Accelerating Sparse LU Factorization with Density-Aware Adaptive Matrix Multiplication for Circuit Simulation
Author:
Affiliation:
1. China University of Petroleum-Beijing,Super Scientific Software Laboratory,China
Funder
National Natural Science Foundation of China
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10247654/10247655/10247767.pdf?arnumber=10247767
Reference12 articles.
1. Machine-Learning-Driven Matrix Ordering for Power Grid Analysis
2. SFLU: Synchronization-Free Sparse LU Factorization for Fast Circuit Simulation on GPUs
3. An introduction to decision tree modeling
4. A communication-avoiding 3D algorithm for sparse LU factorization on heterogeneous systems
5. A Supernodal Approach to Sparse Partial Pivoting
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1. Performance-Driven Analog Layout Automation: Current Status and Future Directions (Invited Paper);2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC);2024-01-22
2. Machine Learning and GPU Accelerated Sparse Linear Solvers for Transistor-Level Circuit Simulation: A Perspective Survey (Invited Paper);2024 29th Asia and South Pacific Design Automation Conference (ASP-DAC);2024-01-22
3. Accelerating Large-Scale Sparse LU Factorization for RF Circuit Simulation;Lecture Notes in Computer Science;2024
4. TileSpTRSV: a tiled algorithm for parallel sparse triangular solve on GPUs;CCF Transactions on High Performance Computing;2023-06
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