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12/06/2022
Enabling and Accelerating Dynamic Vision Transformer Inference for Real-Time Applications
Many state-of-the-art deep learning models for computer vision tasks are...
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05/06/2022
Zhuyi: Perception Processing Rate Estimation for Safety in Autonomous Vehicles
The processing requirement of autonomous vehicles (AVs) for high-accurac...
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04/05/2021
GPU Domain Specialization via Composable On-Package Architecture
As GPUs scale their low precision matrix math throughput to boost deep l...
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03/12/2021
Generating and Characterizing Scenarios for Safety Testing of Autonomous Vehicles
Extracting interesting scenarios from real-world data as well as generat...
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06/08/2020
Making Convolutions Resilient via Algorithm-Based Error Detection Techniques
The ability of Convolutional Neural Networks (CNNs) to accurately proces...
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04/28/2020
Estimating Silent Data Corruption Rates Using a Two-Level Model
High-performance and safety-critical system architects must accurately e...
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02/22/2020
HarDNN: Feature Map Vulnerability Evaluation in CNNs
As Convolutional Neural Networks (CNNs) are increasingly being employed ...
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07/01/2019
ML-based Fault Injection for Autonomous Vehicles: A Case for Bayesian Fault Injection
The safety and resilience of fully autonomous vehicles (AVs) are of sign...
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07/01/2019
Kayotee: A Fault Injection-based System to Assess the Safety and Reliability of Autonomous Vehicles to Faults and Errors
Fully autonomous vehicles (AVs), i.e., AVs with autonomy level 5, are ex...
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06/01/2018
Structurally Sparsified Backward Propagation for Faster Long Short-Term Memory Training
Exploiting sparsity enables hardware systems to run neural networks fast...
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05/23/2017
SCNN: An Accelerator for Compressed-sparse Convolutional Neural Networks
Convolutional Neural Networks (CNNs) have emerged as a fundamental techn...
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05/03/2017
Compressing DMA Engine: Leveraging Activation Sparsity for Training Deep Neural Networks
Popular deep learning frameworks require users to fine-tune their memory...
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02/25/2016