--- title: "Computing & GPUs — papers, page 3" description: "Computing & GPUs: 111 papers of the Elamur Research library · page 3 of 5 — our summary of each, its ideas, references and who cites it." canonical: "https://research.elamur.ai/free/en/shelves/computing/page/3/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/shelves/computing/page/3/) [home](https://md.research.elamur.ai/free/en/) / [shelves](https://md.research.elamur.ai/free/en/shelves/) / [Computing & GPUs](https://md.research.elamur.ai/free/en/shelves/computing/) / page 3 # 🖥️ Computing & GPUs 111 papers · page 3 of 5 · newest first · [all shelves](https://md.research.elamur.ai/free/en/shelves/) GPUs and parallel computing, compilers and languages, systems, databases, security, search and the web. [← prev](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) [1](https://md.research.elamur.ai/free/en/shelves/computing/) [2](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) **3** [4](https://md.research.elamur.ai/free/en/shelves/computing/page/4/) [5](https://md.research.elamur.ai/free/en/shelves/computing/page/5/) [next →](https://md.research.elamur.ai/free/en/shelves/computing/page/4/) - [Unified Pre-training for Program Understanding and Generation](https://md.research.elamur.ai/free/en/papers/ahmad-2021-unified-pre-training-program-understanding/) — Wasi Ahmad, Saikat Chakraborty, Baishakhi Ray, et al. · 2021 - [ZeRO-Offload: Democratizing Billion-Scale Model Training](https://md.research.elamur.ai/free/en/papers/ren-2021-zero-offload-democratizing-billion-scale/) — Jie Ren, Samyam Rajbhandari, Reza Yazdani Aminabadi, et al. · 2021 - [CodeBERT: A Pre-Trained Model for Programming and Natural Languages](https://md.research.elamur.ai/free/en/papers/feng-2020-codebert-pre-trained-model-programming/) — Zhangyin Feng, Daya Guo, Duyu Tang, et al. · 2020 - [CodeSearchNet Challenge: Evaluating the State of Semantic Code Search](https://md.research.elamur.ai/free/en/papers/husain-2020-codesearchnet-challenge-evaluating-state-semantic/) — Hamel Husain, Ho-Hsiang Wu, Tiferet Gazit, et al. · 2020 - [ColBERT: Efficient and Effective Passage Search via Contextualized Late Interaction over BERT](https://md.research.elamur.ai/free/en/papers/khattab-2020-colbert-efficient-effective-passage/) — Omar Khattab, Matei Zaharia · 2020 - [Dense Passage Retrieval for Open-Domain Question Answering](https://md.research.elamur.ai/free/en/papers/karpukhin-2020-dense-passage-retrieval-open-domain/) — Vladimir Karpukhin, Barlas Oguz, Sewon Min, et al. · 2020 - [Language ID in the Wild: Unexpected Challenges on the Path to a Thousand-Language Web Text Corpus](https://md.research.elamur.ai/free/en/papers/caswell-2020-language-id-wild-unexpected/) — Isaac Caswell, Theresa Breiner, Daan van Esch, et al. · 2020 - [PyTorch Distributed: Experiences on Accelerating Data Parallel Training](https://md.research.elamur.ai/free/en/papers/li-2020-pytorch-distributed-experiences-accelerating-data/) — Shen Li, Yanli Zhao, Rohan Varma, et al. · 2020 - [Scalable Zero-shot Entity Linking with Dense Entity Retrieval](https://md.research.elamur.ai/free/en/papers/wu-2020-scalable-zero-shot-entity-linking/) — Ledell Wu, Fabio Petroni, Martin Josifoski, et al. · 2020 - [Topic Modeling in Embedding Spaces](https://md.research.elamur.ai/free/en/papers/dieng-2020-topic-modeling-embedding-spaces/) — Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei · 2020 - [Unsupervised Domain Clusters in Pretrained Language Models](https://md.research.elamur.ai/free/en/papers/aharoni-2020-unsupervised-domain-clusters-pretrained-language/) — Roee Aharoni, Yoav Goldberg · 2020 - [Unsupervised Translation of Programming Languages](https://md.research.elamur.ai/free/en/papers/lachaux-2020-unsupervised-translation-programming-languages/) — Marie-Anne Lachaux, Baptiste Roziere, Lowik Chanussot, et al. · 2020 - [Automatic Language Identification in Texts: A Survey](https://md.research.elamur.ai/free/en/papers/jauhiainen-2019-automatic-language-identification-texts/) — Tommi Jauhiainen, Marco Lui, Marcos Zampieri, et al. · 2019 - [Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach](https://md.research.elamur.ai/free/en/papers/yin-2019-benchmarking-zero-shot-text-classification/) — Wenpeng Yin, Jamaal Hay, Dan Roth · 2019 - [Document Expansion by Query Prediction](https://md.research.elamur.ai/free/en/papers/nogueira-2019-document-expansion-query-prediction/) — Rodrigo Nogueira, Wei Yang, Jimmy Lin, et al. · 2019 - [Triton: An Intermediate Language and Compiler for Tiled Neural Network Computations](https://md.research.elamur.ai/free/en/papers/tillet-2019-triton-intermediate-language-compiler-tiled/) — Philippe Tillet, H. T. Kung, David Cox · 2019 - [Learning to Mine Aligned Code and Natural Language Pairs from Stack Overflow](https://md.research.elamur.ai/free/en/papers/yin-2018-learning-mine-aligned-code-natural/) — Pengcheng Yin, Bowen Deng, Edgar Chen, et al. · 2018 - [Mesh-TensorFlow: Deep Learning for Supercomputers](https://md.research.elamur.ai/free/en/papers/shazeer-2018-mesh-tensorflow-deep-learning-supercomputers/) — Noam Shazeer, Youlong Cheng, Niki Parmar, et al. · 2018 - [SentencePiece: A simple and language independent subword tokenizer and detokenizer for Neural Text Processing](https://md.research.elamur.ai/free/en/papers/kudo-2018-sentencepiece-simple-language-independent-subword/) — Taku Kudo, John Richardson · 2018 - [Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task](https://md.research.elamur.ai/free/en/papers/yu-2018-spider-large-scale-human-labeled/) — Tao Yu, Rui Zhang, Kai Yang, et al. · 2018 - [TVM: An Automated End-to-End Optimizing Compiler for Deep Learning](https://md.research.elamur.ai/free/en/papers/chen-2018-tvm-automated-end-end-optimizing/) — Tianqi Chen, Thierry Moreau, Ziheng Jiang, et al. · 2018 - [UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction](https://md.research.elamur.ai/free/en/papers/mcinnes-2018-umap-uniform-manifold-approximation-projection/) — Leland McInnes, John Healy, James Melville · 2018 - [A Syntactic Neural Model for General-Purpose Code Generation](https://md.research.elamur.ai/free/en/papers/yin-2017-syntactic-neural-model-general-purpose/) — Pengcheng Yin, Graham Neubig · 2017 - [Billion-scale similarity search with GPUs](https://md.research.elamur.ai/free/en/papers/johnson-2017-billion-scale-similarity-search-gpus/) — Jeff Johnson, Matthijs Douze, Hervé Jégou · 2017 - [Findings of the VarDial Evaluation Campaign 2017](https://md.research.elamur.ai/free/en/papers/zampieri-2017-findings-vardial-evaluation-campaign/) — Marcos Zampieri, Shervin Malmasi, Nikola Ljubešić, et al. · 2017 [← prev](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) [1](https://md.research.elamur.ai/free/en/shelves/computing/) [2](https://md.research.elamur.ai/free/en/shelves/computing/page/2/) **3** [4](https://md.research.elamur.ai/free/en/shelves/computing/page/4/) [5](https://md.research.elamur.ai/free/en/shelves/computing/page/5/) [next →](https://md.research.elamur.ai/free/en/shelves/computing/page/4/)