Hybridizing PDHG and Interior-Point Methods
Abstract
The Primal-Dual Hybrid Gradient (PDHG) algorithm is a first-order method that can exploit GPUs to solve large-scale linear programming problems. The approach can often be faster than the alternatives, simplex and interior-point methods, typically at the cost of much lower accuracy. This paper looks at whether PDHG can be hybridized with an interior-point method to retain some of the speed advantages of the former while capturing the accuracy advantages of the latter. --- Source: arXiv:2603.03150...
Description / Details
The Primal-Dual Hybrid Gradient (PDHG) algorithm is a first-order method that can exploit GPUs to solve large-scale linear programming problems. The approach can often be faster than the alternatives, simplex and interior-point methods, typically at the cost of much lower accuracy. This paper looks at whether PDHG can be hybridized with an interior-point method to retain some of the speed advantages of the former while capturing the accuracy advantages of the latter.
Source: arXiv:2603.03150v1 - http://arxiv.org/abs/2603.03150v1 PDF: https://arxiv.org/pdf/2603.03150v1 Original Link: http://arxiv.org/abs/2603.03150v1
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Mar 5, 2026
Mathematics
Mathematics
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