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Backend Systems

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This section displays the backend Run options for a user to run a circuit when submitted as a job on a CPU, GPU, or QPU along with High-Performance Computers(HPCs) options and listed Backend options.

Click Run in the upper right corner. Select an available system simulator or HPC system in the open model. Systems send the circuit to real quantum hardware when selected with the QPU option and simulators.

Demonstrated here with a video tour of the options available at the backend to submit the job on CPU, GPU, and QPU.

 

Select Processor #

Gives a user with an option to select from listed Processors such as –

  • CPU
  • GPU
  • Vector
  • Quantum Processing Unit(QPU)

Select HPC: Gives a user an option to select from listed HPCs such as :

  • Param Utkarsh
  • QACC-Cluster

 

Simulator Backend #

The user has been presented with a range of options for the Simulator Backend, which they can select. Listed here are the CPU options available

CPU #

  • Qiskit QASM Simulator
  • Qiskit Statevector Simulator
  • Aer DM Simulator
  • Cirq Simulator

 

GPU #

Aer_StateVector_simulator_GPU: Aer_StateVector_simulator_GPU is a feature within the Qiskit Aer framework that allows you to leverage the power of your GPU to perform state vector simulations of quantum circuits. State vector simulation involves calculating the complete quantum state of a system after a circuit is applied.

  • Qiskit Aer: Aer is a high-performance simulator for quantum circuits included in the Qiskit library. It provides various simulation methods, including state vector simulation.
  • State vector Simulation: This type of simulation calculates the entire state vector of a quantum circuit. The state vector holds the amplitudes (complex numbers representing probabilities) of finding the system in each possible basis state after applying the circuit.
  • GPU Acceleration: Aer_StateVector_simulaor_GPU utilizes the NVIDIA cuStateVec library, which offers optimized kernels for state vector simulation on GPUs. This significantly speeds up simulations compared to CPU-based approaches, especially for larger circuits.
  • Faster Simulations: Running state vector simulations on GPUs can lead to significant speedups compared to CPU simulations, particularly for complex circuits with many qubits.
  • Improved Scalability: Leveraging GPUs allows you to handle larger quantum circuits that might be impractical to simulate on CPUs due to resource limitations.

 

Nvidia_cudaq_statevector_simulator:

The NVIDIA CUDA-Q Statevector Simulator is a high-performance tool that uses NVIDIA GPUs to accelerate simulations of quantum circuits. Its key features—such as GPU acceleration, scalability, precision, and seamless integration with the CUDA ecosystem—make it an invaluable resource for researchers and developers working on quantum computing applications.

Key Features:

GPU Acceleration: Leverages the parallel processing power of NVIDIA GPUs to significantly speed up quantum circuit simulations. This is crucial for handling larger circuits and more complex simulations that would be prohibitively slow on CPUs alone.
State vector Representation: Stores and manipulates the quantum state as a complex-valued vector. This allows for accurate simulation of quantum circuits and enables calculations of various properties of the quantum system.
Scalability: Supports scaling simulations across multiple GPUs and even multiple nodes in a cluster. This enables researchers to tackle larger and more complex problems that exceed the memory capacity of a single GPU.
Precision: Offers options for both single-precision (FP32) and double-precision (FP64) simulations. This allows users to choose the appropriate level of precision for their simulations, balancing accuracy with performance.
Integration with CUDA-Q: Seamlessly integrates within the NVIDIA CUDA-Q framework. This allows users to leverage other CUDA-Q features like custom kernel definitions and integration with other CUDA libraries.
Efficient Memory Management: Optimizes memory usage to minimize data transfer between CPU and GPU, further improving performance.

 

Select Quantum Hardware(QPU) #

The user is presented with a range of options for the available Quantum Hardware, from which they can select.   A user can only submit a job on QPU if he/she has an API key, which can be generated here and then copied and pasted into the provided placeholder in the user’s profile section.

The following are the available QPU platforms available:

  • ibm_brisbane
  • ibm_kyiv
  • ibm_Sherbrooke