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International Symposium on Symbolic and Numeric Algorithms for Scientific Computing (SYNASC)

A Grid Enabled Quantum Computer Simulator

Simona Caraiman, Alexandru Archip, Vasile Manta

Published Sep 1, 2009• 6 citations
Publisher

Abstract

Simulation of quantum computers using classical computers is a computationally hard problem, requiring a huge amount of operations and storage. Grid systems are a good choice for simulating quantum algorithms, since they provide access to high-performance computer clusters. In this paper we present the design of a message passing parallel version of the quantum computer simulator, QCL, deployed as a grid service. After describing the architecture of our grid service and the parallelization strategy for the general single qubit operator, we present the performance measurements for some test cases, showing the speedups obtained.

DOI
10.1109/synasc.2009.57

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Simulation of quantum computers using classical computers is a computationally hard problem, requiring a huge amount of operations and storage. Grid systems are a good choice for simulating quantum algorithms, since they provide access to high-performance computer clusters. In this paper we present the design of a message passing parallel version of the quantum computer simulator, QCL, deployed as a grid service. After describing the architecture of our grid service and the parallelization strategy for the general single qubit operator, we present the performance measurements for some test cases, showing the speedups obtained.
Simulation of quantum computers using classical computers is a computationally hard problem, requiring a huge amount of operations and storage. Parallelization can alleviate this problem, allowing the simulation of more qubits at the same time or the same number of qubits to be simulated in less time. A promising approach is represented by executing these simulators in Grid systems that can provide access to high performance resources. In this paper we present a parallel implementation of the QC-lib quantum computer simulator deployed as a Grid service. Using a specific scheme for partitioning the terms describing quantum states and efficient parallelization of the general singe qubit operator and of the controlled operators, very good speed-ups were obtained for the simulation of the quantum search problem.
Simulation of quantum computers using classical computers is a hard problem with high memory and computational requirements. Parallelization can alleviate this problem, allowing the simulation of more qubits at the same time or the same number of qubits to be simulated in less time. A promising approach is to exploit the high performance computing capabilities provided by the latest graphical processing units. In this paper we present a parallel implementation of the QC-lib quantum computer simulator on the GPU using the CUDA programming model. The proposed scheme for partitioning the terms that describe the state of a quantum register takes advantage of the specific characteristics of the CUDA memory spaces and allows for an efficient parallelization of the general singe qubit operator. Experimental results indicate that very good speed-ups can be obtained in contrast with the sequential implementation.
The unique principles of quantum mechanics may one day enable computers to perform operations that would be impossible on a classical computer. Although no one knows whether it will be possible to build a large-scale, functional, and stable quantum computer, researchers can study quantum-mechanical systems and develop algorithms and circuits by simulating quantum systems in software. Performance and memory bottlenecks prevent most current quantum computer simulators from being able to simulate quantum systems that are large enough to be useful. In this thesis, we develop a matrix-free sequential quantum computer simulator to vastly improve both time and memory performance of sequential code on a single processor. Next, we distribute the matrix-free algorithm over multiple parallel processors using the Message Passing Interface in order to simulate quantum systems that are too large to reside wholly within the memory of a single processor. Finally, we simulate various quantum circuits using the Hamming high-performance computing cluster in order to conduct algorithmic analysis.
This thesis describes the design and implementation of an environment to allow quantum computation to be simulated on classical computers. Although it is believed that quantum computers cannot in general be efficiently simulated classically, it is nevertheless possible to simulate small but interesting systems, on the order of a few tens of quantum bits. Since the state of the art of physical implementations is less than 10 bits, simulation remains a useful tool for understanding the behavior of quantum algorithms. To create a suitable envrionment for simulation, we constructed a 32-node cluster of workstation class computers linked with a high speed (gigabit Ethernet) network. We then wrote an initial simulation environment based on parallel linear algebra libraries with a Matlab front end. These libraries operated on large matrices representing the problem being simulated. The parallel Matlab environment demonstrated a degree of parallel speedup as we added processors, but overall execution times were high, since the amount of data scaled exponentially with the size of the problem. This increased both the number of operations that had to be performed to compute the simulation, and the volume of data that had to be communicated between the nodes as they were computing. The scaling also affected memory utilization, limiting us to a maximum problem size of 14 qubits. In an attempt to increase simulation efficiency, we revisited the design of the simulation environment. Many quantum algorithms have a structure that can be described using the tensor product operator from linear algebra. We believed that a new simulation environment based on this tensor product structure would be substantially more efficient than one based on large matrices. We designed a new simulation envrionment that exploited this tensor product structure. Benchmarks that we performed on the new simulation environment confirmed that it was substantially more efficient, allowing us to perform simulations of the quantum Fourier transform and the discrete approximation to the solution of 3-SAT by adiabatic evolution up to 25 qubits in a reasonable time. Thesis Supervisor: Stephen A. Benton Title: Professor of Media Arts and Sciences
This paper reports on work to parallelize QC-lib, a C++ library for the simulation of quantum computers at an abstract functional level. After a brief introduction to quantum computing, we give an outline of QC-lib, then describe the parallelization using MPI of the general single qubit gate and the controlled-NOT gate (CNOT). Although QC-lib also implements other gates, this combination is already universal for quantum computing, and has allowed us to implement Grover's quantum search algorithm as a test case. We present some performance measurements made on a Beowulf cluster, which show reasonable speedups for Grover's algorithm.
With the deeply studied of quantum computing by research fellows, the computational complexity and time complexity of quantum algorithms gradually increase. The quantum computing simulator provides an effective platform for the development and verification of quantum algorithms. However, the running time and memory overhead during calculation will increase exponentially with the number of qubits. Therefore, the difficulty of high-speed quantum computing on classical computers will gradually increase. At present, a single node has been unable to meet the resource requirements of the algorithm in the quantum computing process, and it is necessary to expand the memory resources in the multi-node computing cluster. Message passing interface has high performance inter-process communication capabilities, which can balance the data transmission between different hosts. Quantum computing tasks can be distributed on several servers to work together to solve the same problem. Therefore, this paper designs an advanced scheme of deploying quantum computing programs on cloud computing platform to support message exchanging between servers using message passing interface to accelerate quantum computing.