evangelos Georganas; Jorge González-Domínguez; Edgar Solomonik; Yili Zheng; Juan Touriño; Katherine A. Yelick (SC, 2012)

A Communication-Optimal N-Body Algorithm for Direct Interactions. - Michael B. Driscoll; Evangelos Georganas; Penporn Koanantakool; Edgar Solomonik; Katherine A. Yelick (IPDPS, 2013)

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 (SC, 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)

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)

merAligner: A Fully Parallel Sequence Aligner. - Evangelos Georganas; Aydin Buluç; Jarrod Chapman; Leonid Oliker; Daniel Rokhsar; Katherine A. Yelick (IPDPS, 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 (SC, 2015)

Design and Implementation of a Parallel Research Kernel for Assessing Dynamic Load-Balancing Capabilities. - Evangelos Georganas; Rob F. Van der Wijngaart; Timothy G. Mattson (IPDPS, 2016)

Scalable Parallel Algorithms for Genome Analysis. - Evangelos Georganas (2016)

Performance Characterization of De Novo Genome Assembly on Leading Parallel Systems. - Marquita Ellis; Evangelos Georganas; Rob Egan; Steven A. Hofmeyr; Aydin Buluç; Brandon Cook 001; Leonid Oliker; Katherine A. Yelick (Euro-Par, 2017)

MerBench: PGAS Benchmarks for High Performance Genome Assembly. - Evangelos Georganas; Marquita Ellis; Rob Egan; Steven A. Hofmeyr; Aydin Buluç; Brandon Cook 001; Leonid Oliker; Katherine A. Yelick (PAW@SC, 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 (ISC, 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)

Mixed Precision Training of Convolutional Neural Networks using Integer Operations. - Dipankar Das 002; Naveen Mellempudi; Dheevatsa Mudigere; Dhiraj D. Kalamkar; Sasikanth Avancha; Kunal Banerjee 001; Srinivas Sridharan 002; Karthik Vaidyanathan; Bharat Kaul; Evangelos Georganas; Alexander Heinecke; Pradeep Dubey; et al. (ICLR (Poster), 2018)

Anatomy of high-performance deep learning convolutions on SIMD architectures. - Evangelos Georganas; Sasikanth Avancha; Kunal Banerjee 001; Dhiraj D. Kalamkar; Greg Henry; Hans Pabst; Alexander Heinecke (SC, 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 (SC, 2018)

ISA mapper: a compute and hardware agnostic deep learning compiler. - Matthew Sotoudeh; Anand Venkat; Michael J. Anderson; Evangelos Georganas; Alexander Heinecke; Jason Knight (CF, 2019)

Training Google Neural Machine Translation on an Intel CPU Cluster. - Dhiraj D. Kalamkar; Kunal Banerjee 001; Sudarshan Srinivasan; Srinivas Sridharan 002; Evangelos Georganas; Mikhail E. Smorkalov; Cong Xu; Alexander Heinecke (CLUSTER, 2019)

A Study of BFLOAT16 for Deep Learning Training. - Dhiraj D. Kalamkar; Dheevatsa Mudigere; Naveen Mellempudi; Dipankar Das 002; Kunal Banerjee 001; Sasikanth Avancha; Dharma Teja Vooturi; Nataraj Jammalamadaka; Jianyu Huang; Hector Yuen; Jiyan Yang; Jongsoo Park; et al. (CoRR, 2019)

High-Performance Deep Learning via a Single Building Block. - Evangelos Georganas; Kunal Banerjee 001; Dhiraj D. Kalamkar; Sasikanth Avancha; Anand Venkat; Michael J. Anderson; Greg Henry; Hans Pabst; Alexander Heinecke (CoRR, 2019)

Optimizing Deep Learning RNN Topologies on Intel Architecture. - Kunal Banerjee 001; Evangelos Georganas; Dhiraj D. Kalamkar; Barukh Ziv; Eden Segal; Cristina Anderson; Alexander Heinecke (Supercomput. Front. Innov., 2019)

Harnessing Deep Learning via a Single Building Block. - Evangelos Georganas; Kunal Banerjee 001; Dhiraj D. Kalamkar; Sasikanth Avancha; Anand Venkat; Michael J. Anderson; Greg Henry; Hans Pabst; Alexander Heinecke (IPDPS, 2020)

Optimizing deep learning recommender systems training on CPU cluster architectures. - Dhiraj D. Kalamkar; Evangelos Georganas; Sudarshan Srinivasan; Jianping Chen; Mikhail Shiryaev; Alexander Heinecke (SC, 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; et al. (CoRR, 2020)

Towards Flexible and Compiler-Friendly Layer Fusion for CNNs on Multicore CPUs. - Zhongyi Lin; Evangelos Georganas; John D. Owens (Euro-Par, 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; et al. (SC, 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 (SC, 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; et al. (CoRR, 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)

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 (IPDPS Workshops, 2022)

FPGA-Based AI Smart NICs for Scalable Distributed AI Training Systems. - Rui Ma 021; Evangelos Georganas; Alexander Heinecke; Sergey Gribok; Andrew Boutros; Eriko Nurvitadhi (IEEE Comput. Archit. Lett., 2022)

FPGA-based AI Smart NICs for Scalable Distributed AI Training Systems. - Rui Ma; Evangelos Georganas; Alexander Heinecke; Andrew Boutros; Eriko Nurvitadhi (CoRR, 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; et al. (Frontiers Appl. Math. Stat., 2022)

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)

Harnessing Deep Learning and HPC Kernels via High-Level Loop and Tensor Abstractions on CPU Architectures. - Evangelos Georganas; Dhiraj D. Kalamkar; Kirill Voronin; Abhisek Kundu; Antonio Noack; Hans Pabst; Alexander Breuer; Alexander Heinecke (IPDPS, 2024)

Towards a high-performance AI compiler with upstream MLIR. - Renato Golin; Lorenzo Chelini; Adam Siemieniuk; Kavitha Madhu; Niranjan Hasabnis; Hans Pabst; Evangelos Georganas; Alexander Heinecke (CoRR, 2024)

ML-SpecQD: Multi-Level Speculative Decoding with Quantized Drafts. - Evangelos Georganas; Dhiraj D. Kalamkar; Alexander Kozlov; Alexander Heinecke (CoRR, 2025)

DECA: A Near-Core LLM Decompression Accelerator Supporting Out-of-Order Invocation. - Gerasimos Gerogiannis; Stijn Eyerman; Evangelos Georganas; Wim Heirman; Josep Torrellas (CoRR, 2025)

Pushing the Envelope of LLM Inference on AI-PC. - Evangelos Georganas; Dhiraj D. Kalamkar; Alexander Heinecke (CoRR, 2025)