57th DAC | Best Paper/Presentation Nominations

Best paper candidates

• COEXE: An Efficient Co-Execution Architecture for Real-Time Neural Network Services
  
• FLOPS: Efficient On-Chip Learning for Optical Neural Networks Through Stochastic Zeroth-Order Optimization
  
• ATUNs: Modular and Scalable Support for Atomic Operations in a Shared Memory Multiprocessor
  
• TP-GNN: A Graph Neural Network Framework for Tier Partitioning in Monolithic 3D ICs
  
• A Two-Way SRAM Array Based Accelerator for Deep Neural Network On-Chip Training
  
• Algorithm-Hardware Co-Design of Adaptive Floating-Point Encodings for Resilient Deep Learning Inference
  

BEST PAPER COMMITTEE

• Jason M. Fung
• Jeronimo Castrillon
• Jian-Jia Chen
• Noel Menezes
• Partha Pande
• Preeti R. Panda
• Rajiv Joshi
• Seda Ogrenci Memik
• Vijay Raghunathan
• Yu Cao