Saketh Rama

According to our database, Saketh Rama authored at least 6 papers between 2016 and 2023.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2023

Early DSE and Automatic Generation of Coarse-grained Merged Accelerators.

Iulian Brumar, Georgios Zacharopoulos, Yuan Yao, Saketh Rama, David Brooks, Gu-Yeon Wei

ACM Trans. Embed. Comput. Syst., March, 2023

2019

Application of Approximate Matrix Multiplication to Neural Networks and Distributed SLAM.

Brian Plancher, Camelia D. Brumar, Iulian Brumar, Lillian Pentecost, Saketh Rama, David Brooks

Proceedings of the 2019 IEEE High Performance Extreme Computing Conference, 2019

2017

Cognitive Computing Safety: The New Horizon for Reliability / The Design and Evolution of Deep Learning Workloads.

Yuhao Zhu, Vijay Janapa Reddi, Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks

IEEE Micro, 2017

14.3 A 28nm SoC with a 1.2GHz 568nJ/prediction sparse deep-neural-network engine with >0.1 timing error rate tolerance for IoT applications.

Paul N. Whatmough, Sae Kyu Lee, Hyunkwang Lee, Saketh Rama, David M. Brooks, Gu-Yeon Wei

Proceedings of the 2017 IEEE International Solid-State Circuits Conference, 2017

2016

Minerva: Enabling Low-Power, Highly-Accurate Deep Neural Network Accelerators.

Brandon Reagen, Paul N. Whatmough, Robert Adolf, Saketh Rama, Hyunkwang Lee, Sae Kyu Lee, José Miguel Hernández-Lobato, Gu-Yeon Wei, David M. Brooks

Proceedings of the 43rd ACM/IEEE Annual International Symposium on Computer Architecture, 2016

Fathom: reference workloads for modern deep learning methods.

Robert Adolf, Saketh Rama, Brandon Reagen, Gu-Yeon Wei, David M. Brooks

Proceedings of the 2016 IEEE International Symposium on Workload Characterization, 2016