arXiv 1801.010372018-01quant-phcs.DC

量子线路经典模拟的分布式存储技术

Distributed Memory Techniques for Classical Simulation of Quantum Circuits

Ryan LaRose

备注：: Fixed typos, minor reformatting

摘要：

在本文中，我们描述，实现和测试的性能分布式存储器模拟的量子线路上的MSU拉科尼亚Top500超级计算机。使用OpenMP和MPI混合并行化，我们首先使用一个分布式的矩阵-向量乘法与一维分区，并讨论了这种方法的缺点，由于模拟量子计算机的指数内存需求。然后，我们描述了一种更有效的方法，该方法仅存储$n$量子比特状态向量$|ψ\rangle$的$2^n$幅度，并优化其单节点性能。在我们的多节点实现中，我们使用单振幅通信协议，该协议最大化能够被模拟的量子位的数量，并且最小化需要通信的量子位与不需要通信的量子位的比率，并且我们提出了一种用于有效地确定处理器之间的通信对的算法。我们在单个节点上模拟了多达30个量子位，在64个节点上模拟了33个量子位。最后，我们讨论了我们的通信方案的优点和缺点，提出了潜在的改进，并描述了其他优化，如存储在内存中的状态向量非顺序映射通信要求的电路中的空闲量子位。

英文摘要：

In this paper we describe, implement, and test the performance of distributed memory simulations of quantum circuits on the MSU Laconia Top500 supercomputer. Using OpenMP and MPI hybrid parallelization, we first use a distributed matrix-vector multiplication with one-dimensional partitioning and discuss the shortcomings of this method due to the exponential memory requirements in simulating quantum computers. We then describe a more efficient method that stores only the $2^n$ amplitudes of the $n$ qubit state vector $|ψ\rangle$ and optimize its single node performance. In our multi-node implementation, we use a single amplitude communication protocol that maximizes the number of qubits able to be simulated and minimizes the ratio of qubits that require communication to those that do not, and we present an algorithm for efficiently determining communication pairs among processors. We simulate up to 30 qubits on a single node and 33 qubits with the state vector partitioned across 64 nodes. Lastly, we discuss the advantages and disadvantages of our communication scheme, propose potential improvements, and describe other optimizations such as storing the state vector non-sequentially in memory to map communication requirements to idle qubits in the circuit.

机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。

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