Cover Image

GauS: Differentiable Scheduling Optimization via Gaussian Reparameterization

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Cai, Yaohui, Bakhtazad, Vesal, Yu, Cunxi, Zhang, Zhiru
Format:	Preprint
Published:	2026
Subjects:	Machine Learning Hardware Architecture
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Differentiable Combinatorial Scheduling at Scale
by: Liu, Mingju, et al.
Published: (2024)

Differentiable Initialization-Accelerated CPU-GPU Hybrid Combinatorial Scheduling
by: Liu, Mingju, et al.
Published: (2026)

Less is More: Hop-Wise Graph Attention for Scalable and Generalizable Learning on Circuits
by: Deng, Chenhui, et al.
Published: (2024)

e-boost: Boosted E-Graph Extraction with Adaptive Heuristics and Exact Solving
by: Yin, Jiaqi, et al.
Published: (2025)

CuAsmRL: Optimizing GPU SASS Schedules via Deep Reinforcement Learning
by: He, Guoliang, et al.
Published: (2025)

Understanding the Potential of FPGA-Based Spatial Acceleration for Large Language Model Inference
by: Chen, Hongzheng, et al.
Published: (2023)

BoolGebra: Attributed Graph-learning for Boolean Algebraic Manipulation
by: Li, Yingjie, et al.
Published: (2024)

Mapping Fusion: Improving FPGA Technology Mapping with ASIC Mapper
by: Yu, Cunxi
Published: (2025)

DOMAC: Differentiable Optimization for High-Speed Multipliers and Multiply-Accumulators
by: Xue, Chenhao, et al.
Published: (2025)

Allo: A Programming Model for Composable Accelerator Design
by: Chen, Hongzheng, et al.
Published: (2024)

Dato: A Task-Based Programming Model for Dataflow Accelerators
by: Fang, Shihan, et al.
Published: (2025)

TCL: Enabling Fast and Efficient Cross-Hardware Tensor Program Optimization via Continual Learning
by: Shen, Chaoyao, et al.
Published: (2026)

PASCAL: A Phase-Aware Scheduling Algorithm for Serving Reasoning-based Large Language Models
by: Cho, Eunyeong, et al.
Published: (2026)

A Data-Driven Approach to Dataflow-Aware Online Scheduling for Graph Neural Network Inference
by: Puigdemont, Pol, et al.
Published: (2024)

GFormer: Accelerating Large Language Models with Optimized Transformers on Gaudi Processors
by: Zhang, Chengming, et al.
Published: (2024)

AutoPPA: Automated Circuit PPA Optimization via Contrastive Code-based Rule Library Learning
by: Li, Chongxiao, et al.
Published: (2026)

DOSA: Differentiable Model-Based One-Loop Search for DNN Accelerators
by: Hong, Charles, et al.
Published: (2025)

PointODE: Lightweight Point Cloud Learning with Neural Ordinary Differential Equations on Edge
by: Sugiura, Keisuke, et al.
Published: (2025)

GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Models
by: Fu, Yonggan, et al.
Published: (2023)

Cell Library Characterization for Composite Current Source Models Based on Gaussian Process Regression and Active Learning
by: Bai, Tao, et al.
Published: (2025)

Onboard Optimization and Learning: A Survey
by: Pavel, Monirul Islam, et al.
Published: (2025)

BoolE: Exact Symbolic Reasoning via Boolean Equality Saturation
by: Yin, Jiaqi, et al.
Published: (2025)

LOTION: Smoothing the Optimization Landscape for Quantized Training
by: Kwun, Mujin, et al.
Published: (2025)

CircuitVAE: Efficient and Scalable Latent Circuit Optimization
by: Song, Jialin, et al.
Published: (2024)

Hardware Software Optimizations for Fast Model Recovery on Reconfigurable Architectures
by: Xu, Bin, et al.
Published: (2025)

Accelerating Sparse Graph Neural Networks with Tensor Core Optimization
by: Wu, Ka Wai
Published: (2024)

IR-Aware ECO Timing Optimization Using Reinforcement Learning
by: Jiang, Wenjing, et al.
Published: (2024)

BDD2Seq: Enabling Scalable Reversible-Circuit Synthesis via Graph-to-Sequence Learning
by: Miao, Mingkai, et al.
Published: (2025)

LLM-USO: Large Language Model-based Universal Sizing Optimizer
by: S, Karthik Somayaji N., et al.
Published: (2025)

CATransformers: Carbon Aware Transformers Through Joint Model-Hardware Optimization
by: Wang, Irene, et al.
Published: (2025)

Tawa: Automatic Warp Specialization for Modern GPUs with Asynchronous References
by: Chen, Hongzheng, et al.
Published: (2025)

Beyond Tokens: Enhancing RTL Quality Estimation via Structural Graph Learning
by: Liu, Yi, et al.
Published: (2025)

GCoD: Graph Convolutional Network Acceleration via Dedicated Algorithm and Accelerator Co-Design
by: You, Haoran, et al.
Published: (2021)

Autonomous Evolution of EDA Tools: Multi-Agent Self-Evolved ABC
by: Yu, Cunxi, et al.
Published: (2026)

Cross-Layer Co-Optimized LSTM Accelerator for Real-Time Gait Analysis
by: Ahmadilivani, Mohammad Hasan, et al.
Published: (2026)

Low Power Vision Transformer Accelerator with Hardware-Aware Pruning and Optimized Dataflow
by: Hsiung, Ching-Lin, et al.
Published: (2025)

vMCU: Coordinated Memory Management and Kernel Optimization for DNN Inference on MCUs
by: Zheng, Size, et al.
Published: (2024)

EVA: Accelerating LLM Decoding via an Efficient Vector Quantization Architecture
by: Duan, Bowen, et al.
Published: (2026)

PACiM: A Sparsity-Centric Hybrid Compute-in-Memory Architecture via Probabilistic Approximation
by: Zhang, Wenlun, et al.
Published: (2024)

OpenACMv2: An Accuracy-Constrained Co-Optimization Framework for Approximate DCiM
by: Zhou, Yiqi, et al.
Published: (2026)