Febin P. Sunny
PhD candidate ,
Electrical and Computer Engineering Department,
Colorado State University,
Fort Collins , CO
Areas of research
Silicon nano-photonics
Photonic machine learning inference accelerator design
Photonic Network-on-Chips
Education
PhD Candidate, Electrical and Computer engineering department,
Colorado State University, CO, USA (expected Spring 2023)Jointly advised by Prof. Sudeep Pasricha (advisor) and Prof. Mahdi Nikdast (co-advisor)
Bachelor of Technology, Electronics and telecommunications engineering, (graduated Spring 2014)
Mahatma Gandhi University, Kottayam, Kerala, India
Publications
F. Sunny, A. Shafiee, M. Nikdast, S. Pasricha, “COMET: A Cross-Layer Optimized Optical Phase Change Main Memory Architecture,” under review, IEEE/ACM International Conference on Computer-Aided Design (ICCAD), 2023.
F. Sunny, M. Nikdast, S. Pasricha, “Cross-Layer Design for AI Acceleration with Non-Coherent Optical Computing”, to appear, ACM Great Lakes Symposium on VLSI (GLSVLSI), 2023
A. Salma, F. Sunny, M. Nikdast, S. Pasricha, “TRON: Transformer Neural Network Acceleration with Non-Coherent Silicon Photonics,” to appear, ACM Great Lakes Symposium on VLSI (GLSVLSI), 2023
A. Balasubramaniam, F. Sunny, S. Pasricha, “R-TOSS: A Framework for Real-Time Object Detection using Semi-Structured Pruning,” to appear, IEEE/ACM Design Automation Conference (DAC), 2023
F. Sunny, E. Taheri, M. Nikdast, S. Pasricha, “Machine Learning Acceleration in 2.5D Interposer Platforms with Silicon Photonics”, to appear, IEEE/ACM Design and Test in Europe Conference and Exhibition (DATE), 2023
F. Sunny, M. Nikdast, S. Pasricha, “RecLight: A Recurrent Neural Network Accelerator with Integrated Silicon Photonics,” in IEEE Computer Society Annual Symposium on VLSI (ISVLSI) 2022
F. Sunny, M. Nikdast, S. Pasricha, “A Silicon Photonic Accelerator for Convolutional Neural Networks with Heterogeneous Quantization,” ACM Great Lakes Symposium on VLSI (GLSVLSI), 2022
V. S. P. Karempudi, F. Sunny, I. G. Thakkar, S. V. R. Chittamuru, M. Nikdast, S. Pasricha, “Photonic Networks-on-Chip Employing Multilevel Signaling: A Cross-Layer Comparative Study,” ACM Journal on Emerging Technologies in Computing Systems (JETC), 2022
F. Sunny, M. Nikdast, S. Pasricha, “SONIC: A Sparse Neural Network Inference Accelerator with Silicon Photonics for Energy-Efficient Deep Learning,” in IEEE/ACM ASPDAC 2022
F. Sunny, A. Mirza, M. Nikdast, and S. Pasricha, “ROBIN: A Robust Optical Binary Neural Network Accelerator,” in ACM CASES 2021
F. Sunny, A. Mirza, M. Nikdast, and S. Pasricha, “CrossLight: A Cross-Layer Optimized Silicon Photonic Neural Network Accelerator,” IEEE/ACM Design Automation Conference (DAC), 2021
A. Mirza, F. Sunny, P. Walsh, K. Hassan, S. Pasricha, M. Nikdast, “Silicon photonic microring resonators: A comprehensive design-space exploration and optimization under fabrication-process variations,” IEEE Transactions on Computer-Aided Design of Integrated Circuits and Systems (TCAD), vol. 41, no. 10, 2021
A. Shafiee, A. Mirza, F. Sunny, S. Banerjee, K. Chakrabarty, S. Pasricha, M. Nikdast, “Inexact Silicon Photonics: From Devices to Applications,” Photonics in Switching and Computing, 2021
F. Sunny, E. Taheri, M. Nikdast, and S. Pasricha, “A Survey on Silicon Photonics for Deep Learning,” ACM Journal on Emerging Technologies in Computing Systems (JETC), vol. 17, no.4, October 2021
F. Sunny, A. Mirza, I. Thakkar2, S. Pasricha, and M. Nikdast, “ARXON: A Framework for Approximate Communication over Photonic Networks-on-Chip,” IEEE Transactions on Very Large Scale Integration Systems (TVLSI), vol. 29, no. 6, June 2021
F. Sunny, A. Mirza, I. Thakkar, S. Pasricha, and M. Nikdast, “LORAX: Loss-Aware Approximations for Energy-Efficient Silicon Photonic Networks-on-Chip,” ACM Great Lakes Symposium on VLSI (GLSVLSI), 2020 (3rd Best Paper Award)
A. Mirza, F. Sunny, S. Pasricha, M. Nikdast, “Silicon photonic microring resonators: Design optimization under fabrication non-uniformity,” IEEE/ACM Design and Test in Europe Conference and Exhibition (DATE), 2020
Professional Experience
Graduate Research Assistant: Cyberinfrastructure and Research Computing Consultant (Alpine HPC Cluster) (Current)
Consultation for CSU and CU Boulder research projects that use Alpine HPC system
Works on automation scripts for job scheduling, help improve system efficiency, and to provide automated reports
Software documentation and user help documentation
Graduate Research Assistant, under Dr. Sudeep Pasricha at Colorado State University (Current)
Embedded, High Performance and Intelligent Computing (EPIC) Lab
Ongoing research involves design, modeling and optimization of energy-efficient, reliable and low-latency on-chip communication architectures, using silicon photonics technology, for multi-core computing chips; machine learning inference accelerator architectures using silicon photonics;
Works with: C, C++ (SystemC for system modeling), Python, Bash Scripting.
Machine learning libraries used: Tensorflow, Keras, PyTorch, scikit-learn, thunderSVM
Graduate Teaching Assistant
CS/ECE561: Hardwrae/Software Design of Embedded Systems (SP'2023)
CS/ECE528: Embedded Systems and Machine Learning (FA' 2021)
ECE102: Digital Circuit Logic (SP' 2021)
ECE452: Computer Organization and Architecture (SP' 2020)
AI Solutions Architect– Intern (Micron Technologies Inc., Folsom, CA) (May 2022 to Dec 2022)
Performed system-level analysis and benchmarking of proprietary and competitor AI accelerator hardware
Developed proof-of-concept neural network applications for the accelerator
Developed a remote evaluation tool for the AI accelerator for customers
Assisted with various market segment analysis tasks and provided technical analysis for venture capital endeavors
Filed for various patents
Embedded Software Engineer (Danlaw Inc., Bengaluru, KA, India) (Oct 2016 to Jun 2018)
Developed Nordic stack based BLE beacons.
Developed a Tire Pressure Monitoring System POC. Responsible for project from design to functional and system testing.
Responsible for developing Bluetooth based applications using BlueZ in Linux environment.
Implemented GPS tracking system for Gen 3.5 Datalogger devices, which uses Legato framework on Linux platform and Qualcomm modems.
Worked with C and C++ primarily
Systems Software Engineer (Infosys Ltd., Thiruvananthapuram, Kerala, India) (Jun 2014 to May 2016)
Worked as Systems Engineer, in 2 projects for RCLADM division of Infosys;
Clients: Sears, Dick's Sporting Goods (DSG)
Responsibilities involved: developing software, monitoring live project, assisting in application updates/patches when needed.
Worked on Java technology and IBM websphere.
Achievements
3rd Best paper award at ACM Great Lakes Symposium on VLSI 2020
IEEE/ACM Design Automation Conference Young Fellow at IEEE/ACM Design Automation Conference 2020
IEEE/ACM DAC Richard Newton Young Fellow at IEEE/ACM Design and Automation Conference 2019
Walter Scott Jr. PhD Fellowship 2019 at Colorado State University
Memberships
Student member, Institute of Electrical and Electronics Engineers (IEEE)
Student member, Association of Computer Machinery (ACM)
Conferences attended
IEEE Optical Interconnects Conference (Santa Fe, NM, USA, April 2019)
Silicon Photonics for High Performance Computing (SPHPC) workshop (Estes Park, CO, USA, May 2019)
IEEE/ACM Design Automation Conference (DAC) (Las Vegas, NV, USA, June 2019)
IEEE/ACM International Symposium on Networks-on-Chip (NOCS) (New York, NY, October 2019)
ACM Great Lakes Symposium on VLSI (GLSVLSI) (virtual conference, Beijing, China, September 2020)
IEEE/ACM Design Automation Conference (DAC) (virtual conference, San Francisco, CA, USA, July 2020)
IEEE/ACM Design Automation Conference (DAC) (San Francisco, CA, USA, July 2021)
ACM Great Lakes Symposium on VLSI (GLSVLSI) (San Diego, CA, USA, June 2022)