N. Jouppi

Artificial Intelligence · 2000–2023

A researcher in the Science corpus: 14 papers; trusts 28 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it
• Computer Vision and Pattern Recognition — 47 citations into it
• Computer Networks and Communications — 46 citations into it; #4,083 of 9,886 by trust here, #1,275 by citations
• Electrical and Electronic Engineering — 45 citations into it; #6,216 of 16,539 by trust here, #5,811 by citations
• Efficiency & Compression — 20 citations into it
• Model Architectures — 19 citations into it

Whom N. Jouppi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Sergey Ioffe
2. Christian Szegedy
3. Samuel Williams
4. Kaustav Banerjee
5. Joseph Dean
6. Ashish Vaswani
7. Naveen Mellempudi
8. Geoffrey E. Hinton
9. Quoc V. Le
10. Kaiming He

Who trusts N. Jouppi overall

1. Rajeev Balasubramonian
2. Naveen Muralimanohar
3. Yi Tay
4. Weiping Liao
5. Sheng Li
6. Wenhu Chen
7. Edward Suh
8. Mostafa Dehghani
9. Zhehuai Chen
10. Shuangchen Li

Papers from N. Jouppi's perspective

Ordered by how strongly the researchers N. Jouppi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet Large Scale Visual Recognition Challenge
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Gradient-based learning applied to document recognition
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• A domain-specific supercomputer for training deep neural networks (2020) — 294 citations
• Ten Lessons From Three Generations Shaped Google’s TPUv4i : Industrial Product (2021) — 445 citations
• Searching for Fast Model Families on Datacenter Accelerators (2021) — 40 citations
• McPAT: An integrated power, area, and timing modeling framework for multicore and manycore architectures (2009) — 2,322 citations
• NVSim: A Circuit-Level Performance, Energy, and Area Model for Emerging Nonvolatile Memory (2012) — 1,223 citations
• Single-ISA heterogeneous multi-core architectures: the potential for processor power reduction (2003) — 886 citations
• Reconfigurable caches and their application to media processing (2000) — 300 citations
• CACTI-P: Architecture-level modeling for SRAM-based structures with advanced leakage reduction techniques (2011) — 298 citations
• TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings (2023) — 685 citations
• CACTI 6.0: A Tool to Model Large Caches (2009) — 1,102 citations
• Optimizing NUCA Organizations and Wiring Alternatives for Large Caches with CACTI 6.0 (2007) — 803 citations
• Heterogeneous chip multiprocessors (2005) — 388 citations
• Single-ISA heterogeneous multi-core architectures for multithreaded workload performance (2004) — 364 citations
• Cacti 3. 0: an integrated cache timing, power, and area model (2001) — 804 citations