QPlayer: Lightweight, scalable, and fast quantum simulator

Abstract

With the rapid evolution of quantum computing, digital quantum simulations are essential for quantum algorithm verification, quantum error analysis, and new quantum applications. However, the exponential increase in memory overhead and operation time is challenging issues that have not been solved for years. We propose a novel approach that provides more qubits and faster quantum operations with smaller memory than before. Our method selectively tracks realized quantum states using a reduced quantum state representation scheme instead of loading the entire quantum states into memory. This method dramatically reduces memory space ensuring fast quantum computations without compromising the global quantum states. Furthermore, our empirical evaluation reveals that our proposed idea outperforms traditional methods for various algorithms. We verified that the Grover algorithm supports up to 55 qubits and the surface code algorithm supports up to 85 qubits in 512 GB memory on a single computational node, which is against the previous studies that support only between 35 qubits and 49 qubits.

ReQUSA: a novel ReRAM-based hardware accelerator architecture for high-speed quantum computer simulation

“…However, this method does not significantly reduce the simulation time because all qubit state vectors must be repeatedly multiplied by the 2 × 2 matrix. We thus adopt a more efficient simulation technique combined with the RS developed in [14]. By applying quantum gates only to the RSs of qubits, our algorithm drastically reduces the number of VMM operations from that of the previous simulation technique.…”

“…For instance, a 50-qubit quantum computer demands a 2 50 sized vector, equating to approximately 10 15 elements and requiring around 8 petabytes of RAM storage. Recent studies have introduced resource-efficient simulation methods, including optimized single-node frameworks [14,15], simulators for distributed systems [11], and simulators employing data compression techniques.…”

“…As the number of qubits increases, the number of operations on the state vector and matrix becomes exceedingly large and the memory demands increase accordingly. Although several attempts to minimize the memory usage have been published [10,14,[25][26][27][28], an effective solution remains elusive.…”

“…To minimize the computational burden and reduce the memory requirements of large state vectors and quantum gate matrices, Jin et al proposed a realized-state method that represents the qubit states [14]. RSs represent only those qubits with non-zero amplitudes.…”

“…In particular, the ReRAM is specialized for VMM operations in the analog domain. To avoid dimensional expansion of the state vector and quantum gate, we adopt the reduced VMM operation method based on the realized state (RS) described in [14]. The simulation time of our proposed architecture is ×10 4 shorter than that of QuEST, ×10 3 and ×10 2 shorter than those of QPlayer and Qiskit, respectively.…”