文摘
Quantum computing is an emerging field that offers revolutionary and exciting new ways to process, store, and transport information. Moreover, realizing large-scale quantum systems requires advances in science and engineering that are now very close to reality. Such systems will need many classical and quantum parts that must fit together into one architecture, in which each component plays an integral role over the course of an application execution. Therefore, it is important that we draw upon the experiences gained from traditional architectures, to develop a model for a large-scale quantum system that provides the methodology necessary for the many different components to work together.;In this thesis, I describe the design of the Quantum Logic Array (QLA) architecture, which tackles critical scalability issues such as the cost of error correction and distributing data over large-distances. To accurately model the performance of the QLA architecture---the ion-trap technology is used since every component necessary for universal quantum computation has been demonstrated in the laboratory. However, due to its design approach for maximizing parallelism, the QLA system suffers from large area overhead. To combat the area problem, I describe an architecture that uses the concept of hardware specialization employed in traditional architectures. The new architecture is based on the QLA model, but is divided into separately optimized quantum memory hierarchy and logic specific regions. The result is a scalable system design that exploits the available parallelism to balance both quantum and classical resources, while both reducing the area of the chip and increasing its performance.
