Sampling the tensor network state#

The following code example illustrates how to sample the tensor network state (e.g., sampling the final quantum circuit state). The full code can be found in the NVIDIA/cuQuantum repository (here).

Headers and error handling#

 7#include <cstdlib>
 8#include <cstdio>
 9#include <cassert>
10#include <complex>
11#include <vector>
12#include <iostream>
13
14#include <cuda_runtime.h>
15#include <cutensornet.h>
16
17#define HANDLE_CUDA_ERROR(x) \
18{ const auto err = x; \
19  if( err != cudaSuccess ) \
20  { printf("CUDA error %s in line %d\n", cudaGetErrorString(err), __LINE__); fflush(stdout); std::abort(); } \
21};
22
23#define HANDLE_CUTN_ERROR(x) \
24{ const auto err = x; \
25  if( err != CUTENSORNET_STATUS_SUCCESS ) \
26  { printf("cuTensorNet error %s in line %d\n", cutensornetGetErrorString(err), __LINE__); fflush(stdout); std::abort(); } \
27};
28
29
30int main()
31{
32  static_assert(sizeof(size_t) == sizeof(int64_t), "Please build this sample on a 64-bit architecture!");
33
34  constexpr std::size_t fp64size = sizeof(double);

Define the tensor network state and the desired number of output samples to generate#

Let’s define a tensor network state corresponding to a 16-qubit quantum circuit and request to produce 100 output samples for the full qubit register.

38  // Quantum state configuration
39  const int64_t numSamples = 100;
40  const int32_t numQubits = 16;
41  const std::vector<int64_t> qubitDims(numQubits, 2); // qubit size
42  std::cout << "Quantum circuit: " << numQubits << " qubits; " << numSamples << " samples\n";

Initialize the cuTensorNet library handle#

46  // Initialize the cuTensorNet library
47  HANDLE_CUDA_ERROR(cudaSetDevice(0));
48  cutensornetHandle_t cutnHandle;
49  HANDLE_CUTN_ERROR(cutensornetCreate(&cutnHandle));
50  std::cout << "Initialized cuTensorNet library on GPU 0\n";

Define quantum gates on GPU#

54  // Define necessary quantum gate tensors in Host memory
55  const double invsq2 = 1.0 / std::sqrt(2.0);
56  //  Hadamard gate
57  const std::vector<std::complex<double>> h_gateH {{invsq2, 0.0},  {invsq2, 0.0},
58                                                   {invsq2, 0.0}, {-invsq2, 0.0}};
59  //  CX gate
60  const std::vector<std::complex<double>> h_gateCX {{1.0, 0.0}, {0.0, 0.0}, {0.0, 0.0}, {0.0, 0.0},
61                                                    {0.0, 0.0}, {1.0, 0.0}, {0.0, 0.0}, {0.0, 0.0},
62                                                    {0.0, 0.0}, {0.0, 0.0}, {0.0, 0.0}, {1.0, 0.0},
63                                                    {0.0, 0.0}, {0.0, 0.0}, {1.0, 0.0}, {0.0, 0.0}};
64
65  // Copy quantum gates to Device memory
66  void *d_gateH{nullptr}, *d_gateCX{nullptr};
67  HANDLE_CUDA_ERROR(cudaMalloc(&d_gateH, 4 * (2 * fp64size)));
68  std::cout << "H gate buffer allocated on GPU: " << d_gateH << std::endl; //debug
69  HANDLE_CUDA_ERROR(cudaMalloc(&d_gateCX, 16 * (2 * fp64size)));
70  std::cout << "CX gate buffer allocated on GPU: " << d_gateCX << std::endl; //debug
71  std::cout << "Allocated quantum gate memory on GPU\n";
72  HANDLE_CUDA_ERROR(cudaMemcpy(d_gateH, h_gateH.data(), 4 * (2 * fp64size), cudaMemcpyHostToDevice));
73  HANDLE_CUDA_ERROR(cudaMemcpy(d_gateCX, h_gateCX.data(), 16 * (2 * fp64size), cudaMemcpyHostToDevice));
74  std::cout << "Copied quantum gates to GPU memory\n";

Create a pure tensor network state#

Now let’s create a pure tensor network state for a 16-qubit quantum circuit.

78  // Create the initial quantum state
79  cutensornetState_t quantumState;
80  HANDLE_CUTN_ERROR(cutensornetCreateState(cutnHandle, CUTENSORNET_STATE_PURITY_PURE, numQubits, qubitDims.data(),
81                    CUDA_C_64F, &quantumState));
82  std::cout << "Created the initial quantum state\n";

Apply quantum gates#

Let’s construct the GHZ quantum circuit by applying the corresponding quantum gates.

86  // Construct the quantum circuit state (apply quantum gates)
87  int64_t id;
88  HANDLE_CUTN_ERROR(cutensornetStateApplyTensorOperator(cutnHandle, quantumState, 1, std::vector<int32_t>{{0}}.data(),
89                    d_gateH, nullptr, 1, 0, 1, &id));
90  for(int32_t i = 1; i < numQubits; ++i) {
91    HANDLE_CUTN_ERROR(cutensornetStateApplyTensorOperator(cutnHandle, quantumState, 2, std::vector<int32_t>{{i-1,i}}.data(),
92                      d_gateCX, nullptr, 1, 0, 1, &id));
93  }
94  std::cout << "Applied quantum gates\n";

Create the tensor network state sampler#

Once the quantum circuit has been constructed, let’s create the tensor network state sampler for the full qubit register (all qubits).

 98  // Create the quantum circuit sampler
 99  cutensornetStateSampler_t sampler;
100  HANDLE_CUTN_ERROR(cutensornetCreateSampler(cutnHandle, quantumState, numQubits, nullptr, &sampler));
101  std::cout << "Created the quantum circuit sampler\n";

Configure the tensor network state sampler#

Now we can configure the tensor network state sampler by setting the number of hyper-samples to be used by the tensor network contraction path finder.

105  // Configure the quantum circuit sampler
106  const int32_t numHyperSamples = 8; // desired number of hyper samples used in the tensor network contraction path finder
107  HANDLE_CUTN_ERROR(cutensornetSamplerConfigure(cutnHandle, sampler,
108    CUTENSORNET_SAMPLER_CONFIG_NUM_HYPER_SAMPLES, &numHyperSamples, sizeof(numHyperSamples)));
109  const int32_t rndSeed = 13; // explicit random seed to get the same results each run
110  HANDLE_CUTN_ERROR(cutensornetSamplerConfigure(cutnHandle, sampler,
111    CUTENSORNET_SAMPLER_CONFIG_DETERMINISTIC, &rndSeed, sizeof(rndSeed)));

Prepare the tensor network state sampler#

Let’s create a workspace descriptor and prepare the tensor network state sampler.

115  // Query the free memory on Device
116  std::size_t freeSize {0}, totalSize {0};
117  HANDLE_CUDA_ERROR(cudaMemGetInfo(&freeSize, &totalSize));
118  const std::size_t workSizeAvailable = (freeSize - (freeSize % 4096)) / 2; // use half of available memory with alignment
119
120  // Prepare the quantum circuit sampler
121  cutensornetWorkspaceDescriptor_t workDesc;
122  HANDLE_CUTN_ERROR(cutensornetCreateWorkspaceDescriptor(cutnHandle, &workDesc));
123  HANDLE_CUTN_ERROR(cutensornetSamplerPrepare(cutnHandle, sampler, workSizeAvailable, workDesc, 0x0));
124  std::cout << "Prepared the quantum circuit state sampler\n";
125  double flops {0.0};
126  HANDLE_CUTN_ERROR(cutensornetSamplerGetInfo(cutnHandle, sampler,
127                    CUTENSORNET_SAMPLER_INFO_FLOPS, &flops, sizeof(flops)));
128  std::cout << "Total flop count per sample = " << (flops/1e9) << " GFlop\n";

Allocate the workspace buffer on GPU and setup the workspace#

Allocate the required scratch workspace buffer, and provide extra buffer for cache workspace.

132  // Attach the workspace buffer
133  int64_t worksize {0};
134  HANDLE_CUTN_ERROR(cutensornetWorkspaceGetMemorySize(cutnHandle,
135                                                      workDesc,
136                                                      CUTENSORNET_WORKSIZE_PREF_RECOMMENDED,
137                                                      CUTENSORNET_MEMSPACE_DEVICE,
138                                                      CUTENSORNET_WORKSPACE_SCRATCH,
139                                                      &worksize));
140  assert(worksize > 0);
141
142  void *d_scratch {nullptr};
143  if(worksize <= workSizeAvailable) {
144    HANDLE_CUDA_ERROR(cudaMalloc(&d_scratch, worksize));
145    std::cout << "Allocated " << worksize << " bytes of scratch memory on GPU: "
146              << "[" << d_scratch << ":" << (void*)(((char*)(d_scratch))  + worksize) << ")\n";
147
148    HANDLE_CUTN_ERROR(cutensornetWorkspaceSetMemory(cutnHandle, workDesc, CUTENSORNET_MEMSPACE_DEVICE,
149                      CUTENSORNET_WORKSPACE_SCRATCH, d_scratch, worksize));
150  }else{
151    std::cout << "ERROR: Insufficient workspace size on Device!\n";
152    std::abort();
153  }
154
155  int64_t reqCacheSize {0};
156  HANDLE_CUTN_ERROR(cutensornetWorkspaceGetMemorySize(cutnHandle,
157                                                      workDesc,
158                                                      CUTENSORNET_WORKSIZE_PREF_RECOMMENDED,
159                                                      CUTENSORNET_MEMSPACE_DEVICE,
160                                                      CUTENSORNET_WORKSPACE_CACHE,
161                                                      &reqCacheSize));
162
163  //query the free size again
164  HANDLE_CUDA_ERROR(cudaMemGetInfo(&freeSize, &totalSize));
165  // grab the minimum of [required size, or 90% of the free memory (to avoid oversubscribing)]
166  const std::size_t cacheSizeAvailable = std::min(static_cast<size_t>(reqCacheSize), size_t(freeSize * 0.9) - (size_t(freeSize * 0.9) % 4096));
167  void *d_cache {nullptr};
168  HANDLE_CUDA_ERROR(cudaMalloc(&d_cache, cacheSizeAvailable));
169  std::cout << "Allocated " << cacheSizeAvailable << " bytes of cache memory on GPU: "
170            << "[" << d_cache << ":" << (void*)(((char*)(d_cache))  + cacheSizeAvailable) << ")\n";
171  HANDLE_CUTN_ERROR(cutensornetWorkspaceSetMemory(cutnHandle,
172                                                  workDesc,
173                                                  CUTENSORNET_MEMSPACE_DEVICE,
174                                                  CUTENSORNET_WORKSPACE_CACHE,
175                                                  d_cache,
176                                                  cacheSizeAvailable));
177  std::cout << "Set the workspace buffer\n";

Perform sampling of the final quantum circuit state#

Once everything had been set up, we perform sampling of the quantum circuit state and print the output samples.

181  // Sample the quantum circuit state
182  std::vector<int64_t> samples(numQubits * numSamples); // samples[SampleId][QubitId] reside in Host memory
183  HANDLE_CUTN_ERROR(cutensornetSamplerSample(cutnHandle, sampler, numSamples, workDesc, samples.data(), 0));
184  std::cout << "Performed quantum circuit state sampling\n";
185  std::cout << "Bit-string samples:\n";
186  for(int64_t i = 0; i < numSamples; ++i) {
187    for(int64_t j = 0; j < numQubits; ++j) std::cout << " " << samples[i * numQubits + j];
188    std::cout << std::endl;
189  }

Free resources#

193  // Destroy the workspace descriptor
194  HANDLE_CUTN_ERROR(cutensornetDestroyWorkspaceDescriptor(workDesc));
195  std::cout << "Destroyed the workspace descriptor\n";
196
197  // Destroy the quantum circuit sampler
198  HANDLE_CUTN_ERROR(cutensornetDestroySampler(sampler));
199  std::cout << "Destroyed the quantum circuit state sampler\n";
200
201  // Destroy the quantum circuit state
202  HANDLE_CUTN_ERROR(cutensornetDestroyState(quantumState));
203  std::cout << "Destroyed the quantum circuit state\n";
204
205  HANDLE_CUDA_ERROR(cudaFree(d_scratch));
206  HANDLE_CUDA_ERROR(cudaFree(d_cache));
207  HANDLE_CUDA_ERROR(cudaFree(d_gateCX));
208  HANDLE_CUDA_ERROR(cudaFree(d_gateH));
209  std::cout << "Freed memory on GPU\n";
210
211  // Finalize the cuTensorNet library
212  HANDLE_CUTN_ERROR(cutensornetDestroy(cutnHandle));
213  std::cout << "Finalized the cuTensorNet library\n";
214
215  return 0;
216}