no code implementations • 25 Jun 2023 • Haolan Liu, Liangjun Zhang, Siva Kumar Sastry Hari, Jishen Zhao
Generating safety-critical scenarios is essential for testing and verifying the safety of autonomous vehicles.
no code implementations • 6 May 2022 • Yu-Shun Hsiao, Siva Kumar Sastry Hari, Michał Filipiuk, Timothy Tsai, Michael B. Sullivan, Vijay Janapa Reddi, Vasu Singh, Stephen W. Keckler
The processing requirement of autonomous vehicles (AVs) for high-accuracy perception in complex scenarios can exceed the resources offered by the in-vehicle computer, degrading safety and comfort.
no code implementations • 12 Mar 2021 • Zahra Ghodsi, Siva Kumar Sastry Hari, Iuri Frosio, Timothy Tsai, Alejandro Troccoli, Stephen W. Keckler, Siddharth Garg, Anima Anandkumar
Extracting interesting scenarios from real-world data as well as generating failure cases is important for the development and testing of autonomous systems.
no code implementations • 8 Jun 2020 • Siva Kumar Sastry Hari, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler
The ability of Convolutional Neural Networks (CNNs) to accurately process real-time telemetry has boosted their use in safety-critical and high-performance computing systems.
no code implementations • 22 Feb 2020 • Abdulrahman Mahmoud, Siva Kumar Sastry Hari, Christopher W. Fletcher, Sarita V. Adve, Charbel Sakr, Naresh Shanbhag, Pavlo Molchanov, Michael B. Sullivan, Timothy Tsai, Stephen W. Keckler
As Convolutional Neural Networks (CNNs) are increasingly being employed in safety-critical applications, it is important that they behave reliably in the face of hardware errors.