Benoit Steiner
Impact in
- Hardware and Architecture top 5%
- Parallel Computing and Optimization Techniques
- Embedded Systems Design Techniques
Papers in
-
- Parallel Computing and Optimization Techniques 5
-
- Advanced Optimization Algorithms Research 1
- Co-authors
- Jonathan Ragan‐Kelley (1 shared paper)Michaël Gharbi (1 shared paper)Riyadh Baghdadi (1 shared paper)Kayvon Fatahalian (1 shared paper)Frédo Durand (1 shared paper)Tzu‐Mao Li (1 shared paper)Hieu Pham (2 shared papers)Anna Goldie (2 shared papers)
- Journals
- ACM Transactions on Graphics (1 paper)Lecture notes in computer science (1 paper)IEEE/ACM International Symposium on Code Generation and Optimization (CGO) (1 paper)International Conference on Learning Representations (1 paper)
- Partner nations
- United States
In The Last Decade
Benoit Steiner
7 papers receiving 303 citations
Peers
Comparison fields: 5 of 19
- Hardware and Architecture 218
- Computational Mathematics 2
- Computer Graphics and Computer-Aided Design 8
- Information Systems 42
- Computer Networks and Communications 33
Countries citing papers authored by Benoit Steiner
This map shows the geographic impact of Benoit Steiner'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 Benoit Steiner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Benoit Steiner more than expected).
Fields of papers citing papers by Benoit Steiner
This network shows the impact of papers produced by Benoit Steiner. 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 Benoit Steiner. The network helps show where Benoit Steiner may publish in the future.
Co-authors
The 20 scholars most cited alongside Benoit Steiner, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2019 | 164 | |
| 2 | A Hierarchical Model for Device Placement | 2018 | 59 |
| 3 | 2022 | 48 | |
| 4 | Value Learning for Throughput Optimization of Deep Learning Workloads | 2021 | 18 |
| 5 | Hierarchical Planning for Device Placement | 2018 | 12 |
| 6 | 2022 | 3 | |
| 7 | 2023 | 1 |
About Benoit Steiner
Benoit Steiner is a scholar working on Hardware and Architecture, Numerical Analysis, Computer Vision and Pattern Recognition, Information Systems and Artificial Intelligence, having authored 7 papers that have together received 305 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (5 papers), Advanced Neural Network Applications (2 papers), Advanced Optimization Algorithms Research (1 paper), Cloud Computing and Resource Management (1 paper), VLSI and FPGA Design Techniques (1 paper), Complexity and Algorithms in Graphs (1 paper), Logic, programming, and type systems (1 paper) and Software Engineering Research (1 paper). The work is most often cited by research in Hardware and Architecture (218 citations), Computational Mathematics (2 citations), Computer Graphics and Computer-Aided Design (8 citations), Information Systems (42 citations) and Computer Networks and Communications (33 citations). Benoit Steiner has collaborated with scholars based in United States. Frequent co-authors include Jonathan Ragan‐Kelley, Michaël Gharbi, Riyadh Baghdadi, Kayvon Fatahalian, Frédo Durand, Tzu‐Mao Li, Hieu Pham, Anna Goldie, Quoc Viet Le and Azalia Mirhoseini. Their work appears in journals such as ACM Transactions on Graphics, Lecture notes in computer science, IEEE/ACM International Symposium on Code Generation and Optimization (CGO) and International Conference on Learning Representations.
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.