Development of a wireless sensor network for animal management: Experiences with Moosense. - Sanat Sarangi; Akshat Bisht; Vijay Rao; Subrat Kar; Tushar Kumar Mohanty; Anand Prakash Ruhil (IEEE ANTS, 2014)

Pratham: A Low-Cost Wireless Node with Programmable Radio Range and Over-the-Air Programming Capability for Resource-Constrained Applications. - Vijay Rao; P. P. Priyesh; Subrat Kar (ISED, 2014)

Adaptive Transmission Power Protocol for heterogeneous Wireless Sensor Networks. - Vijay Rao; Priyesh P. P; Subrat Kar (NCC, 2015)

VCX: An industry initiative to create an objective camera module evaluation for mobile devices. - Dietmar Wueller; Uwe Artmann; Vijay Rao; Guenter Reif; Jörg Kramer; Fabian Knauf (Photography, Mobile, and Immersive Imaging, 2018)

Deep Learning Inference in Facebook Data Centers: Characterization, Performance Optimizations and Hardware Implications. - Jongsoo Park; Maxim Naumov; Protonu Basu; Summer Deng; Aravind Kalaiah; Daya Shanker Khudia; James Law; Parth Malani; Andrey Malevich; Nadathur Satish; Juan Miguel Pino; Martin Schatz; et al. (CoRR, 2018)

Deep Learning Recommendation Model for Personalization and Recommendation Systems. - Maxim Naumov; Dheevatsa Mudigere; Hao-Jun Michael Shi; Jianyu Huang; Narayanan Sundaraman; Jongsoo Park; Xiaodong Wang 020; Udit Gupta; Carole-Jean Wu; Alisson G. Azzolini; Dmytro Dzhulgakov; Andrey Mallevich; et al. (CoRR, 2019)

Energy efficient routing in wireless sensor networks via circulating operator packets. - Vijay Rao; Subrat Kar (Wirel. Networks, 2019)

High-performance, Distributed Training of Large-scale Deep Learning Recommendation Models. - Dheevatsa Mudigere; Yuchen Hao; Jianyu Huang; Andrew Tulloch; Srinivas Sridharan 002; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; Leon Gao; et al. (CoRR, 2021)

Supporting Massive DLRM Inference Through Software Defined Memory. - Ehsan K. Ardestani; Changkyu Kim; Seung Jae Lee; Luoshang Pan; Valmiki Rampersad; Jens Axboe; Banit Agrawal; Fuxun Yu; Ansha Yu; Trung Le 003; Hector Yuen; Shishir Juluri; et al. (CoRR, 2021)

Supporting Massive DLRM Inference through Software Defined Memory. - Ehsan K. Ardestani; Changkyu Kim; Seung Jae Lee; Luoshang Pan; Jens Axboe; Valmiki Rampersad; Banit Agrawal; Fuxun Yu; Ansha Yu; Trung Le 003; Hector Yuen; Dheevatsa Mudigere; et al. (ICDCS, 2022)

Software-hardware co-design for fast and scalable training of deep learning recommendation models. - Dheevatsa Mudigere; Yuchen Hao; Jianyu Huang; Zhihao Jia; Andrew Tulloch; Srinivas Sridharan 002; Xing Liu; Mustafa Ozdal; Jade Nie; Jongsoo Park; Liang Luo; Jie Amy Yang; et al. (ISCA, 2022)

MTIA: First Generation Silicon Targeting Meta's Recommendation Systems. - Amin Firoozshahian; Joel Coburn; Roman Levenstein; Rakesh Nattoji; Ashwin Kamath; Olívia Wu; Gurdeepak Grewal; Harish Aepala; Bhasker Jakka; Bob Dreyer; Adam Hutchin; Utku Diril; et al. (ISCA, 2023)