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Update docs: Add option to use image with CUDA preinstalled #657

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Feb 12, 2024
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Update docs: Add option to use image with CUDA preinstalled #657

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10e9a53
Add option to use image with CUDA preinstalled
eliottrosenberg Feb 11, 2024
510c658
Update number of V100s
eliottrosenberg Feb 12, 2024
38a0909
implement suggestions
eliottrosenberg Feb 12, 2024
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update link
eliottrosenberg Feb 12, 2024
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6 changes: 3 additions & 3 deletions docs/choose_hw.md
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Expand Up @@ -129,7 +129,7 @@ choose a specific machine:
For GPU simulations, you may follow the instructions in [this](tutorials/gcp_gpu)
guide to set up a virtual machine (VM) on Google Cloud Platform (GCP).
Alternatively, you can use your own hardware.
Note the [hardware requirements](https://docs.nvidia.com/cuda/cuquantum/getting_started.html#custatevec)
Note the [hardware requirements](https://docs.nvidia.com/cuda/cuquantum/latest/getting_started.html#custatevec)
for NVIDIA's cuQuantum when picking a GPU; in particular, it must have
CUDA Compute Capability 7.0 or higher.
At the time of writing, the following compatible GPUs are available on GCP:
Expand All @@ -140,8 +140,8 @@ At the time of writing, the following compatible GPUs are available on GCP:
* [NVIDIA V100](https://www.techpowerup.com/gpu-specs/tesla-v100-pcie-16-gb.c2957).
Like the NVIDIA T4, this GPU has 16GB of RAM and
therefore supports up to 30 qubits. It is faster than the T4.
Further, it is compatible with multi-GPU simulations. With 8 NVIDIA V100s (128GB),
you can simulate up to 33 qubits.
Further, it is compatible with multi-GPU simulations. With 4 NVIDIA V100s (64GB),
you can simulate up to 32 qubits.
* [NVIDIA L4](https://www.techpowerup.com/gpu-specs/l4.c4091). This GPU has 24GB
of RAM and can therefore simulate up to 31 qubits. With eight of them (192GB), you can simulate
up to 34 qubits.
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6 changes: 5 additions & 1 deletion docs/tutorials/gcp_gpu.md
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Expand Up @@ -35,6 +35,11 @@ instance section, ensure that your VM has the following properties:
1. In the **Operating System** option, choose **Ubuntu**.
2. In the **Version** option, choose **20.04 LTS**.
3. In the **Size** field, enter **40** (minimum).

**Alternatively, you can click the "Switch Image" button and use the image with
CUDA pre-installed, which lets you skip step 3. It has been verified that this works
with cuQuantum Appliance (option 3).**

* The instructions above override steps 3 through 5 in the [Create a Linux VM
instance](https://cloud.google.com/compute/docs/quickstart-linux)
Quickstart.
Expand Down Expand Up @@ -178,7 +183,6 @@ to set up NVIDIA Container Toolkit.
Follow the instructions [here](https://catalog.ngc.nvidia.com/orgs/nvidia/containers/cuquantum-appliance)
to set up cuQuantum Appliance. You may need to use `sudo` for the Docker commands.


## 10. Verify your installation (Options 1, 2, and 3)

You can use the following code to verify that qsim uses your GPU. You can paste
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