{"paper":{"title":"HyperParallel-Mpipe: A Composable Algebra System for Optimizing MLLM Training over Supernode Clusters","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Chong Bao, Chong Li, Etienne Filhol, Nelson Lossing, Pierre Leca, Teng Su, Thibaut Tachon, Yujie Yuan, Zhengdao Yu","submitted_at":"2026-07-03T11:41:14Z","abstract_excerpt":"Modern AI applications have expanded beyond text-only interaction into a wide range of multimodal scenarios, making multimodal large language models (MLLMs) crucial for both research and industry. However, compared with traditional decoder-only LLM training, large-scale MLLM training often shows much lower MFU. We analyze the key pain points in MLLM training and introduce Mpipe, which uses a schedule algebra to derive concrete runtime behavior from a compact schedule specification. From this algebra, Mpipe derives transpose, a multimodal-aware heterogeneous parallel schedule that remaps modali"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2607.03229","kind":"arxiv","version":1},"verdict":{"id":null,"model_set":{},"created_at":null,"strongest_claim":"","one_line_summary":"","pipeline_version":null,"weakest_assumption":"","pith_extraction_headline":""},"integrity":{"clean":true,"summary":{"advisory":0,"critical":0,"by_detector":{},"informational":0},"endpoint":"/pith/2607.03229/integrity.json","findings":[],"available":true,"detectors_run":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938"},"references":{"count":0,"sample":[],"resolved_work":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","internal_anchors":0},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"author_claims":{"count":0,"strong_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"builder_version":"pith-number-builder-2026-05-17-v1"}