Bosehedral: Compiler Optimization for Bosonic Quantum Computing

Bosonic quantum computing, based on the infinite-dimensional qumodes, has shown promise for various practical applications that are classically hard. However, the lack of compiler optimizations has hindered its full potential. This paper introduces Bosehedral, an efficient compiler optimization framework for (Gaussian) Boson sampling on Bosonic quantum hardware. Bosehedral overcomes the challenge of handling infinite-dimensional qumode gate matrices by performing all its program analysis and optimizations at a higher algorithmic level, using a compact unitary matrix representation. It optimizes qumode gate decomposition and logical-to-physical qumode mapping, and introduces a tunable probabilistic gate dropout method. Overall, Bosehedral significantly improves the performance by accurately approximating the original program with much fewer gates. Our evaluation shows that Bosehedral can largely reduce the program size but still maintain a high approximation fidelity, which can translate to significant end-to-end application performance improvement

QASMTrans: A QASM based Quantum Transpiler Framework for NISQ Devices

The success of a quantum algorithm hinges on the ability to orchestrate a successful application induction. Detrimental overheads in mapping general quantum circuits to physically implementable routines can be the deciding factor between a successful and erroneous circuit induction. In QASMTrans, we focus on the problem of rapid circuit transpilation. Transpilation plays a crucial role in converting high-level, machine-agnostic circuits into machine-specific circuits constrained by physical topology and supported gate sets. The efficiency of transpilation continues to be a substantial bottleneck, especially when dealing with larger circuits requiring high degrees of inter-qubit interaction. QASMTrans is a high-performance C++ quantum transpiler framework that demonstrates up to 369X speedups compared to the commonly used Qiskit transpiler. We observe speedups on large dense circuits such as uccsd_n24 and qft_n320 which require O(10^6) gates. QASMTrans successfully transpiles the aforementioned circuits in 69s and 31s, whilst Qiskit exceeded an hour of transpilation time. With QASMTrans providing transpiled circuits in a fraction of the time of prior transpilers, potential design space exploration, and heuristic-based transpiler design becomes substantially more tractable. QASMTrans is released at http://github.com/pnnl/qasmtrans

Towards High-Performance, Efficient, and Reliable Quantum Computing System

As the new ``race to the moon'', quantum computing can possibly trigger a computation revolution due to its strong potential in several important domains, e.g., cryptography, chemistry simulation, optimization, and machine learning. However, as an emerging research area, grand challenges remain ahead since state-of-the-art quantum computing, from software to hardware, is still highly immature. This dissertation explores high-performance, efficient, and reliable quantum computing systems, and strikes a synergy among different technology stacks, including application, programming language, compiler optimization, hardware architecture design, and simulation. In particular, this dissertation focuses on two directions: 1) cross-layer co-design for quantum computing system; and 2) enabling deep quantum software/compiler optimizations at the high level. In the first direction, this dissertation studies how to efficiently map quantum software to hardware via carefully designed compiler optimization, and then investigates the application-specific architecture design with substantial hardware efficiency improvement. Following the application-specific principle and putting the algorithm optimization and hardware design together, this dissertation proposed a software-hardware co-optimization for chemistry simulation and achieved a wide range of benefits across multiple system stacks. In the second direction, this dissertation explores leveraging the algorithmic information, which is usually carried by new high-level programming languages, to design quantum software optimizations that are hard to implement in conventional quantum software infrastructures. These optimizations include a Pauli-string-based intermediate representation for large-scope compiler optimization on quantum simulation programs, a projection-operator-based runtime assertion language for efficient quantum program testing and debugging, and a trial scheduling technique to identify and eliminate redundant computation in noisy quantum computing simulation