Modern scientific discovery depends heavily on computational workflows that can orchestrate large and complex in-silico experiments. The evolution of workflow application requirements in contemporary computing is pushing the need to integrate a diverse portfolio of services for high-performance computing (HPC), artificial intelligence (AI), cloud computing, and other large-scale computing environments and their associated data. Looking ahead, key players in cutting-edge technologies are making substantial investments and long-term strategic decisions about the future landscape of distributed computing and supercomputing infrastructures.
Quantum Computing (QC) systems are increasingly being explored as the next high-impact extension to the computing spectrum, particularly with integration into supercomputers and cloud environments. The successful interoperability between classical and quantum systems will depend on middleware interacting with heterogeneous hardware technologies (e.g., CPU, GPU, TPU, FPGA, QPU) and their associated software stacks and data management methods. The most realistically feasible approach towards leveraging QC in the near term involves loosely-coupled integration of the classical and quantum devices through classical computing networks. Although these solutions can offload computation to quantum systems, approaches toward high-level hybrid programming are still lacking.
Current work on integrating QC into classical computing ecosystems focuses on the algorithms' interoperability and performance without considering workflow-specific challenges like task-resource mapping, orchestration, workload balancing, and integration with existing workflow management environments. In this context, we find complex open challenges in combining multiple programming models in a single application with workflow steps that combine quantum and classical processing in a domain-agnostic manner.
This Birds-of-a-Feather session aims to develop hybrid quantum-classical workflows that reconcile quantum and classical systems and software stacks. To this end, we will gather experts in workflow management, task-based runtimes, QC technologies, and large-scale classical infrastructures to discuss the opportunities and directions in this emerging space. By bringing together academia, government, and industry representatives of the QC and computational workflows communities, we expect to enable new collaborations and identify immediate next steps to address pressing challenges.
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