3 papers
cs.CL2022
Accelerating Attention through Gradient-Based Learned Runtime Pruning
Zheng Li, Soroush Ghodrati, Amir Yazdanbakhsh +2
Self-attention is a key enabler of state-of-art accuracy for various transformer-based Natural Language Processing models. This attention mechanism calculates a correlation score f…
cs.LG2020
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…
cs.AR2019
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…