Quantum Computing (QC) is an emerging technology that requires customized tools, such as software stacks and programming interfaces. However, currently, the tools are generally tightly coupled and exhibit limited interoperability. This, in particular, affects High Performance Computing (HPC) facilities and data centers, which are required to support multiple programming interfaces. In this paper, we introduce MQSS Client, a unifying, context-aware access layer and programming library that decouples the programming interfaces and the underlying compilation and runtime stack. MQSS Client aims to support all existing programming interfaces by providing abstractions for resources, jobs, and results. It provides two access modes to accommodate the varied needs of remote and HPC users. Thus, interoperability between software stacks and programming interfaces increases.
Quantum Computing (QC) is an emerging technology that requires customized tools, such as software stacks and programming interfaces. However, currently, the tools are generally tightly coupled and exhibit limited interoperability. This, in particular, affects High Performance Computing (HPC) facilities and data centers, which are required to support multiple programming interfaces. In this paper, we introduce MQSS Client, a unifying, context-aware access layer and programming library that decouples the programming interfaces and the underlying compilation and runtime stack. MQSS Client aims to support all existing programming interfaces by providing abstractions for resources, jobs, and results. It provides two access modes to accommodate the varied needs of remote and HPC users. Thus, interoperability between software stacks and programming interfaces increases.
Quantum computing systems are increasingly accessed through software stacks that hide hardware-specific details behind higher-level abstractions. This is necessary because current quantum resources differ in their physical realisation, supported program formats, execution parameters, calibration data, status models, and result representations. At the same time, independent software stack initiatives create an interoperability challenge: even systems with similar goals may not communicate directly if their APIs encode different assumptions. This thesis studies this problem for the Munich Quantum Software Stack (MQSS), whose backend abstraction is the Quantum Device Management Interface (QDMI), and QCI Connect, a modular full-stack quantum computing platform developed within the DLR Quantum Computing Initiative. The goal is to connect these systems bidirectionally while preserving their architectural abstractions. In one direction, MQSS resources are exposed as QCI Connect QPUs via a dedicated QPU connector. In the other direction, QCI Connect is exposed as a QDMI-compatible device that translates QDMI session, query, job, status, cancellation, and result calls into QCI Connect API requests. The thesis compares the relevant API concepts and implements mappings for resource discovery, job submission, status handling, cancellation, and result retrieval. The implementation shows that bidirectional communication is feasible through existing extension points in both stacks. It also reveals semantic mismatches, including incomplete metadata equivalence, differences in status granularity, assumptions about circuit formats, and result fields requiring custom handling. These findings show that interoperability between quantum software stacks is possible, but long-term portability requires clearer standardisation of capabilities, execution parameters, status models, and result schemas.
Quantum computers are making their way into High Performance Computing (HPC) centers as next-generation accelerators. Due to their physical implementation as mostly large appliances in separate racks, their number in typical data centers is significantly lower than the number of nodes offloading work to them, unlike the case with GPU accelerators. As a consequence, they form large-scale disaggregated infrastructures that pose a number of integration challenges due to their diverse implementation technologies and their need to be used as a shared resource for optimal utilization. Running hybrid High Performance Computing-Quantum Computing (HPCQC) applications in HPC environments, where the quantum portion is offloaded to the quantum processing units (QPUs), requires sophisticated resource management strategies to optimize resource utilization and performance. In this paper, we present one aspect of the Munich Quantum Software Stack (MQSS) - a Just-In-Time (JIT) compilation and execution software stack for quantum and hybrid quantum-HPC workloads - beneficial for integrating disaggregated quantum accelerators into traditional HPC workflows. MQSS is centered around a series of novel contributions aimed at optimizing the compilation process while managing the disaggregated resources ensuring efficient utilization of all available quantum resources. The key stages of our JIT compilation stack involve hardware-agnostic optimizations, quantum circuit cutting – when necessary – and a novel hardware platform selection process. Included here is description of the use of the MQSS’s Quantum Device Management Interface (QDMI), a unified interface between the software stack and the quantum accelerators, which allows connection to several, potentially different, quantum resources. Our methodology demonstrates notable advancements in HPCQC integration workflows, offering researchers a powerful framework for leveraging quantum computational capabilities. Overall, our work represents a significant step towards the practical integration of disaggregated quantum devices within the realm of supercomputing, unlocking new avenues for computational exploration and discovery.
Quantum resources are increasingly integrated into high-performance computing (HPC) and cloud environments, but quantum high-performance computing (QHPC) software stacks remain isolated, often proprietary, full-stack solutions lacking common interfaces across runtime, resource management, orchestration, and execution layers. This paper analyzes nine production QHPC stacks and identifies common design patterns and emerging requirements, covering deployment models, application interaction patterns, SDK support, and readiness for fault-tolerant operation. The survey exposes consistent needs in runtime abstraction, resource management, interconnect semantics, and observability. Based on these findings, we propose the open quantum-HPC software ecosystem ( openQSE) reference architecture as a first step toward unifying the state-of-the-practice. openQSE defines a set of layer boundaries that allow different implementations to interoperate while preserving deployment flexibility, and is structured to support both current noisy intermediate-scale quantum (NISQ) workloads and future fault-tolerant quantum computing (FTQC) systems without changes to upper-layer application interfaces.
Quantum computing is advancing rapidly, with notable progress in both hardware and algorithm development. However, to make quantum computing truly accessible and usable across disciplines, a comprehensive, efficient and unified software stack is essential. Such a software stack must be flexible enough to support diverse hardware platforms and evolving algorithms, while enabling programming models for a wide range of users from quantum specialists to users without deep quantum expertise. Additionally, a software stack must support dynamic resource management for efficient system utilization as well as seamless integration with classical High-Performance Computing (HPC) environments. The latter is key, as quantum systems are increasingly envisioned as accelerators within hybrid workflows, supporting various levels of integration from loosely to tightly coupled. Despite numerous discussions, conceptual proposals, and initial efforts in recent years, few tangible implementations of such full-featured software stacks currently exist.
As quantum computing systems mature and move from laboratories to production computing environments, corresponding software stacks are becoming key for their successful utilization. In particular, the expected use of quantum systems as HPC accelerators requires a deep integration with the existing and widely deployed HPC software stacks. Additionally, new requirements such as dynamic compilation and new challenges for tools and programming models must be considered. We tackle these challenges by developing the Munich Quantum Software Stack—a comprehensive initiative by the Munich Quantum Valley to offer a flexible, efficient, and user-oriented software environment. In this poster, we describe the core components and workflows, and how they will enable this transformation from quantum experiments to quantum accelerators.
The Munich Quantum Software Stack (MQSS) is a compilation and runtime infrastructure designed to bridge the gap between high-performance computing (HPC) and quantum computing (QC). A unified, extensible, and efficient compilation framework becomes important as quantum devices and applications scale. This paper proposes the integration of Multi-Level Intermediate Representation (MLIR) as intermediate representation into the MQSS to address the challenges of optimizing and compiling hybrid classical-quantum applications across diverse quantum devices. Accordingly, the MQSS can separate abstraction layers, enabling high-level optimizations, seamless integration of existing quantum dialects, and targetspecific optimizations for diverse quantum devices.