Emerging Neural Workloads and Their Impact on Hardware
- David Brooks
- Martin M. Frank
- et al.
- 2020
- DATE 2020
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20 results for Anand Raghunathan
Dynamic Spike Bundling for Energy-Efficient Spiking Neural Networks
- Sarada Krithivasan
- Sanchari Sen
- et al.
- 2019
- ISLPED 2019
Data Subsetting: A Data-Centric Approach to Approximate Computing
- Younghoon Kim
- Swagath Venkataramani
- et al.
- 2019
- DATE 2019
Ax-BxP: Approximate Blocked Computation for Precision-reconfigurable Deep Neural Network Acceleration
- Reena Elangovan
- Shubham Jain
- et al.
- 2022
- ACM TODAES
Accelerating DNN Training Through Selective Localized Learning
- Sarada Krithivasan
- Sanchari Sen
- et al.
- 2022
- Frontiers in Neuroscience
Resistive Crossbars as Approximate Hardware Building Blocks for Machine Learning: Opportunities and Challenges
- Indranil Chakraborty
- Mustafa Ali
- et al.
- 2020
- Proceedings of the IEEE
DyVEDeep: Dynamic Variable Effort Deep Neural Networks
- Sanjay Ganapathy
- Swagath Venkataramani
- et al.
- 2020
- ACM TECS
Valley-Coupled-Spintronic Non-Volatile Memories with Compute-In-Memory Support
- Sandeep Krishna Thirumala
- Yi Tse Hung
- et al.
- 2020
- IEEE TNANO
Neural network accelerator design with resistive crossbars: Opportunities and challenges
- Shubham Jain
- Aayush Ankit
- et al.
- 2019
- IBM J. Res. Dev
Embedding read-only memory in spin-transfer torque MRAM-based on-chip caches
- Xuanyao Fong
- Rangharajan Venkatesan
- et al.
- 2016
- IEEE Transactions on VLSI Systems