76 citations · 78 across the 5 of their papers we have counts for
4 papers · 1 filter
GauS: Differentiable Scheduling Optimization via Gaussian Reparameterization
Yaohui Cai, Vesal Bakhtazad, Cunxi Yu +1
Efficient operator scheduling is a fundamental challenge in software compilation and hardware synthesis. While recent differentiable approaches have sought to replace traditional o…
HeuriGym: An Agentic Benchmark for LLM-Crafted Heuristics in Combinatorial Optimization
Hongzheng Chen, Yingheng Wang, Yaohui Cai +10
While Large Language Models (LLMs) have demonstrated significant advancements in reasoning and agent-based problem-solving, current evaluation methodologies fail to adequately asse…
Trainable Fixed-Point Quantization for Deep Learning Acceleration on FPGAs
Dingyi Dai, Yichi Zhang, Jiahao Zhang +4
Quantization is a crucial technique for deploying deep learning models on resource-constrained devices, such as embedded FPGAs. Prior efforts mostly focus on quantizing matrix mult…
Understanding the Potential of FPGA-Based Spatial Acceleration for Large Language Model Inference
Hongzheng Chen, Jiahao Zhang, Yixiao Du +5
Recent advancements in large language models (LLMs) boasting billions of parameters have generated a significant demand for efficient deployment in inference workloads. The majorit…