RecPipe: Co-designing Models and HW to Jointly Optimize Recommendation Quality and Performance Sunday, February 6, 2022 Deep learning recommendation systems must provide high quality, personalized content under strict tail-latency targets and high system loads. This... Read more about RecPipe: Co-designing Models and HW to Jointly Optimize Recommendation Quality and Performance
Chasing Carbon: The Elusive Environmental Footprint of Computing Sunday, February 6, 2022 Given recent algorithm, software, and hardware innovation, computing has enabled a plethora of new applications. As computing becomes increasingly ubiquitous, however, so... Read more about Chasing Carbon: The Elusive Environmental Footprint of Computing
A 16nm SoC for noise-robust speech recognition via bayesian denoising and attention-based DNNs. Friday, April 2, 2021 This work presents a 16nm SoC that executes a full speech-enhancing ASR pipeline in hardware, with the following key contributions: 1) unsupervised... Read more about A 16nm SoC for noise-robust speech recognition via bayesian denoising and attention-based DNNs.
Cross-Stack Workload Characterization of Deep Recommendation Systems Wednesday, January 20, 2021 Authors: Samuel Hsia, Udit Gupta, Mark Wilkening, Carole-Jean Wu , Gu-Yeon Wei, David Brooks Abstract: Deep learning based recommendation systems... Read more about Cross-Stack Workload Characterization of Deep Recommendation Systems