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Ace-TN: GPU-Accelerated Corner-Transfer-Matrix Renormalization of Infinite Projected Entangled-Pair States
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The infinite projected entangled-pair state (iPEPS) ansatz is a powerful tensor-network approximation of an infinite two-dimensional quantum many-body state. Tensor-based calculations are particularly well-suited to utilize the high parallel efficiency of modern GPUs. We present Ace-TN, a modular and easily extendable open-source library developed to address the current need for an iPEPS framework focused on GPU acceleration. We demonstrate the advantage of using GPUs for the core iPEPS simulation methods and present a simple parallelization scheme for efficient multi-GPU execution. The latest distribution of Ace-TN can be obtained at https://github.com/ace-tn/ace-tn.
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Cited by 1 Pith paper
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Fast two-dimensional tensor-network contraction via subspace iteration
A new CTMRG variant, SI-CTMRG, substitutes QR-based subspace iteration for the dominant large SVD, shifting cost to tensor contractions and enabling state-of-the-art iPEPS calculations on a single H100 GPU.
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