  We define some of the programming and system-level challenges facing the
application of quantum processing to high-performance computing. Alongside
barriers to physical integration, prominent differences in the execution of
quantum and conventional programs challenges the intersection of these
computational models. Following a brief overview of the state of the art, we
discuss recent advances in programming and execution models for hybrid
quantum-classical computing. We discuss a novel quantum-accelerator framework
that uses specialized kernels to offload select workloads while integrating
with existing computing infrastructure. We elaborate on the role of the host
operating system to manage these unique accelerator resources, the prospects
for deploying quantum modules, and the requirements placed on the language
hierarchy connecting these different system components. We draw on recent
advances in the modeling and simulation of quantum computing systems with the
development of architectures for hybrid high-performance computing systems and
the realization of software stacks for controlling quantum devices. Finally, we
present simulation results that describe the expected system-level behavior of
high-performance computing systems composed from compute nodes with quantum
processing units. We describe performance for these hybrid systems in terms of
time-to-solution, accuracy, and energy consumption, and we use simple
application examples to estimate the performance advantage of quantum
acceleration.
