Ivan's wiki

Site Tools

cuda-q

Differences

This shows you the differences between two versions of the page.

Link to this comparison view

Both sides previous revisionPrevious revision
cuda-q [August 22, 2026 at 18:20] – removed Ivan Janevskicuda-q [August 22, 2026 at 18:21] (current) – created - external edit 127.0.0.1
Line 1: Line 1:
 +# CUDA-Q
 +
 +**CUDA-Q** is NVIDIA's open-source quantum computing platform for hybrid quantum-classical computing in C++. Define quantum [[cuda-q-quantum-kernels|kernels]] as C++ functions, execute on quantum simulators (GPU-accelerated via cuQuantum) or real quantum hardware; integrate with classical compute and ML. CUDA-Q abstracts backend details, letting you write once and target different quantum processors.
 +
 +A **quantum kernel** is a C++ function marked with `__qpu__` containing quantum operations. Mix classical control flow with quantum code—loops, conditionals, and function calls all work naturally. Leverage NVIDIA GPUs for massive parallel simulation (thousands of qubits) or distribute across multiple GPUs.
 +
 +```cpp
 +#include "cudaq.h"
 +
 +// Quantum kernel: Bell pair
 +struct BellPair {
 +  void operator()() __qpu__ {
 +    cudaq::qvector q(2);
 +    h(q[0]);
 +    cx(q[0], q[1]);
 +    mz(q);
 +  }
 +};
 +
 +// Execute on GPU-accelerated simulator
 +auto result = cudaq::sample<BellPair>(1000);
 +for (auto& [bits, count] : result) {
 +  printf("%s: %lu\n", bits.c_str(), count);
 +}
 +```
 +
 +CUDA-Q bridges quantum computing and classical HPC—ideal for near-term algorithms combining quantum circuits with classical optimization and machine learning.
 +
 +## Concepts
 +
 + 1. [[cuda-q-hybrid-computing|Hybrid quantum-classical computing]]
 + 2. [[cuda-q-quantum-kernels|Quantum kernels]]
 + 3. [[cuda-q-programming-model|CUDA-Q programming model]]
 + 4. [[cuda-q-state-preparation|State preparation]]
 + 5. [[cuda-q-measurement|Measurement and readout]]
 + 6. [[cuda-q-parameterized-circuits|Parameterized quantum circuits]]
 + 7. [[cuda-q-quantum-algorithms|Quantum algorithms library]]
 + 8. [[cuda-q-vqe|VQE (Variational Quantum Eigensolver)]]
 + 9. [[cuda-q-qaoa|QAOA (Quantum Approximate Optimization)]]
 + 10. [[cuda-q-backends|Backends and execution]]
 + 11. [[cuda-q-gpu-acceleration|GPU acceleration with cuQuantum]]
 + 12. [[cuda-q-distributed-simulation|Distributed quantum simulation]]
 + 13. [[cuda-q-noise-models|Noise models and open system simulation]]
 + 14. [[cuda-q-gradients|Gradient computation and optimization]]
 + 15. [[cuda-q-quantum-ml|Quantum machine learning]]
 + 16. [[cuda-q-classical-integration|Integration with classical compute]]
 + 17. [[cuda-q-optimization|Optimization in CUDA-Q]]
 + 18. [[cuda-q-debugging|Debugging and profiling]]
 + 19. [[cuda-q-performance|Performance optimization]]
 + 20. [[cuda-q-hardware|Hardware integration and QPUs]]
  
cuda-q.md · Last modified: by 127.0.0.1