Aleksandr Drozd

40 papers A* 1A 3B 1C 2Journal 16Unranked 16
YearRankTypeTitle / Venue / Authors
2025 — conf
Aurora-M: Open Source Continual Pre-training for Multilingual Language and Code.
COLING (Industry)
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, Xuan-Son Vu, Marzena Karpinska, Arnav Varma Dantuluri, Wojciech Kusa, Tommaso Furlanello, Rio Yokota, Niklas Muennighoff, Suhas Pai, Tosin P. Adewumi, Veronika Laippala, Xiaozhe Yao, Adalberto Barbosa Junior, Aleksandr Drozd, Jordan Clive, Kshitij Gupta, Liangyu Chen, Qi Sun, Ken Tsui, Nour Moustafa-Fahmy, Nicolo Monti, Tai Dang, Ziyang Luo, Tien-Tung Bui, Roberto Navigli, Virendra Mehta, Matthew Blumberg, Victor May, Hiep Nguyen, Sampo Pyysalo
2024 J jnl
Aurora-M: The First Open Source Multilingual Language Model Red-teamed according to the U.S. Executive Order.
CoRR
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, Xuan-Son Vu, Marzena Karpinska, Arnav Varma Dantuluri, Wojciech Kusa, Tommaso Furlanello, Rio Yokota, Niklas Muennighoff, Suhas Pai, Tosin P. Adewumi, Veronika Laippala, Xiaozhe Yao, Adalberto Barbosa Junior, Alpay Ariyak, Aleksandr Drozd, Jordan Clive, Kshitij Gupta, Liangyu Chen, Qi Sun, Ken Tsui, Noah Persaud, Nour Moustafa-Fahmy, Tianlong Chen, Mohit Bansal, Nicolo Monti, Tai Dang, Ziyang Luo, Tien-Tung Bui, Roberto Navigli, Virendra Mehta, Matthew Blumberg, Victor May, Huu Nguyen, Sampo Pyysalo
2024 J jnl
Tadashi: Enabling AI-Based Automated Code Generation With Guaranteed Correctness.
CoRR
Emil Vatai, Aleksandr Drozd, Ivan R. Ivanov, Yinghao Ren, Mohamed Wahib
2024 — conf
Welcome Message from LLMxHPC Workshop.
CLUSTER Workshops
Kevin A. Brown, Tanwi Mallick, Juliane Mueller, Aleksandr Drozd
2023 J jnl
At the Locus of Performance: Quantifying the Effects of Copious 3D-Stacked Cache on HPC Workloads.
ACM Trans. Archit. Code Optim.
Jens Domke, Emil Vatai, Balazs Gerofi, Yuetsu Kodama, Mohamed Wahib, Artur Podobas, Sparsh Mittal, Miquel Pericàs, Lingqi Zhang, Peng Chen, Aleksandr Drozd, Satoshi Matsuoka
2023 J jnl
Myths and Legends in High-Performance Computing.
CoRR
Satoshi Matsuoka, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Torsten Hoefler
2023 J jnl
Myths and legends in high-performance computing.
Int. J. High Perform. Comput. Appl.
Satoshi Matsuoka, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Torsten Hoefler
2022 J jnl
At the Locus of Performance: A Case Study in Enhancing CPUs with Copious 3D-Stacked Cache.
CoRR
Jens Domke, Emil Vatai, Balazs Gerofi, Yuetsu Kodama, Mohamed Wahib, Artur Podobas, Sparsh Mittal, Miquel Pericàs, Lingqi Zhang, Peng Chen, Aleksandr Drozd, Satoshi Matsuoka
2022 — conf
Outlier Dimensions that Disrupt Transformers are Driven by Frequency.
EMNLP (Findings)
Giovanni Puccetti, Anna Rogers, Aleksandr Drozd, Felice Dell'Orletta
2022 J jnl
Outliers Dimensions that Disrupt Transformers Are Driven by Frequency.
CoRR
Giovanni Puccetti, Anna Rogers, Aleksandr Drozd, Felice Dell'Orletta
2022 J jnl
Preparing for the Future - Rethinking Proxy Applications.
Comput. Sci. Eng.
Satoshi Matsuoka, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Andrew A. Chien, Raymond Bair, Jeffrey S. Vetter, John Shalf
2022 J jnl
Preparing for the Future - Rethinking Proxy Apps.
CoRR
Satoshi Matsuoka, Jens Domke, Mohamed Wahib, Aleksandr Drozd, Ray Bair, Andrew A. Chien, Jeffrey S. Vetter, John Shalf
2022 — ed.
Proceedings of the Third Workshop on Insights from Negative Results in NLP, Insights@ACL 2022, Dublin, Ireland, May 26, 2022
Insights@ACL
Shabnam Tafreshi, João Sedoc, Anna Rogers, Aleksandr Drozd, Anna Rumshisky, Arjun R. Akula
2022 A conf
Why Globally Re-shuffle? Revisiting Data Shuffling in Large Scale Deep Learning.
IPDPS
Truong Thao Nguyen, François Trahay, Jens Domke, Aleksandr Drozd, Emil Vatai, Jianwei Liao, Mohamed Wahib, Balazs Gerofi
2021 J jnl
Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics.
CoRR
Prajjwal Bhargava, Aleksandr Drozd, Anna Rogers
2021 J jnl
MLPerf HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.
CoRR
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, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
2021 — conf
MLPerf™ HPC: A Holistic Benchmark Suite for Scientific Machine Learning on HPC Systems.
MLHPC@SC
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, Kento Sato, Koichi Shirahata, Tsuguchika Tabaru, Aristeidis Tsaris, Jan Balewski, Ben Cumming, Takumi Danjo, Jens Domke, Takaaki Fukai, Naoto Fukumoto, Tatsuya Fukushi, Balazs Gerofi, Takumi Honda, Toshiyuki Imamura, Akihiko Kasagi, Kentaro Kawakami, Shuhei Kudo, Akiyoshi Kuroda, Maxime Martinasso, Satoshi Matsuoka, Henrique Mendonça, Kazuki Minami, Prabhat Ram, Takashi Sawada, Mallikarjun Shankar, Tom St. John, Akihiro Tabuchi, Venkatram Vishwanath, Mohamed Wahib, Masafumi Yamazaki, Junqi Yin
2021 A conf
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws?
IPDPS
Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka
2020 J jnl
Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws?
CoRR
Jens Domke, Emil Vatai, Aleksandr Drozd, Peng Chen, Yosuke Oyama, Lingqi Zhang, Shweta Salaria, Daichi Mukunoki, Artur Podobas, Mohamed Wahib, Satoshi Matsuoka
2020 J jnl
Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA.
CoRR
Mohamed Wahib, Haoyu Zhang, Truong Thao Nguyen, Aleksandr Drozd, Jens Domke, Lingqi Zhang, Ryousei Takano, Satoshi Matsuoka
2020 A conf
Scaling distributed deep learning workloads beyond the memory capacity with KARMA.
SC
Mohamed Wahib, Haoyu Zhang, Truong Thao Nguyen, Aleksandr Drozd, Jens Domke, Lingqi Zhang, Ryousei Takano, Satoshi Matsuoka
2019 C conf
Learning Neural Representations for Predicting GPU Performance.
ISC
Shweta Salaria, Aleksandr Drozd, Artur Podobas, Satoshi Matsuoka
2019 J jnl
Scaling Word2Vec on Big Corpus.
Data Sci. Eng.
Bofang Li, Aleksandr Drozd, Yuhe Guo, Tao Liu, Satoshi Matsuoka, Xiaoyong Du
2018 C conf
Predicting Performance Using Collaborative Filtering.
CLUSTER
Shweta Salaria, Aleksandr Drozd, Artur Podobas, Satoshi Matsuoka
2018 — conf
VANT at TRECVID 2018.
TRECVID
Nakamasa Inoue, Chihiro Shiraishi, Aleksandr Drozd, Koichi Shinoda, Shi-wook Lee, Alex ChiChung Kot
2017 A* conf
Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings.
EMNLP
Bofang Li, Tao Liu, Zhe Zhao, Buzhou Tang, Aleksandr Drozd, Anna Rogers, Xiaoyong Du
2017 — conf
The (too Many) Problems of Analogical Reasoning with Word Vectors.
*SEM
Anna Rogers, Aleksandr Drozd, Bofang Li
2016 — conf
Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn't.
SRW@HLT-NAACL
Anna Gladkova, Aleksandr Drozd, Satoshi Matsuoka
2016 J jnl
Critical mass in the emergence of collective intelligence: a parallelized simulation of swarms in noisy environments.
Artif. Life Robotics
Aleksandr Drozd, Olaf Witkowski, Satoshi Matsuoka, Takashi Ikegami
2016 J jnl
GPU-Accelerated Large-Scale Distributed Sorting Coping with Device Memory Capacity.
IEEE Trans. Big Data
Hideyuki Shamoto, Koichi Shirahata, Aleksandr Drozd, Hitoshi Sato, Satoshi Matsuoka
2016 — conf
Intrinsic Evaluations of Word Embeddings: What Can We Do Better?
RepEval@ACL
Anna Gladkova, Aleksandr Drozd
2016 — conf
Migrating Legacy Fortran to Python While Retaining Fortran-Level Performance through Transpilation and Type Hints.
PyHPC@SC
Mateusz Bysiek, Aleksandr Drozd, Satoshi Matsuoka
2016 B conf
Word Embeddings, Analogies, and Machine Learning: Beyond king - man + woman = queen.
COLING
Aleksandr Drozd, Anna Gladkova, Satoshi Matsuoka
2015 — conf
Discovering Aspectual Classes of Russian Verbs in Untagged Large Corpora.
DSDIS
Aleksandr Drozd, Anna Gladkova, Satoshi Matsuoka
2015 — conf
Python, performance, and natural language processing.
PyHPC@SC
Aleksandr Drozd, Anna Gladkova, Satoshi Matsuoka
2014 — conf
Efficient String Sorting on Multi - and Many-Core Architectures.
BigData Congress
Aleksandr Drozd, Miquel Pericàs, Satoshi Matsuoka
2014 — conf
Large-scale distributed sorting for GPU-based heterogeneous supercomputers.
IEEE BigData
Hideyuki Shamoto, Koichi Shirahata, Aleksandr Drozd, Hitoshi Sato, Satoshi Matsuoka
2012 — conf
A Multi GPU Read Alignment Algorithm with Model-Based Performance Optimization.
VECPAR
Aleksandr Drozd, Naoya Maruyama, Satoshi Matsuoka
2012 — conf
Sequence Alignment on Massively Parallel Heterogeneous Systems.
IPDPS Workshops
Aleksandr Drozd, Naoya Maruyama, Satoshi Matsuoka
2011 — conf
Poster: fast GPU read alignment with burrows wheeler transform based index.
SC Companion
Aleksandr Drozd, Naoya Maruyama, Satoshi Matsuoka