
Launch GPU instance
Use the drop-down at the top of your account page to select the GPU Lab image, and then click Launch Lab.

500 TimeOutError
, click Home in the top-left,
and re-start your server.
Configuration
qBraid Lab GPUs instances are configured with the following specification:Provider | NVIDIA |
---|---|
GPU Architecture | Volta |
GPU Name | Tesla V100 |
CUDA | 12.0 |
Driver | 525.105.17 |
nvidia-smi
) and
NVIDIA CUDA Toolkit (nvcc
) command line utilities.
GPU-enabled environments
The GPU Lab image comes pre-configured with the NVIDIA cuQuantum SDK GPU simulator library, and includes GPU integrations with other popular quantum softwares packages such as Pennylane-Lightning, Qiskit Aer, and Qsim-Cirq.
Pennylane-Lighting
PennyLane is a cross-platform Python library for quantum machine learning, automatic differentiation, and optimization of hybrid quantum-classical computations. The PennyLane-Lightning-GPU plugin extends the Pennylane-Lightning state-vector simulator written in C++, and offloads to the NVIDIA cuQuantum SDK for GPU accelerated circuit simulation. Thelightning.gpu
device is an extension of PennyLane’s built-in lightning.qubit
device. It extends the
CPU-focused Lightning simulator to run using the NVIDIA cuQuantum SDK, enabling GPU-accelerated simulation of
quantum state-vector evolution.
A lightning.gpu
device can be loaded using:
lightning.qubit
and perform all simulation on the CPU.
Qiskit Aer
Qiskit is an open-source framework for working with noisy quantum computers at the level of pulses, circuits, and algorithms. The Qiskit Aer library provides high-performance quantum computing simulators with realistic noise models. On qBraid, the Qiskit Aer GPU environment comes with theqiskit-aer-gpu
package, extending the same functionality of the
canonical qiskit-aer
package, plus the ability to run the GPU supported simulators: statevector, density matrix, and unitary.
Here is a basic example: