171 citations · 296 across the 16 of their papers we have counts for
6 papers · 1 filter
EdgeBERT: Sentence-Level Energy Optimizations for Latency-Aware Multi-Task NLP Inference
Thierry Tambe, Coleman Hooper, Lillian Pentecost +8
Transformer-based language models such as BERT provide significant accuracy improvement for a multitude of natural language processing (NLP) tasks. However, their hefty computation…
Chasing Carbon: The Elusive Environmental Footprint of Computing
Udit Gupta, Young Geun Kim, Sylvia Lee +5
Given recent algorithm, software, and hardware innovation, computing has enabled a plethora of new applications. As computing becomes increasingly ubiquitous, however, so does its…
Cross-Stack Workload Characterization of Deep Recommendation Systems
Samuel Hsia, Udit Gupta, Mark Wilkening +3
Deep learning based recommendation systems form the backbone of most personalized cloud services. Though the computer architecture community has recently started to take notice of…
Cheetah: Optimizing and Accelerating Homomorphic Encryption for Private Inference
Brandon Reagen, Wooseok Choi, Yeongil Ko +4
As the application of deep learning continues to grow, so does the amount of data used to make predictions. While traditionally, big-data deep learning was constrained by computing…
DeepRecSys: A System for Optimizing End-To-End At-scale Neural Recommendation Inference
Udit Gupta, Samuel Hsia, Vikram Saraph +6
Neural personalized recommendation is the corner-stone of a wide collection of cloud services and products, constituting significant compute demand of the cloud infrastructure. Thu…
CHIPKIT: An agile, reusable open-source framework for rapid test chip development
Paul Whatmough, Marco Donato, Glenn Ko +3
The current trend for domain-specific architectures (DSAs) has led to renewed interest in research test chips to demonstrate new specialized hardware. Tape-outs also offer huge ped…