Search Results for author: Armin Alaghi

Found 5 papers, 2 papers with code

Neural Network Compression for Noisy Storage Devices

no code implementations15 Feb 2021 Berivan Isik, Kristy Choi, Xin Zheng, Tsachy Weissman, Stefano Ermon, H. -S. Philip Wong, Armin Alaghi

We propose a radically different approach that: (i) employs analog memories to maximize the capacity of each memory cell, and (ii) jointly optimizes model compression and physical storage to maximize memory utility.

Neural Network Compression

Synthesizing Number Generators for Stochastic Computing using Mixed Integer Programming

2 code implementations15 Feb 2019 Vincent T. Lee, Samuel Archibald Elliot, Armin Alaghi, Luis Ceze

Stochastic computing (SC) is a high density, low-power computation technique which encodes values as unary bitstreams instead of binary-encoded (BE) values.

Emerging Technologies

Stochastic Synthesis for Stochastic Computing

1 code implementation10 Oct 2018 Vincent T. Lee, Armin Alaghi, Luis Ceze, Mark Oskin

Stochastic computing (SC) is an emerging computing technique which offers higher computational density, and lower power over binary-encoded (BE) computation.

Emerging Technologies

MATIC: Learning Around Errors for Efficient Low-Voltage Neural Network Accelerators

no code implementations14 Jun 2017 Sung Kim, Patrick Howe, Thierry Moreau, Armin Alaghi, Luis Ceze, Visvesh Sathe

As a result of the increasing demand for deep neural network (DNN)-based services, efforts to develop dedicated hardware accelerators for DNNs are growing rapidly.

Cannot find the paper you are looking for? You can Submit a new open access paper.