DAC-Papers-Collection

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.

Table of Contents

• DAC Papers
  • 2020
  • 2018
  • 2016
  • 2014
  • 2012

DAC Papers

2020 DAC

Machine learning in solving traditional EDA problems

• Reinforcement Learning-based Power. Management Policy for Mobile Device Systems
• A Neural Network that Routes ICs

Neural network accelerator design

• 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

High-level synthesis

• DECOY: Deflection-Driven HLS-Based Computation Partitioning for Obfuscating Intellectual Property