---
title: "Who cites NVIDIA Tesla V100 GPU — 125 citing papers"
description: "125 papers of the Elamur Research library cite «NVIDIA Tesla V100 GPU Architecture», found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/papers/nvidia-2017-nvidia-tesla-v100-gpu-architecture/cited-by/"
---
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[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [NVIDIA Tesla V100 GPU Architecture](https://md.research.elamur.ai/free/en/papers/nvidia-2017-nvidia-tesla-v100-gpu-architecture/) / cited by

# Who cites «NVIDIA Tesla V100 GPU Architecture»

125 papers of our library cite it (of the 149,439 whose bibliographies we read) · 2 with a page here, the most cited first · [← back to «NVIDIA Tesla V100 GPU Architecture»](https://md.research.elamur.ai/free/en/papers/nvidia-2017-nvidia-tesla-v100-gpu-architecture/)

1. [**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/)
2. [**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.

- [← back to](https://md.research.elamur.ai/free/en/papers/nvidia-2017-nvidia-tesla-v100-gpu-architecture/) — NVIDIA Tesla V100 GPU Architecture