A personal collection and evaluation of recent decade's DAC papers.
My research interests include high-level synthesis, neural network compilation and architecture design for deep learning. In order to construct a systematic view of these research fields, as well as learning fresh ideas. I am collecting and sorting DAC (Design Automation Conference) papers by publishing year and those above mentioned research topics.
- Reinforcement Learning-based Power. Management Policy for Mobile Device Systems
- A Neural Network that Routes ICs
- MEMTONIC: A Neuromorphic Accelerator for Energy Efficient Deep Learning
- Designed for inference and training
- Building an On-Chip Deep Learning Memory Hierarchy Brick by Brick
- Memory access is one of the most important bottlenecks in designing NN accelerators
- Automated Hardware Generation of CNN Models on FPGAs
- Bit Parallel 6T SRAM In-memory Computing with Reconfigurable Bit-Precision
- Factored Radix-8 Systolic Array for Tensor Processing
- DECOY: Deflection-Driven HLS-Based Computation Partitioning for Obfuscating Intellectual Property