A Scalable Multi-TeraOPS Deep Learning Processor Core for AI Trainina and Inference
- Bruce Fleischer
- Sunil Shukla
- et al.
- 2018
- VLSI Circuits 2018
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60 results for Vijayalakshmi Srinivasan
Compensated-DNN: Energy efficient low-precision deep neural networks by compensating quantization errors
- Shubham Jain
- Swagath Venkataramani
- et al.
- 2018
- DAC 2018
Exploiting approximate computing for deep learning acceleration
- Chia-Yu Chen
- Jungwook Choi
- et al.
- 2018
- DATE 2018
POSTER: Design Space Exploration for Performance Optimization of Deep Neural Networks on Shared Memory Accelerators
- Swagath Venkataramani
- Jungwook Choi
- et al.
- 2017
- PACT 2017
INVITED: Accelerator Design for Deep Learning Training: Extended Abstract: Invited
- Ankur Agrawal
- Chia-Yu Chen
- et al.
- 2017
- DAC 2017
Needle: Leveraging Program Analysis to Analyze and Extract Accelerators from Whole Programs
- Snehasish Kumar
- Nick Sumner
- et al.
- 2017
- HPCA 2017
Co-designing accelerators and SoC interfaces using gem5-Aladdin
- Yakun Sophia Shao
- Sam Likun Xi
- et al.
- 2016
- MICRO 2016
Approximate computing: Challenges and opportunities
- Ankur Agrawal
- Jungwook Choi
- et al.
- 2016
- ICRC 2016
Peruse and profit : Estimating the accelerability of loops
- Snehasish Kumar
- Vijayalakshmi Srinivasan
- et al.
- 2016
- ICS 2016
Self-contained, accurate precomputation prefetching
- Islam Atta
- Xin Tong
- et al.
- 2015
- MICRO 2015