Robust Cache-Aware Quantum Processor Layout

TL;DR: This work modify the Qiskit quantum simulation library to work with caches and investigate the effects of region size and topology on the swap characteristics of algorithm execution, and presents mix scale-out simulations to examine the impact of cache on future large-scale machines.

Abstract: Quantum computation has taken over as one of the largest current research areas in computer architecture and information theory. With the potential to make a large number of factorization-based encryption methods obsolete, companies and governments around the globe are racing to build the first large-scale quantum computer. Currently, most quantum computers are noisy intermediate-scale quantum (NISQ), using a relatively small collection of unreliable qubits. While error correction methods exist, they require a large number of ancilla qubits to protect the data qubits which is not practical for use on current NISQ machines. However, following the Dowling-Neven Law, available qubits on a superconducting chip are growing at an exponential rate similar to Moore’s Law. Looking toward larger scale quantum machines, we examine a method to increase usable qubit density of quantum machines implementing error correction by using quantum caches that utilize simpler error correction codes. Alternatively, this also allows for the design of reliable systems while meeting the performance and qubit requirements for quantum algorithms. We modify the Qiskit quantum simulation library to work with caches and investigate the effects of region size and topology on the swap characteristics of algorithm execution. We also present our results and discuss recommended topologies for each algorithm. Lastly, we present mix scale-out simulations to examine the impact of cache on future large-scale machines. The default central cache topology gains a maximum performance increase of 2.15 times compared to the worst topology, which creates a robust cache-aware quantum processor layout.