30 citations · 45 across the 4 of their papers we have counts for
5 papers
DaCapo: Accelerating Continuous Learning in Autonomous Systems for Video Analytics
Yoonsung Kim, Changhun Oh, Jinwoo Hwang +6
Deep neural network (DNN) video analytics is crucial for autonomous systems such as self-driving vehicles, unmanned aerial vehicles (UAVs), and security robots. However, real-world…
In-Storage Domain-Specific Acceleration for Serverless Computing
Rohan Mahapatra, Soroush Ghodrati, Byung Hoon Ahn +8
While (1) serverless computing is emerging as a popular form of cloud execution, datacenters are going through major changes: (2) storage dissaggregation in the system infrastructu…
Bit-Parallel Vector Composability for Neural Acceleration
Soroush Ghodrati, Hardik Sharma, Cliff Young +2
Conventional neural accelerators rely on isolated self-sufficient functional units that perform an atomic operation while communicating the results through an operand delivery-aggr…
Mixed-Signal Charge-Domain Acceleration of Deep Neural networks through Interleaved Bit-Partitioned Arithmetic
Soroush Ghodrati, Hardik Sharma, Sean Kinzer +5
Low-power potential of mixed-signal design makes it an alluring option to accelerate Deep Neural Networks (DNNs). However, mixed-signal circuitry suffers from limited range for inf…
Bit Fusion: Bit-Level Dynamically Composable Architecture for Accelerating Deep Neural Networks
Hardik Sharma, Jongse Park, Naveen Suda +5
Fully realizing the potential of acceleration for Deep Neural Networks (DNNs) requires understanding and leveraging algorithmic properties. This paper builds upon the algorithmic i…