*********************************************************************** cuTensorNet: A High-Performance Library for Tensor Network Computations *********************************************************************** Welcome to the cuTensorNet library documentation! **NVIDIA cuTensorNet** is a high-performance library for tensor network computations, a component of the :doc:`NVIDIA cuQuantum SDK <../index>`. Functionalities of *cuTensorNet* are described in :doc:`Overview ` with installation and usage guide provided in :doc:`Getting Started `. .. TODO: mention what cuTensorNet can be used in addition to quantum circuit simulations. We don't want to limit ourselves in quantum information science. Tensor networks can be used in many areas beyond that. .. topic:: Key Features * Based on NVIDIA's high-performance tensor linear algebra library: `cuTENSOR `_ * Provides APIs for: - Creating a tensor or tensor network object - Finding a low-cost contraction path for any given tensor network - Finding a low-overhead slicing for the tensor network contraction to meet specified memory constraints - Tuning the path finder configuration for better performance - Performing tensor network contraction plan auto-tuning and its subsequent execution - Performing tensor decomposition using QR or SVD - Applying a gate operand to a pair of connected tensors - Enabling automatic distributed parallelization in the contraction path finder and executor - Enabling custom memory management - Logging .. topic:: Support * *Supported GPU Architectures*: ``Volta``, ``Ampere``, ``Hopper`` * *Supported OS*: ``Linux`` * *Supported CPU Architectures*: ``x86_64``, ``ARM64``, ``ppc64le`` .. topic:: Prerequisites * `CUDA® Toolkit 11.x `_ and compatible driver r450+ (see `CUDA Toolkit Release Notes `_). * `cuTENSOR v1.6.1 (or above) `_ .. toctree:: :caption: Contents :maxdepth: 2 release_notes overview getting_started api/index acknowledgements