5 papers
Boosting Entropy with Bell Box Quantization
Ningfeng Yang, Tor M. Aamodt
Quantization-Aware Pre-Training (QAPT) is an effective technique to reduce the compute and memory overhead of Deep Neural Networks while improving their energy efficiency on edge d…
RoboGPU: Accelerating GPU Collision Detection for Robotics
Lufei Liu, Liwei Xue, Youssef Mohammed +3
Autonomous robots are increasingly prevalent in our society, emerging in medical care, transportation vehicles, and home assistance. These robots rely on motion planning and collis…
Improving the Straight-Through Estimator with Zeroth-Order Information
Ningfeng Yang, Tor M. Aamodt
We study the problem of training neural networks with quantized parameters. Learning low-precision quantized parameters by enabling computation of gradients via the Straight-Throug…
ReFrame: Layer Caching for Accelerated Inference in Real-Time Rendering
Lufei Liu, Tor M. Aamodt
Graphics rendering applications increasingly leverage neural networks in tasks such as denoising, supersampling, and frame extrapolation to improve image quality while maintaining…
Graph-based identification of qubit network (GidNET) for qubit reuse
Gideon Uchehara, Tor M. Aamodt, Olivia Di Matteo
Quantum computing introduces the challenge of optimizing quantum resources crucial for executing algorithms within the limited qubit availability of current quantum architectures.…