Suchit Subhaschandra

763 total citations · 1 hit paper
8 papers, 518 citations indexed

About

Suchit Subhaschandra is a scholar working on Hardware and Architecture, Electrical and Electronic Engineering and Computer Networks and Communications. According to data from OpenAlex, Suchit Subhaschandra has authored 8 papers receiving a total of 518 indexed citations (citations by other indexed papers that have themselves been cited), including 7 papers in Hardware and Architecture, 6 papers in Electrical and Electronic Engineering and 2 papers in Computer Networks and Communications. Recurrent topics in Suchit Subhaschandra's work include Parallel Computing and Optimization Techniques (7 papers), Embedded Systems Design Techniques (5 papers) and Low-power high-performance VLSI design (4 papers). Suchit Subhaschandra is often cited by papers focused on Parallel Computing and Optimization Techniques (7 papers), Embedded Systems Design Techniques (5 papers) and Low-power high-performance VLSI design (4 papers). Suchit Subhaschandra collaborates with scholars based in United Kingdom, United States and Australia. Suchit Subhaschandra's co-authors include Eriko Nurvitadhi, Jaewoong Sim, Duncan J. M. Moss, Debbie Marr, Srivatsan Krishnan, Guy Boudoukh, Ganesh Venkatesh, Randy Huang, Philip H. W. Leong and Asit Mishra and has published in prestigious journals such as .

In The Last Decade

Suchit Subhaschandra

8 papers receiving 500 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?

2017 287 citations Eriko Nurvitadhi, Ganesh Venkatesh et al. profile →

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name	h						Papers	Cites
Suchit Subhaschandra United Kingdom	7	239	221	213	171	143	8	518
Thomas B. Preußer Germany	11	199 0.8×	148 0.7×	201 0.9×	111 0.6×	160 1.1×	35	486
David Sheffield United States	8	235 1.0×	196 0.9×	212 1.0×	147 0.9×	171 1.2×	14	552
Robert Adolf United States	7	427 1.8×	295 1.3×	347 1.6×	190 1.1×	227 1.6×	11	783
Ritchie Zhao United States	12	297 1.2×	263 1.2×	317 1.5×	181 1.1×	180 1.3×	15	660
Meghan Cowan United States	4	156 0.7×	313 1.4×	223 1.0×	132 0.8×	251 1.8×	6	568
Xuan Yang United States	9	385 1.6×	292 1.3×	257 1.2×	131 0.8×	149 1.0×	18	640
Randy Huang United States	8	278 1.2×	154 0.7×	271 1.3×	202 1.2×	96 0.7×	14	539
Emmanuel Amaro United States	8	299 1.3×	211 1.0×	317 1.5×	242 1.4×	180 1.3×	15	674
Ramyad Hadidi United States	15	261 1.1×	314 1.4×	329 1.5×	391 2.3×	210 1.5×	31	781
Divya Mahajan United States	13	536 2.2×	266 1.2×	380 1.8×	205 1.2×	213 1.5×	31	873

Countries citing papers authored by Suchit Subhaschandra

Since Specialization

Citations

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

Fields of papers citing papers by Suchit Subhaschandra

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Suchit Subhaschandra

This figure shows the co-authorship network connecting the top 25 collaborators of Suchit Subhaschandra. A scholar is included among the top collaborators of Suchit Subhaschandra based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Suchit Subhaschandra. Suchit Subhaschandra is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

8 of 8 papers shown

1.

Krishnan, Srivatsan, et al.. (2018). A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+FPGA Platform A Deep Learning Case Study. 107–116. 7 indexed citations

2.

Moss, Duncan J. M., Srivatsan Krishnan, Eriko Nurvitadhi, et al.. (2018). A Customizable Matrix Multiplication Framework for the Intel HARPv2 Xeon+FPGA Platform. 107–116. 60 indexed citations

3.

Ling, Andrew C., et al.. (2018). Harnessing Numerical Flexibility for Deep Learning on FPGAs. 1–3. 2 indexed citations

4.

Nurvitadhi, Eriko, Ganesh Venkatesh, Jaewoong Sim, et al.. (2017). Can FPGAs Beat GPUs in Accelerating Next-Generation Deep Neural Networks?. 5–14. 287 indexed citations breakdown →

5.

Moss, Duncan J. M., Eriko Nurvitadhi, Jaewoong Sim, et al.. (2017). High performance binary neural networks on the Xeon+FPGA™ platform. 1–4. 47 indexed citations

6.

Nurvitadhi, Eriko, Davor Capalija, Andrew C. Ling, et al.. (2017). Customizable FPGA OpenCL matrix multiply design template for deep neural networks. 259–262. 10 indexed citations

7.

Hahn, Scott, Prabhat Gupta, Dheeraj Reddy, et al.. (2012). QuickIA: Exploring heterogeneous architectures on real prototypes. 1–8. 62 indexed citations

8.

Sharma, Rahul, et al.. (2011). A Reconfigurable Computing System Based on a Cache-Coherent Fabric. 80–85. 43 indexed citations

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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