Simplifying Active Memory Clusters by Leveraging Directory Protocol Threads. - Dhiraj D. Kalamkar; Mainak Chaudhuri; Mark A. Heinrich (ISPASS, 2007)

High Performance Non-uniform FFT on Modern X86-based Multi-core Systems. - Dhiraj D. Kalamkar; Joshua D. Trzasko; Srinivas Sridharan 002; Mikhail Smelyanskiy; Daehyun Kim 001; Armando Manduca; Yunhong Shu; Matt A. Bernstein; Bharat Kaul; Pradeep Dubey (IPDPS, 2012)

Analysis and Optimization of Financial Analytics Benchmark on Modern Multi- and Many-core IA-Based Architectures. - Mikhail Smelyanskiy; Jason Sewall; Dhiraj D. Kalamkar; Nadathur Satish; Pradeep Dubey; Nikita Astafiev; Ilya Burylov; Andrey Nikolaev; Sergey Maidanov; Shuo Li; Sunil Kulkarni; Charles H. Finan; et al. (SC Companion, 2012)

Optimization of geometric multigrid for emerging multi- and manycore processors. - Samuel Williams 001; Dhiraj D. Kalamkar; Amik Singh; Anand M. Deshpande; Brian van Straalen; Mikhail Smelyanskiy; Ann S. Almgren; Pradeep Dubey; John Shalf; Leonid Oliker (SC, 2012)

Lattice QCD on Intel® Xeon PhiTM Coprocessors. - Bálint Joó; Dhiraj D. Kalamkar; Karthikeyan Vaidyanathan; Mikhail Smelyanskiy; Kiran Pamnany; Victor W. Lee; Pradeep Dubey; William A. Watson III (ISC, 2013)

Improving Communication Performance and Scalability of Native Applications on Intel Xeon Phi Coprocessor Clusters. - Karthikeyan Vaidyanathan; Kiran Pamnany; Dhiraj D. Kalamkar; Alexander Heinecke; Mikhail Smelyanskiy; Jongsoo Park; Daehyun Kim 001; Aniruddha G. Shet; Bharat Kaul; Bálint Joó; Pradeep Dubey (IPDPS, 2014)

Lattice QCD with Domain Decomposition on Intel® Xeon Phi Co-Processors. - Simon Heybrock; Bálint Joó; Dhiraj D. Kalamkar; Mikhail Smelyanskiy; Karthikeyan Vaidyanathan; Tilo Wettig; Pradeep Dubey (SC, 2014)

Efficient Shared-Memory Implementation of High-Performance Conjugate Gradient Benchmark and its Application to Unstructured Matrices. - Jongsoo Park; Mikhail Smelyanskiy; Karthikeyan Vaidyanathan; Alexander Heinecke; Dhiraj D. Kalamkar; Xing Liu; Md. Mostofa Ali Patwary; Yutong Lu; Pradeep Dubey (SC, 2014)

Enabling Efficient Multithreaded MPI Communication through a Library-Based Implementation of MPI Endpoints. - Srinivas Sridharan 002; James Dinan; Dhiraj D. Kalamkar (SC, 2014)

Improving concurrency and asynchrony in multithreaded MPI applications using software offloading. - Karthikeyan Vaidyanathan; Dhiraj D. Kalamkar; Kiran Pamnany; Jeff R. Hammond; Pavan Balaji; Dipankar Das 002; Jongsoo Park; Bálint Joó (SC, 2015)

Optimizing Wilson-Dirac Operator and Linear Solvers for Intel® KNL. - Bálint Joó; Dhiraj D. Kalamkar; Thorsten Kurth; Karthikeyan Vaidyanathan; Aaron Walden (ISC Workshops, 2016)

Distributed Deep Learning Using Synchronous Stochastic Gradient Descent. - Dipankar Das 002; Sasikanth Avancha; Dheevatsa Mudigere; Karthikeyan Vaidyanathan; Srinivas Sridharan 002; Dhiraj D. Kalamkar; Bharat Kaul; Pradeep Dubey (CoRR, 2016)

Optimizations in a high-performance conjugate gradient benchmark for IA-based multi- and many-core processors. - Jongsoo Park; Mikhail Smelyanskiy; Karthikeyan Vaidyanathan; Alexander Heinecke; Dhiraj D. Kalamkar; Md. Mostofa Ali Patwary; Vadim O. Pirogov; Pradeep Dubey; Xing Liu; Carlos Rosales; Cyril Mazauric; Christopher S. Daley (Int. J. High Perform. Comput. Appl., 2016)

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)

On Scale-out Deep Learning Training for Cloud and HPC. - Srinivas Sridharan 002; Karthikeyan Vaidyanathan; Dhiraj D. Kalamkar; Dipankar Das 002; Mikhail E. Smorkalov; Mikhail Shiryaev; Dheevatsa Mudigere; Naveen Mellempudi; Sasikanth Avancha; Bharat Kaul; Pradeep Dubey (CoRR, 2018)

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)

K-TanH: Hardware Efficient Activations For Deep Learning. - Abhisek Kundu; Sudarshan Srinivasan; Eric C. Qin; Dhiraj D. Kalamkar; Naveen K. Mellempudi; Dipankar Das 002; Kunal Banerjee 001; Bharat Kaul; Pradeep Dubey (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)

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)

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)

LOSM: Leveraging OpenMP and Shared Memory for Accelerating Blocking MPI Allreduce. - Pranjal Walia; Ishan Shanware; Karthikeyan Vaidyanathan; Dhiraj D. Kalamkar; Uma M. Natarajan (HIPCW, 2024)

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)

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

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