Current and near-future quantum computers face resource limitations due to noise and low qubit counts. Despite this, effective quantum advantage can still be achieved due to the exponential nature of bit-to-qubit conversion. However, optimizing the software architecture of these systems is essential to utilize available resources efficiently. Unfortunately, the focus on user-friendly quantum computers has obscured critical steps in the software stack, leading to ripple effects into the stack's upper layer induced by limitations in current qubit implementations. This paper unveils the hidden interplay among layers of the quantum software stack.
Current and near-future quantum computers face resource limitations due to noise and low qubit counts. Despite this, effective quantum advantage can still be achieved due to the exponential nature of bit-to-qubit conversion. However, optimizing the software architecture of these systems is essential to utilize available resources efficiently. Unfortunately, the focus on user-friendly quantum computers has obscured critical steps in the software stack, leading to ripple effects into the stack's upper layer induced by limitations in current qubit implementations. This paper unveils the hidden interplay among layers of the quantum software stack.
Building a quantum computer that surpasses the computational power of its classical counterpart is a great engineering challenge. Quantum software optimizations can provide an accelerated pathway to the first generation of quantum computing (QC) applications that might save years of engineering effort. Current quantum software stacks follow a layered approach similar to the stack of classical computers, which was designed to manage the complexity. In this review, we point out that greater efficiency of QC systems can be achieved by breaking the abstractions between these layers. We review several works along this line, including two hardware-aware compilation optimizations that break the quantum instruction set architecture (ISA) abstraction and two error-correction/information-processing schemes that break the qubit abstraction. Last, we discuss several possible future directions.
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.
The advances in quantum hardware with functional quantum processors integrating tens of noisy qubits, together with the availability of near-term quantum algorithms have allowed the development of the so-called full-stacks that bridge quantum applications with quantum devices. In this talk, we will provide an overview of the different layers of the quantum computing full-stack, with emphasis on the software ones that include the compilation of quantum algorithms. We will then discuss the need for optimal physical-aware and algorithm-driven compilation techniques in the midst of the NISQ (Noisy Intermediate-scale quantum) era. We will also focus on key principles for architecting quantum computers such as codesign, optimization and benchmarking and illustrate how the use of structured design space exploration methodologies could help towards the development of a cross-layer codesign framework for full-stack quantum computing systems. Finally, we will talk about the scalability of quantum computing systems, which is one of the main challenges the quantum computing community is currently facing.
This short report explores the (non exhaustive) current state of quantum technologies, their potential applications, and the challenges that must be addressed to harness their full potential. In particular we will focus on the quantum computer architecture and its ecosystem. Such architecture represents a complex, multi-layered system that integrates quantum and classical components to enable the execution of quantum algorithms. This manuscript is then organized as follows : first we will introduce the quantum processing unit, the lowest layer of a quantum computer. Then we will progress from the lowest to the higher layer of the system architectures : measurement, circuit control, error correction and mitigation system, the quantum compiler and finally the software stack, with particular emphasis on the interactions between these components
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.
Abstract We propose a layer model to specify functionality and interfacing for hardware and software modules, to enable modular quantum computers. The group of lower layers covers multiple stacks, one for each hardware architecture, while the upper layers are defined around a common software stack. A hardware abstraction layer connects the two. The addition of a separate communication unit offers a robust separation between the stack and the outside world, and allows controlled access for multiple users as well as for being a server to hybrid computing systems.