Post-Moore Technologies for Plasma Simulation: A Community Roadmap
Luca Pennati, Erik M. {\AA}sgrim, Jeremy J. Williams, Stefan Costea, David Tskhakaya, Leon Kos, Ales Podolnik, Yi Ju, Tapish Narwal, Julian Lenz, Michael Bussmann, Urs Ganse, Minna Palmroth, Kallia Chronaki, Vassilis Papaefstathiou, Etienne Renault, Felix Jung, Martin Schulz

TL;DR
This paper reviews post-Moore computing technologies like accelerators, non-von Neumann architectures, and quantum computing for plasma simulation, highlighting their potential roles and limitations.
Contribution
It provides a community perspective on integrating emerging post-Moore technologies into plasma simulation workflows through a co-design approach.
Findings
No single technology can replace current HPC platforms.
FPGA-class accelerators enable near-term kernel offload.
Quantum computing could be disruptive for specific plasma physics applications.
Abstract
Plasma simulations are among the most computationally demanding scientific workloads, combining high-dimensional kinetic evolution, particle-mesh coupling, field solves, and data-intensive communication. As general-purpose processor scaling slows, post-Moore technologies are being explored to address bottlenecks in data movement, memory access, and power consumption. This paper provides a community perspective on the role of these technologies in plasma simulation, assessing three major classes: reconfigurable and data-path accelerators, non-von Neumann architectures, and quantum computing. Each is evaluated, in a co-design approach, against representative plasma workloads spanning particle-in-cell, continuum Vlasov, gyrokinetic, fluid/MHD, hybrid, and warm dense matter methods. We find that no single technology can replace existing HPC platforms. Instead, three tiers of opportunity…
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