Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new hybrid linear equation solver for quadratic placement. The new solver is a combination of stochastic solver and iterative solver: it is proven in this paper that an approximate LDL factorization can be obtained from random walks, and used as a preconditioner for conjugate gradient solver. Testing on real-life placement benchmarks shows a speedup of up to 7.1 times over traditional Incomplete Cholesky preconditioned Conjugate Gradient (ICCG).
['Haifeng Qian', 'Sachin S. Sapatnekar']
I am writing a research paper on a idea A hybrid linear equation solver and its application in quadratic placement
[{"from": "human", "value": "I am writing a research paper on a idea A hybrid linear equation solver and its application in quadratic placement"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  presents a new hybrid linear equation solver for quadratic placement. The new solver is a combination of stochastic solver and iterative solver: it is proven in this paper that an approximate LDL factorization can be obtained from random walks, and used as a preconditioner for conjugate gradient solver. Testing on real-life placement benchmarks shows a speedup of up to 7.1 times over traditional Incomplete Cholesky preconditioned Conjugate Gradient (ICCG)."}]