{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:ASXSVAGJSWJAU6ZFMKTMR5AIJA","short_pith_number":"pith:ASXSVAGJ","canonical_record":{"source":{"id":"2502.05043","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2025-02-07T16:09:17Z","cross_cats_sorted":[],"title_canon_sha256":"59e61b319e6c648a8c78a4774067363cf9a159ee39227edddf5e6ea8a5b41a45","abstract_canon_sha256":"47dab40c7ac0e207f357de65fcd48781911359378214eb065ee9384bfcce8124"},"schema_version":"1.0"},"canonical_sha256":"04af2a80c995920a7b2562a6c8f408480e7d6702885ef51805a1301ab08f098e","source":{"kind":"arxiv","id":"2502.05043","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05043","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05043v2","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05043","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"pith_short_12","alias_value":"ASXSVAGJSWJA","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"pith_short_16","alias_value":"ASXSVAGJSWJAU6ZF","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"pith_short_8","alias_value":"ASXSVAGJ","created_at":"2026-07-05T10:31:53Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:ASXSVAGJSWJAU6ZFMKTMR5AIJA","target":"record","payload":{"canonical_record":{"source":{"id":"2502.05043","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2025-02-07T16:09:17Z","cross_cats_sorted":[],"title_canon_sha256":"59e61b319e6c648a8c78a4774067363cf9a159ee39227edddf5e6ea8a5b41a45","abstract_canon_sha256":"47dab40c7ac0e207f357de65fcd48781911359378214eb065ee9384bfcce8124"},"schema_version":"1.0"},"canonical_sha256":"04af2a80c995920a7b2562a6c8f408480e7d6702885ef51805a1301ab08f098e","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:31:53.893927Z","signature_b64":"1ypEVQjfRwZdIRWNWqHDfoMcvh6k3UdCoPJ2a04d7gF4U/AWJ7ngIjTawjmPCPKCYSrHDRbvPrfcHVnOl/4JDg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"04af2a80c995920a7b2562a6c8f408480e7d6702885ef51805a1301ab08f098e","last_reissued_at":"2026-07-05T10:31:53.893444Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:31:53.893444Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.05043","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:31:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"x/PRo5qkcdydSjwSToAsvzIi1xHq4TForYB+0Ja6j4Ypddff1pH+odqR0IadTEWsvvIAPtnY22Zwz5VK1LIpBw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:54:15.885695Z"},"content_sha256":"d28977da3e82314466482a7b3f615119a96907f97f401261a377224ceb12cf9c","schema_version":"1.0","event_id":"sha256:d28977da3e82314466482a7b3f615119a96907f97f401261a377224ceb12cf9c"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:ASXSVAGJSWJAU6ZFMKTMR5AIJA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"EcoServe: Designing Carbon-Aware AI Inference Systems","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Esha Choukse, G. Edward Suh, Rodrigo Fonseca, Udit Gupta, Yueying Li, Zhanqiu Hu","submitted_at":"2025-02-07T16:09:17Z","abstract_excerpt":"The rapid increase in LLM ubiquity and scale levies unprecedented demands on computing infrastructure. These demands not only incur large compute and memory resources but also significant energy, yielding large operational and embodied carbon emissions. In this work, we present three main observations based on modeling and traces from the production deployment of two Generative AI services in a major cloud service provider. First, while GPUs dominate operational carbon, host processing systems (e.g., CPUs, memory, storage) dominate embodied carbon. Second, offline, batch inference accounts for"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05043","kind":"arxiv","version":2},"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/2502.05043/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"},"verdict_id":null},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:31:53Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"OElC8aiQGfWId+GBqVd5RXuIIGxfEs4xEkRNhIpVCYwuFEhGCu47Ra4fMlwB0Cko1yDS8JNFBuvVg1qjVSmnDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-07T10:54:15.886188Z"},"content_sha256":"3d275abfc69e8ce491c3d78314dddac97f29c0ebfbf6eaf9950f7788e159f683","schema_version":"1.0","event_id":"sha256:3d275abfc69e8ce491c3d78314dddac97f29c0ebfbf6eaf9950f7788e159f683"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/ASXSVAGJSWJAU6ZFMKTMR5AIJA/bundle.json","state_url":"https://pith.science/pith/ASXSVAGJSWJAU6ZFMKTMR5AIJA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/ASXSVAGJSWJAU6ZFMKTMR5AIJA/bundle.json","status":"primary"}],"public_keys":[{"key_id":"pith-v1-2026-05","algorithm":"ed25519","format":"raw","public_key_b64":"stVStoiQhXFxp4s2pdzPNoqVNBMojDU/fJ2db5S3CbM=","public_key_hex":"b2d552b68890857171a78b36a5dccf368a953413288c353f7c9d9d6f94b709b3","fingerprint_sha256_b32_first128bits":"RVFV5Z2OI2J3ZUO7ERDEBCYNKS","fingerprint_sha256_hex":"8d4b5ee74e4693bcd1df2446408b0d54","rotates_at":null,"url":"https://pith.science/pith-signing-key.json","notes":"Pith uses this Ed25519 key to sign canonical record SHA-256 digests. Verify with: ed25519_verify(public_key, message=canonical_sha256_bytes, signature=base64decode(signature_b64))."}],"merge_version":"pith-open-graph-merge-v1","built_at":"2026-08-07T10:54:15Z","links":{"resolver":"https://pith.science/pith/ASXSVAGJSWJAU6ZFMKTMR5AIJA","bundle":"https://pith.science/pith/ASXSVAGJSWJAU6ZFMKTMR5AIJA/bundle.json","state":"https://pith.science/pith/ASXSVAGJSWJAU6ZFMKTMR5AIJA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/ASXSVAGJSWJAU6ZFMKTMR5AIJA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:ASXSVAGJSWJAU6ZFMKTMR5AIJA","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":"47dab40c7ac0e207f357de65fcd48781911359378214eb065ee9384bfcce8124","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2025-02-07T16:09:17Z","title_canon_sha256":"59e61b319e6c648a8c78a4774067363cf9a159ee39227edddf5e6ea8a5b41a45"},"schema_version":"1.0","source":{"id":"2502.05043","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.05043","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"arxiv_version","alias_value":"2502.05043v2","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.05043","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"pith_short_12","alias_value":"ASXSVAGJSWJA","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"pith_short_16","alias_value":"ASXSVAGJSWJAU6ZF","created_at":"2026-07-05T10:31:53Z"},{"alias_kind":"pith_short_8","alias_value":"ASXSVAGJ","created_at":"2026-07-05T10:31:53Z"}],"graph_snapshots":[{"event_id":"sha256:3d275abfc69e8ce491c3d78314dddac97f29c0ebfbf6eaf9950f7788e159f683","target":"graph","created_at":"2026-07-05T10:31:53Z","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/2502.05043/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The rapid increase in LLM ubiquity and scale levies unprecedented demands on computing infrastructure. These demands not only incur large compute and memory resources but also significant energy, yielding large operational and embodied carbon emissions. In this work, we present three main observations based on modeling and traces from the production deployment of two Generative AI services in a major cloud service provider. First, while GPUs dominate operational carbon, host processing systems (e.g., CPUs, memory, storage) dominate embodied carbon. Second, offline, batch inference accounts for","authors_text":"Esha Choukse, G. Edward Suh, Rodrigo Fonseca, Udit Gupta, Yueying Li, Zhanqiu Hu","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2025-02-07T16:09:17Z","title":"EcoServe: Designing Carbon-Aware AI Inference Systems"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.05043","kind":"arxiv","version":2},"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:d28977da3e82314466482a7b3f615119a96907f97f401261a377224ceb12cf9c","target":"record","created_at":"2026-07-05T10:31:53Z","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":"47dab40c7ac0e207f357de65fcd48781911359378214eb065ee9384bfcce8124","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2025-02-07T16:09:17Z","title_canon_sha256":"59e61b319e6c648a8c78a4774067363cf9a159ee39227edddf5e6ea8a5b41a45"},"schema_version":"1.0","source":{"id":"2502.05043","kind":"arxiv","version":2}},"canonical_sha256":"04af2a80c995920a7b2562a6c8f408480e7d6702885ef51805a1301ab08f098e","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"04af2a80c995920a7b2562a6c8f408480e7d6702885ef51805a1301ab08f098e","first_computed_at":"2026-07-05T10:31:53.893444Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:31:53.893444Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"1ypEVQjfRwZdIRWNWqHDfoMcvh6k3UdCoPJ2a04d7gF4U/AWJ7ngIjTawjmPCPKCYSrHDRbvPrfcHVnOl/4JDg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:31:53.893927Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.05043","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d28977da3e82314466482a7b3f615119a96907f97f401261a377224ceb12cf9c","sha256:3d275abfc69e8ce491c3d78314dddac97f29c0ebfbf6eaf9950f7788e159f683"],"state_sha256":"e2a86ee940d6cbdb975347520cd96f0e88c6ddde4922206a2c70c4634bac4e6d"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"MM51HX+r5kVjoRbuMRzo8fChvCX/qhFMMe6CSTJjXeSjO/oh8LuCR8eqJMZcCJExQgyFxuhGZH8BGrQvmFJ0Bw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-07T10:54:15.889924Z","bundle_sha256":"83443c1c05f052abe569b816d0f2545fd3a7ba2a8e6c5ed0f28d1142eccabbc6"}}