Aleksandr Drozd

发表

A Multi GPU Read Alignment Algorithm with Model-Based Performance Optimization

Satoshi Matsuoka, Naoya Maruyama, Aleksandr Drozd, 2012, VECPAR.

Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws? pdf

Mohamed Wahib, Yosuke Oyama, Jens Domke, 2020, 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS).

Subcharacter Information in Japanese Embeddings: When Is It Worth It?

Bofang Li, Marzena Karpinska, Anna Rogers, 2018 .

Efficient String Sorting on Multi - and Many-Core Architectures

Satoshi Matsuoka, Miquel Pericàs, Aleksandr Drozd, 2014, 2014 IEEE International Congress on Big Data.

Learning Neural Representations for Predicting GPU Performance

Satoshi Matsuoka, Artur Podobas, Aleksandr Drozd, 2019, ISC.

Critical mass in the emergence of collective intelligence: a parallelized simulation of swarms in noisy environments

Satoshi Matsuoka, Olaf Witkowski, Takashi Ikegami, 2016, Artificial Life and Robotics.

Sequence Alignment on Massively Parallel Heterogeneous Systems

Satoshi Matsuoka, Naoya Maruyama, Aleksandr Drozd, 2012, 2012 IEEE 26th International Parallel and Distributed Processing Symposium Workshops & PhD Forum.

Poster: fast GPU read alignment with burrows wheeler transform based index

Satoshi Matsuoka, Naoya Maruyama, Aleksandr Drozd, 2011, SC '11 Companion.

Migrating Legacy Fortran to Python While Retaining Fortran-Level Performance through Transpilation and Type Hints

Satoshi Matsuoka, Aleksandr Drozd, Mateusz Bysiek, 2016, 2016 6th Workshop on Python for High-Performance and Scientific Computing (PyHPC).

GPU Implementation of Splitter-based Parallel Sorting for Large-scale Heterogeneous Architectures

Satoshi Matsuoka, 佐藤仁, 松岡聡, 2014 .

Python, performance, and natural language processing

Satoshi Matsuoka, Anna Gladkova, Aleksandr Drozd, 2015, PyHPC '15.

Fast GPU Read Alignmennt with Burrows Wheeler Transform Based Index

Satoshi Matsuoka, Naoya Maruyama, Aleksandr Drozd, 2011 .

Investigating Different Syntactic Context Types and Context Representations for Learning Word Embeddings

Xiaoyong Du, Tao Liu, Zhe Zhao, 2017, EMNLP.

Subword-level Composition Functions for Learning Word Embeddings

Xiaoyong Du, Tao Liu, Bofang Li, 2018 .

Word Embeddings, Analogies, and Machine Learning: Beyond king - man + woman = queen

Satoshi Matsuoka, Anna Gladkova, Aleksandr Drozd, 2016, COLING.

Scaling Distributed Deep Learning Workloads beyond the Memory Capacity with KARMA pdf

Mohamed Wahib, Jens Domke, Ryousei Takano, 2020, ArXiv.

VANT at TRECVID 2018

Alex ChiChung Kot, Shi-wook Lee, Nakamasa Inoue, 2018, TRECVID.

GPU-Accelerated Large-Scale Distributed Sorting Coping with Device Memory Capacity

Satoshi Matsuoka, Hitoshi Sato, Koichi Shirahata, 2016, IEEE Transactions on Big Data.

Analogy-based detection of morphological and semantic relations with word embeddings: what works and what doesn’t.

Satoshi Matsuoka, Anna Gladkova, Aleksandr Drozd, 2016, NAACL.

Memory-Conscious Optimizations for Sorting and Sequence Alignment for Massively Parallel Heterogeneous Architectures

Aleksandr Drozd, 2014 .

Intrinsic Evaluations of Word Embeddings: What Can We Do Better?

Anna Gladkova, Aleksandr Drozd, Anna Rogers, 2016, RepEval@ACL.

The (too Many) Problems of Analogical Reasoning with Word Vectors

Bofang Li, Anna Rogers, Aleksandr Drozd, 2017, *SEMEVAL.

Predicting Performance Using Collaborative Filtering

Satoshi Matsuoka, Artur Podobas, Aleksandr Drozd, 2018, 2018 IEEE International Conference on Cluster Computing (CLUSTER).

Discovering Aspectual Classes of Russian Verbs in Untagged Large Corpora

Satoshi Matsuoka, Anna Gladkova, Aleksandr Drozd, 2015, 2015 IEEE International Conference on Data Science and Data Intensive Systems.

Towards Portable High Performance in Python: Transpilation, High-Level IR, Code Transformations and Compiler Directives

Satoshi Matsuoka, Mohamed Wahib, Aleksandr Drozd, 2018 .

Large-scale distributed sorting for GPU-based heterogeneous supercomputers

Satoshi Matsuoka, Hitoshi Sato, Koichi Shirahata, 2014, 2014 IEEE International Conference on Big Data (Big Data).

Scaling Word2Vec on Big Corpus

Satoshi Matsuoka, Xiaoyong Du, Tao Liu, 2019, Data Science and Engineering.

Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics pdf

Aleksandr Drozd, Prajjwal Bhargava, Anna Rogers, 2021, INSIGHTS.

Matrix Engines for High Performance Computing: A Paragon of Performance or Grasping at Straws?

Satoshi Matsuoka, Mohamed Wahib, Yosuke Oyama, 2021, 2021 IEEE International Parallel and Distributed Processing Symposium (IPDPS).