Cliff Young

17.5k citations

39 papers · 1.9k indexed · 2 hit papers · h-index 21

Impact in

Hardware and Architecture top 0.5%
- Parallel Computing and Optimization Techniques
- Embedded Systems Design Techniques
Computer Networks and Communications top 1%
- Advanced Data Storage Technologies
- Interconnection Networks and Systems

Papers in ⓘ

Hardware and Architecture 31
- Parallel Computing and Optimization Techniques 31
- Embedded Systems Design Techniques 6
Computer Networks and Communications 22
- Advanced Data Storage Technologies 16
- Distributed and Parallel Computing Systems 5
- Distributed systems and fault tolerance 5

Co-authors: Nishant Patil (7 shared papers)Norman P. Jouppi (7 shared papers)David A. Patterson (6 shared papers)Michael D. Smith (6 shared papers)Joseph A. Fisher (3 shared papers)Paolo Faraboschi (3 shared papers)Michael D. Smith (4 shared papers)George Thomas Kurian (5 shared papers)
Journals: IEEE Micro (4 papers)ACM SIGPLAN Notices (3 papers)Communications of the ACM (2 papers)ACM Transactions on Programming Languages and Systems (1 paper)Proceedings of the IEEE (1 paper)
Partner nations: United States Germany United Kingdom

In The Last Decade

Cliff Young

38 papers receiving 1.8k citations

Hit Papers

align trajectories log scale

TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings 2023 · 215 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2023 TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings
2021 Ten Lessons From Three Generations Shaped Google’s TPUv4i : Industrial Product

Peers

Countries citing papers authored by Cliff Young

Since Specialization

Citations

This map shows the geographic impact of Cliff Young's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cliff Young with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cliff Young more than expected).

Fields of papers citing papers by Cliff Young

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cliff Young. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cliff Young. The network helps show where Cliff Young may publish in the future.

Co-authors

The 25 scholars most cited alongside Cliff Young, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Cliff Young Line = papers co-authored together Cliff Young links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 39 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	TPU v4: An Optically Reconfigurable Supercomputer for Machine Learning with Hardware Support for Embeddings Norman P. Jouppi, George Thomas Kurian, Sheng Li, Peter Ma, Rahul Nagarajan, Lifeng Nai, Nishant Patil, Suvinay Subramanian, Andy Swing, Brian Towles, Cliff Young, Xiang Zhou, Zongwei Zhou, David A. Patterson Hit paper breakdown →	2023	215
2	Ten Lessons From Three Generations Shaped Google’s TPUv4i : Industrial Product Norman P. Jouppi, Doe Hyun Yoon, Matthew B. Ashcraft, Mark Gottscho, Thomas B. Jablin, George Thomas Kurian, James Laudon, Sheng Li, Peter Ma, Xiaoyu Ma, Thomas Norrie, Nishant Patil, Sushma Prasad, Cliff Young, Zongwei Zhou, David A. Patterson Hit paper breakdown →	2021	199
3	Embedded Computing: A VLIW Approach to Architecture, Compilers and Tools Medical Entomology and Zoology ·Joseph A. Fisher, Paolo Faraboschi, Cliff Young	2004	174
4	A domain-specific supercomputer for training deep neural networks Communications of the ACM ·Norman P. Jouppi, Doe Hyun Yoon, George Thomas Kurian, Sheng Li, Nishant Patil, James Laudon, Cliff Young, David A. Patterson	2020	154
5	Motivation for and Evaluation of the First Tensor Processing Unit IEEE Micro ·Norman P. Jouppi, Cliff Young, Nishant Patil, David A. Patterson	2018	136
6	A comparative analysis of schemes for correlated branch prediction Cliff Young, Nicolas Gloy, Michael D. Smith	1995	121
7	A New Golden Age in Computer Architecture: Empowering the Machine-Learning Revolution IEEE Micro ·Jeff Dean, David A. Patterson, Cliff Young	2018	102
8	A domain-specific architecture for deep neural networks Communications of the ACM ·Norman P. Jouppi, Cliff Young, Nishant Patil, David A. Patterson	2018	94
9	The Design Process for Google's Training Chips: TPUv2 and TPUv3 IEEE Micro ·Thomas Norrie, Nishant Patil, Doe Hyun Yoon, George Thomas Kurian, Sheng Li, James Laudon, Cliff Young, Norman P. Jouppi, David A. Patterson	2021	72
10	Planaria: Dynamic Architecture Fission for Spatial Multi-Tenant Acceleration of Deep Neural Networks Soroush Ghodrati, Byung Hoon Ahn, Joon Kyung Kim, Sean Kinzer, Brahmendra Reddy Yatham, Navateja Alla, Hardik Sharma, Mohammad Alian, Eiman Ebrahimi, Nam Sung Kim, Cliff Young, Hadi Esmaeilzadeh	2020	66
11	Improving the accuracy of static branch prediction using branch correlation ACM SIGPLAN Notices ·Cliff Young, Michael D. Smith	1994	65
12	Improving the accuracy of static branch prediction using branch correlation Cliff Young, Michael D. Smith	1994	62
13	Coherence communication prediction in shared-memory multiprocessors Stefanos Kaxiras, Cliff Young	2002	51
14	An analysis of dynamic branch prediction schemes on system workloads Nicolas Gloy, Cliff Young, J. Bradley Chen, Michael D. Smith	1996	45
15	Better global scheduling using path profiles International Symposium on Microarchitecture ·Cliff Young, Michael D. Smith	1998	39
16	Near-optimal intraprocedural branch alignment Cliff Young, David S. Johnson, Michael D. Smith, David R. Karger	1997	34
17	A 32x32x32, spatially distributed 3D FFT in four microseconds on Anton Cliff Young, Joseph A. Bank, Ron O. Dror, J.P. Grossman, John K. Salmon, David E. Shaw	2009	30
18	Instruction scheduling for instruction level parallel processors Proceedings of the IEEE ·Paolo Faraboschi, Joseph A. Fisher, Cliff Young	2001	27
19	Google's Training Chips Revealed: TPUv2 and TPUv3 Thomas Norrie, Nishant Patil, Doe Hyun Yoon, George Thomas Kurian, Sheng Li, James Laudon, Cliff Young, Norman P. Jouppi, David A. Patterson	2020	24
20	Static correlated branch prediction ACM Transactions on Programming Languages and Systems ·Cliff Young, Michael D. Smith	1999	23

About Cliff Young

Cliff Young is a scholar working on Hardware and Architecture, Computer Networks and Communications, Information Systems, Artificial Intelligence and Electrical and Electronic Engineering, having authored 39 papers that have together received 1.9k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (31 papers), Advanced Data Storage Technologies (16 papers), Cloud Computing and Resource Management (6 papers), Embedded Systems Design Techniques (6 papers), Distributed and Parallel Computing Systems (5 papers), Advanced Neural Network Applications (5 papers), Distributed systems and fault tolerance (5 papers) and Software Testing and Debugging Techniques (4 papers). The work is most often cited by research in Hardware and Architecture (1.1k citations), Computer Networks and Communications (825 citations), Computational Mathematics (21 citations), Software (63 citations) and Computer Vision and Pattern Recognition (289 citations). Cliff Young has collaborated with scholars based in United States, Germany and United Kingdom. Frequent co-authors include Nishant Patil, Norman P. Jouppi, David A. Patterson, Michael D. Smith, Joseph A. Fisher, Paolo Faraboschi, Michael D. Smith, George Thomas Kurian, David A. Patterson and Sheng Li. Their work appears in journals such as IEEE Micro, ACM SIGPLAN Notices, Communications of the ACM, ACM Transactions on Programming Languages and Systems and Proceedings of the IEEE.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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