Gregory Diamos

4.4k citations
29 papers · 1.3k · h-index 20

Impact in

Papers in

Gregory Diamos

29 papers receiving 1.2k citations

Peers

Gregory Diamos
Comparison fields: 5 of 80
  • Hardware and Architecture 805
  • Computer Networks and Communications 826
  • Signal Processing 192
  • Information Systems 266
  • Computer Vision and Pattern Recognition 228
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Won Woo Ro South Korea
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Citations per year

Countries citing papers authored by Gregory Diamos

Since Specialization
Citations

This map shows the geographic impact of Gregory Diamos'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 Gregory Diamos with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gregory Diamos more than expected).

Fields of papers citing papers by Gregory Diamos

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gregory Diamos. 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 Gregory Diamos. The network helps show where Gregory Diamos may publish in the future.

Co-authors

The 25 scholars most cited alongside Gregory Diamos, 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 Gregory Diamos Line = papers co-authored together Gregory Diamos links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 29 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2010163
2 2008111
3 200996
4
Deep Voice 2: Multi-Speaker Neural Text-to-Speech.
201781
5 201273
6 201069
7 201868
8
Mixed Precision Training
201762
9 201161
10 201251
11 201946
12 201445
13
Deep Voice: Real-time Neural Text-to-Speech
201739
14 201139
15 201437
16
Persistent RNNs: stashing recurrent weights on-chip
201636
17 201236
18 201234
19
Efficient Relational Algebra Algorithms and Data Structures for GPU
201227
20
Translating GPU Binaries to Tiered SIMD Architectures with Ocelot
200922

About Gregory Diamos

Gregory Diamos is a scholar working on Computer Networks and Communications, Hardware and Architecture, Signal Processing, Artificial Intelligence and Computer Vision and Pattern Recognition, having authored 29 papers that have together received 1.3k indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (18 papers), Advanced Data Storage Technologies (12 papers), Distributed and Parallel Computing Systems (12 papers), Advanced Database Systems and Queries (6 papers), Speech Recognition and Synthesis (5 papers), Data Management and Algorithms (4 papers), Embedded Systems Design Techniques (3 papers) and Music and Audio Processing (3 papers). The work is most often cited by research in Hardware and Architecture (805 citations), Computer Networks and Communications (826 citations), Signal Processing (192 citations), Information Systems (266 citations) and Computer Vision and Pattern Recognition (228 citations). Gregory Diamos has collaborated with scholars based in United States, United Kingdom and China. Frequent co-authors include Sudhakar Yalamanchili, Andrew Kerr, Haicheng Wu, Nathan Clark, Sercan Ö. Arık, Nicolas Brunie, Caroline Collange, Srihari Cadambi, Heewoo Jun and Joel Hestness. Their work appears in journals such as IEEE Signal Processing Letters, The International Journal of High Performance Computing Applications, HAL (Le Centre pour la Communication Scientifique Directe), arXiv (Cornell University) and International Conference on Machine Learning.

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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