Poster: fast GPU read alignment with burrows wheeler transform based index. - Aleksandr Drozd; Naoya Maruyama; Satoshi Matsuoka (SC Companion, 2011)

Sequence Alignment on Massively Parallel Heterogeneous Systems. - Aleksandr Drozd; Naoya Maruyama; Satoshi Matsuoka (IPDPS Workshops, 2012)

A Multi GPU Read Alignment Algorithm with Model-Based Performance Optimization. - Aleksandr Drozd; Naoya Maruyama; Satoshi Matsuoka (VECPAR, 2012)

Efficient String Sorting on Multi - and Many-Core Architectures. - Aleksandr Drozd; Miquel Pericàs; Satoshi Matsuoka (BigData Congress, 2014)

Large-scale distributed sorting for GPU-based heterogeneous supercomputers. - Hideyuki Shamoto; Koichi Shirahata; Aleksandr Drozd; Hitoshi Sato; Satoshi Matsuoka (IEEE BigData, 2014)

Discovering Aspectual Classes of Russian Verbs in Untagged Large Corpora. - Aleksandr Drozd; Anna Gladkova 001; Satoshi Matsuoka (DSDIS, 2015)

Python, performance, and natural language processing. - Aleksandr Drozd; Anna Gladkova 001; Satoshi Matsuoka (PyHPC@SC, 2015)

Word Embeddings, Analogies, and Machine Learning: Beyond king - man + woman = queen. - Aleksandr Drozd; Anna Gladkova 001; Satoshi Matsuoka (COLING, 2016)

Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't. - Anna Gladkova 001; Aleksandr Drozd; Satoshi Matsuoka (SRW@HLT-NAACL, 2016)

Intrinsic Evaluations of Word Embeddings: What Can We Do Better? - Anna Gladkova 001; Aleksandr Drozd (RepEval@ACL, 2016)

Migrating Legacy Fortran to Python While Retaining Fortran-Level Performance through Transpilation and Type Hints. - Mateusz Bysiek; Aleksandr Drozd; Satoshi Matsuoka (PyHPC@SC, 2016)

Critical mass in the emergence of collective intelligence: a parallelized simulation of swarms in noisy environments. - Aleksandr Drozd; Olaf Witkowski; Satoshi Matsuoka; Takashi Ikegami (Artif. Life Robotics, 2016)

GPU-Accelerated Large-Scale Distributed Sorting Coping with Device Memory Capacity. - Hideyuki Shamoto; Koichi Shirahata; Aleksandr Drozd; Hitoshi Sato; Satoshi Matsuoka (IEEE Trans. Big Data, 2016)

Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings. - Bofang Li; Tao Liu 001; Zhe Zhao 006; Buzhou Tang; Aleksandr Drozd; Anna Rogers; Xiaoyong Du 001 (EMNLP, 2017)

The (too Many) Problems of Analogical Reasoning with Word Vectors. - Anna Rogers; Aleksandr Drozd; Bofang Li (*SEM, 2017)

Predicting Performance Using Collaborative Filtering. - Shweta Salaria; Aleksandr Drozd; Artur Podobas; Satoshi Matsuoka (CLUSTER, 2018)

VANT at TRECVID 2018. - Nakamasa Inoue; Chihiro Shiraishi; Aleksandr Drozd; Koichi Shinoda; Shi-wook Lee; Alex ChiChung Kot (TRECVID, 2018)

Learning Neural Representations for Predicting GPU Performance. - Shweta Salaria; Aleksandr Drozd; Artur Podobas; Satoshi Matsuoka (ISC, 2019)

Scaling Word2Vec on Big Corpus. - Bofang Li; Aleksandr Drozd; Yuhe Guo; Tao Liu 001; Satoshi Matsuoka; Xiaoyong Du 001 (Data Sci. Eng., 2019)

Scaling distributed deep learning workloads beyond the memory capacity with KARMA. - Mohamed Wahib; Haoyu Zhang; Truong Thao Nguyen; Aleksandr Drozd; Jens Domke; Lingqi Zhang 001; Ryousei Takano; Satoshi Matsuoka (SC, 2020)

Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws? - Jens Domke; Emil Vatai; Aleksandr Drozd; Peng Chen 035; Yosuke Oyama; Lingqi Zhang 001; Shweta Salaria; Daichi Mukunoki; Artur Podobas; Mohamed Wahib; Satoshi Matsuoka (IPDPS, 2021)

MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. - Steven Farrell; Murali Emani; Jacob Balma; Lukas Drescher; Aleksandr Drozd; Andreas Fink; Geoffrey C. Fox; David Kanter; Thorsten Kurth; Peter Mattson; Dawei Mu; Amit Ruhela; et al. (MLHPC@SC, 2021)

Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics. - Prajjwal Bhargava; Aleksandr Drozd; Anna Rogers (CoRR, 2021)

MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems. - Steven Farrell; Murali Emani; Jacob Balma; Lukas Drescher; Aleksandr Drozd; Andreas Fink; Geoffrey C. Fox; David Kanter; Thorsten Kurth; Peter Mattson; Dawei Mu; Amit Ruhela; et al. (CoRR, 2021)

Outlier Dimensions that Disrupt Transformers are Driven by Frequency. - Giovanni Puccetti 002; Anna Rogers; Aleksandr Drozd; Felice Dell'Orletta (EMNLP (Findings), 2022)

Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning. - Truong Thao Nguyen; François Trahay; Jens Domke; Aleksandr Drozd; Emil Vatai; Jianwei Liao 001; Mohamed Wahib; Balazs Gerofi (IPDPS, 2022)

At the Locus of Performance: A Case Study in Enhancing CPUs with Copious 3D-Stacked Cache. - Jens Domke; Emil Vatai; Balazs Gerofi; Yuetsu Kodama; Mohamed Wahib; Artur Podobas; Sparsh Mittal; Miquel Pericàs; Lingqi Zhang 001; Peng Chen 035; Aleksandr Drozd; Satoshi Matsuoka (CoRR, 2022)

Preparing for the Future - Rethinking Proxy Apps. - Satoshi Matsuoka; Jens Domke; Mohamed Wahib; Aleksandr Drozd; Ray Bair; Andrew A. Chien; Jeffrey S. Vetter; John Shalf (CoRR, 2022)

Outliers Dimensions that Disrupt Transformers Are Driven by Frequency. - Giovanni Puccetti 002; Anna Rogers; Aleksandr Drozd; Felice Dell'Orletta (CoRR, 2022)

Preparing for the Future - Rethinking Proxy Applications. - Satoshi Matsuoka; Jens Domke; Mohamed Wahib; Aleksandr Drozd; Andrew A. Chien; Raymond Bair; Jeffrey S. Vetter; John Shalf (Comput. Sci. Eng., 2022)

Myths and legends in high-performance computing. - Satoshi Matsuoka; Jens Domke; Mohamed Wahib; Aleksandr Drozd; Torsten Hoefler (Int. J. High Perform. Comput. Appl., 2023)

At the Locus of Performance: Quantifying the Effects of Copious 3D-Stacked Cache on HPC Workloads. - Jens Domke; Emil Vatai; Balazs Gerofi; Yuetsu Kodama; Mohamed Wahib; Artur Podobas; Sparsh Mittal; Miquel Pericàs; Lingqi Zhang 001; Peng Chen 035; Aleksandr Drozd; Satoshi Matsuoka (ACM Trans. Archit. Code Optim., 2023)

Welcome Message from LLMxHPC Workshop. - Kevin A. Brown; Tanwi Mallick; Juliane Mueller 002; Aleksandr Drozd (CLUSTER Workshops, 2024)

Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order. - Taishi Nakamura; Mayank Mishra; Simone Tedeschi; Yekun Chai; Jason T. Stillerman; Felix Friedrich; Prateek Yadav; Tanmay Laud; Minh Chien Vu; Terry Yue Zhuo; Diganta Misra; Ben Bogin; et al. (CoRR, 2024)

Tadashi: Enabling AI-Based Automated Code Generation With Guaranteed Correctness. - Emil Vatai; Aleksandr Drozd; Ivan R. Ivanov; Yinghao Ren; Mohamed Wahib (CoRR, 2024)

Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code. - Taishi Nakamura; Mayank Mishra; Simone Tedeschi; Yekun Chai; Jason T. Stillerman; Felix Friedrich; Prateek Yadav; Tanmay Laud; Minh Chien Vu; Terry Yue Zhuo; Diganta Misra; Ben Bogin; et al. (COLING (Industry), 2025)