Memory and Interconnect Optimizations for Peta-Scale Deep Learning Systems
- Swagath Venkataramani
- Vijayalakshmi Srinivasan
- et al.
- 2019
- HiPC 2019
Conference paper
Publications
66 results for Vijayalakshmi Srinivasan
Performance-driven Programming of Multi-TFLOP Deep Learning Accelerators∗
- Swagath Venkataramani
- Jungwook Choi
- et al.
- 2019
- IISWC 2019
Conference paperDeepTools: Compiler and Execution Runtime Extensions for RaPiD AI Accelerator
- Swagath Venkataramani
- Jungwook Choi
- et al.
- 2019
- IEEE Micro
PaperBiScaled-DNN: Quantizing long-tailed datastructures with two scale factors for deep neural networks
- Shubham Jain
- Swagath Venkataramani
- et al.
- 2019
- DAC 2019
Conference paperA Compiler for Deep Neural Network Accelerators to Generate Optimized Code for a Wide Range of Data Parameters from a Hand-crafted Computation Kernel
- Eri Ogawa
- Kazuaki Ishizaki
- et al.
- 2019
- COOL CHIPS 2019
Conference paperA Scalable Multi-TeraOPS Core for AI Training and Inference
- Sunil Shukla
- Bruce Fleischer
- et al.
- 2018
- IEEE SSC-L
PaperA Scalable Multi-TeraOPS Deep Learning Processor Core for AI Trainina and Inference
- Bruce Fleischer
- Sunil Shukla
- et al.
- 2018
- VLSI Circuits 2018
Conference paperCompensated-DNN: Energy efficient low-precision deep neural networks by compensating quantization errors
- Shubham Jain
- Swagath Venkataramani
- et al.
- 2018
- DAC 2018
Conference paperExploiting approximate computing for deep learning acceleration
- Chia-Yu Chen
- Jungwook Choi
- et al.
- 2018
- DATE 2018
Conference paperPOSTER: Design Space Exploration for Performance Optimization of Deep Neural Networks on Shared Memory Accelerators
- Swagath Venkataramani
- Jungwook Choi
- et al.
- 2017
- PACT 2017
Conference paper