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Update README to fix broken links #43

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Dec 20, 2023
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Update README to fix broken links #43

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b62fdc1
Updated broken links and added compute capability
PabloAndresCQ Nov 14, 2023
12c814d
Some typos
PabloAndresCQ Nov 14, 2023
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13 changes: 7 additions & 6 deletions README.md
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Expand Up @@ -9,9 +9,9 @@ This repository contains the pytket-cutensornet extension, using Quantinuum's
with tket, a quantum computing toolkit and optimisation compiler developed by Quantinuum.


[cuTensorNet](https://docs.nvidia.com/cuda/cuquantum/cutensornet/index.html) is a
[cuTensorNet](https://docs.nvidia.com/cuda/cuquantum/latest/cutensornet/index.html) is a
high-performance library for tensor network computations, developed by NVIDIA.
It is part of the [cuQuantum](https://docs.nvidia.com/cuda/cuquantum/index.html) SDK -
It is part of the [cuQuantum](https://docs.nvidia.com/cuda/cuquantum/latest/index.html) SDK -
a high-performance library aimed at quantum circuit simulations on the NVIDIA GPU chips,
consisting of two major components:
- `cuStateVec`: a high-performance library for state vector computations.
Expand All @@ -21,17 +21,18 @@ Both components have both C and Python API.

`pytket-cutensornet` is an extension to `pytket` that allows `pytket` circuits and
expectation values to be simulated using `cuTensorNet` via an interface to
[cuQuantum Python](https://docs.nvidia.com/cuda/cuquantum/python/index.html).
[cuQuantum Python](https://docs.nvidia.com/cuda/cuquantum/latest/cutensornet/index.html).

Currently, only single-GPU calculations are supported, but a multi-GPU execution will be
implemented in the due course using `mpi4py` library.

## Getting started

`pytket-cutensornet` is available for Python 3.9, 3.10 and 3.11 on Linux.
In order to use it, you need access to a Linux machine with either `Volta`, `Ampere`
or `Hopper` GPU and first install `cuQuantum Python` following their installation
[instructions](https://docs.nvidia.com/cuda/cuquantum/python/README.html#installation).
In order to use it, you need access to a Linux machine with an NVIDIA GPU of
Compute Capability +7.0 (check it [here](https://developer.nvidia.com/cuda-gpus)) and first
install `cuQuantum Python` following their installation
[instructions](https://docs.nvidia.com/cuda/cuquantum/latest/python/README.html#installation).
This will include the necessary dependencies such as CUDA toolkit. Then, to install
`pytket-cutensornet`, run:

Expand Down