activity
20162022
most citedBenchmarking TPU, GPU, and CPU Platforms for Deep Learning

233 citations · 833 across the 22 of their papers we have counts for

collaborators
Showing 2021Show all

8 papers · 1 filter

cs.ET2021★ 1 cited

NVMExplorer: A Framework for Cross-Stack Comparisons of Embedded Non-Volatile Memories

Lillian Pentecost, Alexander Hankin, Marco Donato +3

Repeated off-chip memory accesses to DRAM drive up operating power for data-intensive applications, and SRAM technology scaling and leakage power limits the efficiency of embedded…

cs.DC2021

Application-driven Design Exploration for Dense Ferroelectric Embedded Non-volatile Memories

Mohammad Mehdi Sharifi, Lillian Pentecost, Ramin Rajaei +8

The memory wall bottleneck is a key challenge across many data-intensive applications. Multi-level FeFET-based embedded non-volatile memories are a promising solution for denser an…

cs.CR2021★ 11 cited

Gradient Disaggregation: Breaking Privacy in Federated Learning by Reconstructing the User Participant Matrix

Maximilian Lam, Gu-Yeon Wei, David Brooks +2

We show that aggregated model updates in federated learning may be insecure. An untrusted central server may disaggregate user updates from sums of updates across participants give…

cond-mat.mes-hall2021★ 92 cited

Logic Compatible High-Performance Ferroelectric Transistor Memory

Sourav Dutta, Huacheng Ye, Abhishek Khanna +11

Silicon ferroelectric field-effect transistors (FeFETs) with low-k interfacial layer (IL) between ferroelectric gate stack and silicon channel suffers from high write voltage, limi…

cs.AR2021

RecPipe: Co-designing Models and Hardware to Jointly Optimize Recommendation Quality and Performance

Udit Gupta, Samuel Hsia, Jeff Zhang +6

Deep learning recommendation systems must provide high quality, personalized content under strict tail-latency targets and high system loads. This paper presents RecPipe, a system…

cs.RO2021★ 5 cited

MAVFI: An End-to-End Fault Analysis Framework with Anomaly Detection and Recovery for Micro Aerial Vehicles

Yu-Shun Hsiao, Zishen Wan, Tianyu Jia +6

Safety and resilience are critical for autonomous unmanned aerial vehicles (UAVs). We introduce MAVFI, the micro aerial vehicles (MAVs) resilience analysis methodology to assess th…

cs.RO2021★ 3 cited

AutoPilot: Automating SoC Design Space Exploration for SWaP Constrained Autonomous UAVs

Srivatsan Krishnan, Zishen Wan, Kshitij Bhardwaj +6

Building domain-specific accelerators for autonomous unmanned aerial vehicles (UAVs) is challenging due to a lack of systematic methodology for designing onboard compute. Balancing…

cs.AR2021★ 4 cited

RecSSD: Near Data Processing for Solid State Drive Based Recommendation Inference

Mark Wilkening, Udit Gupta, Samuel Hsia +4

Neural personalized recommendation models are used across a wide variety of datacenter applications including search, social media, and entertainment. State-of-the-art models compr…