Search Results for author: Hardik Sharma

Found 5 papers, 1 papers with code

DaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics

no code implementations21 Mar 2024 Yoonsung Kim, Changhun Oh, Jinwoo Hwang, Wonung Kim, Seongryong Oh, Yubin Lee, Hardik Sharma, Amir Yazdanbakhsh, Jongse Park

Deep neural network (DNN) video analytics is crucial for autonomous systems such as self-driving vehicles, unmanned aerial vehicles (UAVs), and security robots.

CoVA: Exploiting Compressed-Domain Analysis to Accelerate Video Analytics

1 code implementation2 Jul 2022 Jinwoo Hwang, Minsu Kim, Daeun Kim, Seungho Nam, Yoonsung Kim, Dohee Kim, Hardik Sharma, Jongse Park

This paper presents CoVA, a novel cascade architecture that splits the cascade computation between compressed domain and pixel domain to address the decoding bottleneck, supporting both temporal and spatial queries.

Bit-Parallel Vector Composability for Neural Acceleration

no code implementations11 Apr 2020 Soroush Ghodrati, Hardik Sharma, Cliff Young, Nam Sung Kim, Hadi Esmaeilzadeh

This paper explores a different design style, where each unit is only responsible for a slice of the bit-level operations to interleave and combine the benefits of bit-level parallelism with the abundant data-level parallelism in deep neural networks.

Mixed-Signal Charge-Domain Acceleration of Deep Neural networks through Interleaved Bit-Partitioned Arithmetic

no code implementations27 Jun 2019 Soroush Ghodrati, Hardik Sharma, Sean Kinzer, Amir Yazdanbakhsh, Kambiz Samadi, Nam Sung Kim, Doug Burger, Hadi Esmaeilzadeh

Low-power potential of mixed-signal design makes it an alluring option to accelerate Deep Neural Networks (DNNs).

Hardware Architecture

Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks

no code implementations5 Dec 2017 Hardik Sharma, Jongse Park, Naveen Suda, Liangzhen Lai, Benson Chau, Joon Kyung Kim, Vikas Chandra, Hadi Esmaeilzadeh

Compared to Stripes, BitFusion provides 2. 6x speedup and 3. 9x energy reduction at 45 nm node when BitFusion area and frequency are set to those of Stripes.

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