Prasanth Chatarasi

707 citations
14 papers · 426 · h-index 8

Impact in

Papers in

Prasanth Chatarasi

13 papers receiving 418 citations

Peers

Prasanth Chatarasi
Comparison fields: 5 of 42
  • Computational Mathematics 20
  • Hardware and Architecture 213
  • Computer Vision and Pattern Recognition 191
  • Computer Networks and Communications 116
  • Electrical and Electronic Engineering 219
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Citations per field
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Citations per year

Countries citing papers authored by Prasanth Chatarasi

Since Specialization
Citations

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

Fields of papers citing papers by Prasanth Chatarasi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 13 scholars most cited alongside Prasanth Chatarasi, 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 Prasanth Chatarasi Line = papers co-authored together Prasanth Chatarasi links everyone, so they are left out of the graph.

All Works

14 of 14 papers shown
#Work
1 2019204
2 2020116
3 202123
4 202122
5 201517
6 202410
7 202110
8 20199
9
A Data-Centric Approach for Modeling and Estimating Efficiency of Dataflows for Accelerator Design
20185
10
Understanding Reuse, Performance, and Hardware Cost of DNN Dataflows: A Data-Centric Approach
20183
11 20183
12
Polyhedral Transformations of Explicitly Parallel Programs
20153
13
MARVEL: A Decoupled Model-driven Approach for Efficiently Mapping Convolutions on Spatial DNN Accelerators.
20201
14 20150

About Prasanth Chatarasi

Prasanth Chatarasi is a scholar working on Hardware and Architecture, Computer Networks and Communications, Artificial Intelligence, Computer Vision and Pattern Recognition and Electrical and Electronic Engineering, having authored 14 papers that have together received 426 indexed citations. Recurring topics across this work include Parallel Computing and Optimization Techniques (12 papers), Advanced Data Storage Technologies (4 papers), Distributed and Parallel Computing Systems (3 papers), Embedded Systems Design Techniques (3 papers), Advanced Neural Network Applications (3 papers), Logic, programming, and type systems (2 papers), Distributed systems and fault tolerance (2 papers) and Cloud Computing and Resource Management (2 papers). The work is most often cited by research in Computational Mathematics (20 citations), Hardware and Architecture (213 citations), Computer Vision and Pattern Recognition (191 citations), Computer Networks and Communications (116 citations) and Electrical and Electronic Engineering (219 citations). Prasanth Chatarasi has collaborated with scholars based in United States and South Korea. Frequent co-authors include Vivek Sarkar, Tushar Krishna, Hyoukjun Kwon, Angshuman Parashar, Michael Pellauer, Jun Shirako, Sivasankaran Rajamanickam, Jeffrey Young, Jason Riedy and Thomas M. Conte. Their work appears in journals such as IEEE Micro, IEEE Transactions on Parallel and Distributed Systems, ACM Transactions on Architecture and Code Optimization, arXiv (Cornell University) and OSTI OAI (U.S. Department of Energy Office of Scientific and Technical Information).

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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