---
title: "Who cites NVIDIA A100 Tensor Core GPU Architecture"
description: "129 papers of the Elamur Research library cite «NVIDIA A100 Tensor Core GPU Architecture», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/nvidia-2020-nvidia-a100-tensor-core-gpu/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [NVIDIA A100 Tensor Core GPU Architecture](https://md.research.elamur.ai/free/en/papers/nvidia-2020-nvidia-a100-tensor-core-gpu/) / cited by

# Who cites «NVIDIA A100 Tensor Core GPU Architecture»

129 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · [← back to «NVIDIA A100 Tensor Core GPU Architecture»](https://md.research.elamur.ai/free/en/papers/nvidia-2020-nvidia-a100-tensor-core-gpu/)

1. **[TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings](https://md.research.elamur.ai/free/en/papers/jouppi-2023-tpu-v4-optically-reconfigurable-supercomputer/) [Proceedings - International Symposium on Computer Architecture/Proceedings](https://md.research.elamur.ai/free/en/venues/proceedings-international-symposium-on-computer-architecture-proceedings/)**Norman P. Jouppi; George Kurian; Sheng Li; Peter Ma; Rahul Nagarajan; Lifeng Nai; Nishant Patil; Suvinay Subramanian; Andy Swing; Brian Towles; Cliff Young; Xiang Zhou; Zongwei Zhou;, David Patterson*2023 · 615 citations*
2. **[Sparse GPU Kernels for Deep Learning](https://md.research.elamur.ai/free/en/papers/gale-2020-sparse-gpu-kernels-deep-learning/) [2012 International Conference for High Performance Computing, Networking, Storage and Analysis](https://md.research.elamur.ai/free/en/venues/2012-international-conference-for-high-performance-computing-networking-storage/)**Trevor Gale, Matei Zaharia, Cliff Young, et al.*2020 · 259 citations*
3. [**KernelBench: Can LLMs Write Efficient GPU Kernels? arXiv:2502.10517**Anne Ouyang, Simon Guo, Simran Arora, et al.*2025 · 178 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2025-kernelbench-llms-write-efficient-gpu/)
4. [**Tutel: Adaptive Mixture-of-Experts at Scale MLSys 2023**Changho Hwang, Wei Cui, Yifan Xiong, et al.*2022 · 168 citations*](https://md.research.elamur.ai/free/en/papers/hwang-2022-tutel-adaptive-mixture-experts-scale/)
5. [**Accelerating Sparse Deep Neural Networks arXiv 2021 (NVIDIA)**Asit Mishra, Jorge Albericio Latorre, Jeff Pool, et al.*2021 · 97 citations*](https://md.research.elamur.ai/free/en/papers/mishra-2021-accelerating-sparse-deep-neural-networks/)
6. [**From Decoding to Meta-Generation: Inference-time Algorithms for Large Language Models arXiv:2406.16838**Sean Welleck, Amanda Bertsch, Matthew Finlayson, et al.*2024 · 51 citations*](https://md.research.elamur.ai/free/en/papers/welleck-2024-decoding-meta-generation-inference-time/)

123 more papers of our library cite it; they have no page here yet.

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