{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:B2FU44HFDPEAVWZWZRXQYFT27G","merge_version":"pith-open-graph-merge-v1","event_count":2,"valid_event_count":2,"invalid_event_count":0,"equivocation_count":0,"current":{"canonical_record":{"metadata":{"abstract_canon_sha256":"ac9c1d8aff50c2e49078541315854e1936e237e97d8339d7064d457172f7bfbd","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2024-10-16T16:13:19Z","title_canon_sha256":"be19a12a2e4679500a0ca9cf5a34de5853b32597afef4bd68ccb7b9f8bf5f1bb"},"schema_version":"1.0","source":{"id":"2410.12707","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2410.12707","created_at":"2026-07-05T09:21:32Z"},{"alias_kind":"arxiv_version","alias_value":"2410.12707v1","created_at":"2026-07-05T09:21:32Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2410.12707","created_at":"2026-07-05T09:21:32Z"},{"alias_kind":"pith_short_12","alias_value":"B2FU44HFDPEA","created_at":"2026-07-05T09:21:32Z"},{"alias_kind":"pith_short_16","alias_value":"B2FU44HFDPEAVWZW","created_at":"2026-07-05T09:21:32Z"},{"alias_kind":"pith_short_8","alias_value":"B2FU44HF","created_at":"2026-07-05T09:21:32Z"}],"graph_snapshots":[{"event_id":"sha256:2951f01d1b32dc44c3b7358ec9c8439f286b7c68228fa406be22359c51e24be6","target":"graph","created_at":"2026-07-05T09:21:32Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"graph_snapshot":{"author_claims":{"count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57","strong_count":0},"builder_version":"pith-number-builder-2026-05-17-v1","claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"formal_canon":{"evidence_count":0,"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"integrity":{"available":true,"clean":true,"detectors_run":[],"endpoint":"/pith/2410.12707/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"To alleviate hardware scarcity in training large deep neural networks (DNNs), particularly large language models (LLMs), we present FusionLLM, a decentralized training system designed and implemented for training DNNs using geo-distributed GPUs across different computing clusters or individual devices. Decentralized training faces significant challenges regarding system design and efficiency, including: 1) the need for remote automatic differentiation (RAD), 2) support for flexible model definitions and heterogeneous software, 3) heterogeneous hardware leading to low resource utilization or th","authors_text":"Amelie Chi Zhou, Bingsheng He, Bo Li, Kaiyong Zhao, Qiang Wang, Rongfei Zeng, Shaohuai Shi, Xiaowen Chu, Xinglin Pan, Xin He, Xueze Kang, Yiming Yin, Yuxin Wang, Zhenheng Tang","cross_cats":["cs.AI","cs.LG"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2024-10-16T16:13:19Z","title":"FusionLLM: A Decentralized LLM Training System on Geo-distributed GPUs with Adaptive Compression"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2410.12707","kind":"arxiv","version":1},"verdict":{"created_at":null,"id":null,"model_set":{},"one_line_summary":"","pipeline_version":null,"pith_extraction_headline":"","strongest_claim":"","weakest_assumption":""}},"verdict_id":null}}],"author_attestations":[],"timestamp_anchors":[],"storage_attestations":[],"citation_signatures":[],"replication_records":[],"corrections":[],"mirror_hints":[],"record_created":{"event_id":"sha256:face849835d5b30a6912e2b906b42dbc621e1691fae8762fc8d08d742bd5cd41","target":"record","created_at":"2026-07-05T09:21:32Z","signer":{"key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signer_id":"pith.science","signer_type":"pith_registry"},"payload":{"attestation_state":"computed","canonical_record":{"metadata":{"abstract_canon_sha256":"ac9c1d8aff50c2e49078541315854e1936e237e97d8339d7064d457172f7bfbd","cross_cats_sorted":["cs.AI","cs.LG"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2024-10-16T16:13:19Z","title_canon_sha256":"be19a12a2e4679500a0ca9cf5a34de5853b32597afef4bd68ccb7b9f8bf5f1bb"},"schema_version":"1.0","source":{"id":"2410.12707","kind":"arxiv","version":1}},"canonical_sha256":"0e8b4e70e51bc80adb36cc6f0c167af996761d748bf2b628d1276cb9feb0c27c","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"0e8b4e70e51bc80adb36cc6f0c167af996761d748bf2b628d1276cb9feb0c27c","first_computed_at":"2026-07-05T09:21:32.690021Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:21:32.690021Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"7SdcjvVNUH+3qufvTvqC8mTsJwwTVc0uVN47J0gGZ8EIld+JTCqlMaJvqd1IhncWSSxF3kMQshjV79jhzkiQBA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:21:32.690500Z","signed_message":"canonical_sha256_bytes"},"source_id":"2410.12707","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:face849835d5b30a6912e2b906b42dbc621e1691fae8762fc8d08d742bd5cd41","sha256:2951f01d1b32dc44c3b7358ec9c8439f286b7c68228fa406be22359c51e24be6"],"state_sha256":"f396d218ba914405ce2c4176db339892370a3f8e49c0f99d6e7c0c606be6b9d9"}