Scaledeep: A scalable compute architecture for learning and evaluating deep networks
- Swagath Venkataramani
- Ashish Ranjan
- et al.
- 2017
- ISCA 2017
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36 results for Swagath Venkataramani
INVITED: Accelerator Design for Deep Learning Training: Extended Abstract: Invited
- Ankur Agrawal
- Chia-Yu Chen
- et al.
- 2017
- DAC 2017
A 7-nm Four-Core Mixed-Precision AI Chip with 26.2-TFLOPS Hybrid-FP8 Training, 104.9-TOPS INT4 Inference, and Workload-Aware Throttling
- Sae Kyu Lee
- Ankur Agrawal
- et al.
- 2021
- IEEE JSSC
SparCE: Sparsity Aware General-Purpose Core Extensions to Accelerate Deep Neural Networks
- Sanchari Sen
- Shubham Jain
- et al.
- 2019
- IEEE TC
Approximate computing and the efficient machine learning expedition
- Jörg Henkel
- Hai Li
- et al.
- 2022
- ICCAD 2022
Accelerating Inference and Language Model Fusion of Recurrent Neural Network Transducers via End-to-End 4-bit Quantization
- Andrea Fasoli
- Chia-Yu Chen
- et al.
- 2022
- INTERSPEECH 2022
4-bit quantization of LSTM-based speech recognition models
- Andrea Fasoli
- Chia-Yu Chen
- et al.
- 2021
- INTERSPEECH 2021
Efficacy of Pruning in Ultra-Low Precision DNNs
- Sanchari Sen
- Swagath Venkataramani
- et al.
- 2021
- ISLPED 2021
Efficient Management of Scratch-Pad Memories in Deep Learning Accelerators
- Subhankar Pal
- Swagath Venkataramani
- et al.
- 2021
- ISPASS 2021
Value Similarity Extensions for Approximate Computing in General-Purpose Processors
- Younghoon Kim
- Swagath Venkataramani
- et al.
- 2021
- DATE 2021