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(int argc, char **argv)
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(cutensornetStateApplyTensor(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(cutensornetStateApplyTensor(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";
Allocate the scratch buffer on GPU¶
105 // Query the free memory on Device
106 std::size_t freeSize {0}, totalSize {0};
107 HANDLE_CUDA_ERROR(cudaMemGetInfo(&freeSize, &totalSize));
108 const std::size_t scratchSize = (freeSize - (freeSize % 4096)) / 2; // use half of available memory with alignment
109 void *d_scratch {nullptr};
110 HANDLE_CUDA_ERROR(cudaMalloc(&d_scratch, scratchSize));
111 std::cout << "Allocated " << scratchSize << " bytes of scratch memory on GPU: "
112 << "[" << d_scratch << ":" << (void*)(((char*)(d_scratch)) + scratchSize) << ")\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.
116 // Configure the quantum circuit sampler
117 const int32_t numHyperSamples = 8; // desired number of hyper samples used in the tensor network contraction path finder
118 HANDLE_CUTN_ERROR(cutensornetSamplerConfigure(cutnHandle, sampler,
119 CUTENSORNET_SAMPLER_OPT_NUM_HYPER_SAMPLES, &numHyperSamples, sizeof(numHyperSamples)));
Prepare the tensor network state sampler¶
Let’s create a workspace descriptor and prepare the tensor network state sampler.
123 // Prepare the quantum circuit sampler
124 cutensornetWorkspaceDescriptor_t workDesc;
125 HANDLE_CUTN_ERROR(cutensornetCreateWorkspaceDescriptor(cutnHandle, &workDesc));
126 HANDLE_CUTN_ERROR(cutensornetSamplerPrepare(cutnHandle, sampler, scratchSize, workDesc, 0x0));
127 std::cout << "Prepared the quantum circuit state sampler\n";
Set up the workspace¶
Now we can set up the required workspace buffer.
131 // Attach the workspace buffer
132 int64_t worksize {0};
133 HANDLE_CUTN_ERROR(cutensornetWorkspaceGetMemorySize(cutnHandle,
134 workDesc,
135 CUTENSORNET_WORKSIZE_PREF_RECOMMENDED,
136 CUTENSORNET_MEMSPACE_DEVICE,
137 CUTENSORNET_WORKSPACE_SCRATCH,
138 &worksize));
139 assert(worksize > 0);
140 if(worksize <= scratchSize) {
141 HANDLE_CUTN_ERROR(cutensornetWorkspaceSetMemory(cutnHandle, workDesc, CUTENSORNET_MEMSPACE_DEVICE,
142 CUTENSORNET_WORKSPACE_SCRATCH, d_scratch, worksize));
143 }else{
144 std::cout << "ERROR: Insufficient workspace size on Device!\n";
145 std::abort();
146 }
147 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.
151 // Sample the quantum circuit state
152 std::vector<int64_t> samples(numQubits * numSamples); // samples[SampleId][QubitId] reside in Host memory
153 HANDLE_CUTN_ERROR(cutensornetSamplerSample(cutnHandle, sampler, numSamples, workDesc, samples.data(), 0));
154 std::cout << "Performed quantum circuit state sampling\n";
155 std::cout << "Bit-string samples:\n";
156 for(int64_t i = 0; i < numSamples; ++i) {
157 for(int64_t j = 0; j < numQubits; ++j) std::cout << " " << samples[i * numQubits + j];
158 std::cout << std::endl;
159 }
Free resources¶
163 // Destroy the workspace descriptor
164 HANDLE_CUTN_ERROR(cutensornetDestroyWorkspaceDescriptor(workDesc));
165 std::cout << "Destroyed the workspace descriptor\n";
166
167 // Destroy the quantum circuit sampler
168 HANDLE_CUTN_ERROR(cutensornetDestroySampler(sampler));
169 std::cout << "Destroyed the quantum circuit state sampler\n";
170
171 // Destroy the quantum circuit state
172 HANDLE_CUTN_ERROR(cutensornetDestroyState(quantumState));
173 std::cout << "Destroyed the quantum circuit state\n";
174
175 HANDLE_CUDA_ERROR(cudaFree(d_scratch));
176 HANDLE_CUDA_ERROR(cudaFree(d_gateCX));
177 HANDLE_CUDA_ERROR(cudaFree(d_gateH));
178 std::cout << "Freed memory on GPU\n";
179
180 // Finalize the cuTensorNet library
181 HANDLE_CUTN_ERROR(cutensornetDestroy(cutnHandle));
182 std::cout << "Finalized the cuTensorNet library\n";
183
184 return 0;
185}