A survey of on-device learning in TinyML organized by distribution change regimes, highlighting influences on applications, hardware, and solutions plus a gap between benchmarks and deployments.
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No single post-Moore technology replaces current HPC for plasma simulations, but FPGA-class accelerators offer near-term kernel offload, non-von Neumann architectures medium-term operator acceleration, and quantum computing long-term potential for warm dense matter microphysics.
Current SYCL implementations show inconsistencies in memory management (USM vs buffers) and kernel models (NDRange vs hierarchical) that reduce cross-platform reliability.
citing papers explorer
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What changes after deployment? A survey on On-device Learning in TinyML
A survey of on-device learning in TinyML organized by distribution change regimes, highlighting influences on applications, hardware, and solutions plus a gap between benchmarks and deployments.
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Post-Moore Technologies for Plasma Simulation: A Community Roadmap
No single post-Moore technology replaces current HPC for plasma simulations, but FPGA-class accelerators offer near-term kernel offload, non-von Neumann architectures medium-term operator acceleration, and quantum computing long-term potential for warm dense matter microphysics.
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Evaluating SYCL as a Unified Programming Model for Heterogeneous Systems
Current SYCL implementations show inconsistencies in memory management (USM vs buffers) and kernel models (NDRange vs hierarchical) that reduce cross-platform reliability.