  High performance computing (HPC) and cloud have traditionally been separate,
and presented in an adversarial light. The conflict arises from disparate
beginnings that led to two drastically different cultures, incentive
structures, and communities that are now in direct competition with one another
for resources, talent, and speed of innovation. With the emergence of converged
computing, a new paradigm of computing has entered the space that advocates for
bringing together the best of both worlds from a technological and cultural
standpoint. This movement has emerged due to economic and practical needs.
Emerging heterogeneous, complex scientific workloads that require an
orchestration of services, simulation, and reaction to state can no longer be
served by traditional HPC paradigms. However, while cloud offers automation,
portability, and orchestration, as it stands now it cannot deliver the network
performance, fine-grained resource mapping, or scalability that these same
simulations require. These novel requirements call for change not just in
workflow software or design, but also in the underlying infrastructure to
support them. This is one of the goals of converged computing. While the future
of traditional HPC and commercial cloud cannot be entirely known, a reasonable
approach to take is one that focuses on new models of convergence, and a
collaborative mindset. In this paper, we introduce a new paradigm for compute
-- a traditional HPC workload manager, Flux Framework, running seamlessly with
a user-space Kubernetes "Usernetes" to bring a service-oriented, modular, and
portable architecture directly to on-premises HPC clusters. We present
experiments that assess HPC application performance and networking between the
environments, and provide a reproducible setup for the larger community to do
exactly that.
