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Compass

1 mentions in 7 days · 2 in 30 days · 2 total · first seen Sep 3, 2026 · last 1d ago

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COMPASS: Ordered Clustered Routing at 100K Scale

COMPASS combines search with learning-accelerated parallel sub-solvers for the Ordered Clustered TSP, scaling to 100K synthetic and 28.5K real e-commerce nodes.

COMPASS is an algorithm for the Ordered Clustered Traveling Salesman Problem (OCTSP) that orchestrates parallel sub-solvers, combining search with learning-accelerated routing. It has no quality ceiling, exploits clustered structure to reach exact solutions exponential in cluster size rather than instance size, and accepts general distance matrices beyond coordinate inputs. The method scales to 100K synthetic nodes and 28.5K real e-commerce nodes, the largest reported routing solution over asymmetric distances, 9x beyond established ATSP benchmarks.

arXiv cs.AI / cs.LG / cs.CLSep 17, 13:17 UTC · 1d agoAI research

Hoss: Fast Oblivious Semantic Search with Heterogeneous GPU-CPU-TEE Architecture

Hoss uses heterogeneous GPU-CPU TEEs for oblivious semantic search, achieving up to 67x speedup over the Compass ORAM-based system.

Hoss is a first-of-its-kind oblivious semantic search system built on a heterogeneous CPU-GPU TEE architecture, hosting hot-path HNSW graph traversal in large GPU TEE private memory and offloading lower graph layers to CPU TEEs. It invokes oblivious primitives only for lower-layer accesses and adds host-access ORAM and data-dependent optimizations. Benchmarked against prior state-of-the-art Compass, the prototype achieves up to 67x speedup while maintaining high recall, with larger gains at scale.

arXiv cs.CRSep 3, 22:21 UTC · 14d agoResearch

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