AI Engines enable larger low-latency neural networks for extreme-edge scientific computing on FPGAs than programmable logic, via a new latency-adjusted resource equivalence metric and tailored optimizations.
Evaluation of xilinx versal architecture for next-gen edge computing in space
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
M100 is a tensor-based dataflow architecture that eliminates heavy caching through compiler-managed data streams, claiming higher utilization and better performance than GPGPUs for AD and LLM inference tasks.
citing papers explorer
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Design Rules for Extreme-Edge Scientific Computing on AI Engines
AI Engines enable larger low-latency neural networks for extreme-edge scientific computing on FPGAs than programmable logic, via a new latency-adjusted resource equivalence metric and tailored optimizations.
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M100: An Orchestrated Dataflow Architecture Powering General AI Computing
M100 is a tensor-based dataflow architecture that eliminates heavy caching through compiler-managed data streams, claiming higher utilization and better performance than GPGPUs for AD and LLM inference tasks.