HARP-ME: Closure-Driven Exact Induced Motif Enumeration on GPUs
2026-07-15T08:52:19Z•20ea5307904b5fa52f8c3c7d5598ba9ac047af2b7ca1c8fad7a14216e18a1a7d
5G edge computing','RIC','slice scheduling','profiling','saga','DGDEnsembleLauncherFlashDiffGPU accelerationHARP-MEO-DAGO-RANautonomous sciencedecentralized gradient descentdecentralized optimizationdiffusion modelsensemble orchestrationexascalegovernancegraph miningmodel servingmotif enumerationregional executionreproducibilitysafetyschedulingtrustworthinessverificationworkflow orchestration
What happened
Collection of recent systems and machine-learning infrastructure papers (arXiv 15 Jul 2026) covering: HARP-ME — a GPU framework for exact induced 4-node motif enumeration that uses closure-aware compilation and induced-signature reuse to reduce candidate expansion and edge checks; FlashDiff — an adaptive regional-execution and scheduling system to speed diffusion-model serving by skipping low-impact latent-region updates and reclaiming compute; a two-year community roadmap for trustworthy autonomous science that elevates verification, reproducibility, safety/security, and governance; analyzes/
Why it matters
A reviewed impact interpretation has not been published for this record.
Evidence and limitations
- Source ID
- arxiv_cs_dc
- Record identifier
- 20ea5307904b5fa52f8c3c7d5598ba9ac047af2b7ca1c8fad7a14216e18a1a7d
- Enrichment time
- 2026-07-15T08:52:19Z
- AI-assisted enrichment
- Yes
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