{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:OLJKZO3YDMUMGD5ODKIFE7DULT","short_pith_number":"pith:OLJKZO3Y","canonical_record":{"source":{"id":"2207.11434","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2022-07-23T06:45:14Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5ca53dd093d4feac696b4d72f56f43b8814df768e11dbc81142a9477c682f991","abstract_canon_sha256":"9ad3aac0a0c3e48374bcd1b880d6e0e0156ca51c06655cbb6a2359ece656f59b"},"schema_version":"1.0"},"canonical_sha256":"72d2acbb781b28c30fae1a90527c745cd1db9069bcbf2de5ba1eb6973056dfa7","source":{"kind":"arxiv","id":"2207.11434","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.11434","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"arxiv_version","alias_value":"2207.11434v2","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.11434","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"pith_short_12","alias_value":"OLJKZO3YDMUM","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"pith_short_16","alias_value":"OLJKZO3YDMUMGD5O","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"pith_short_8","alias_value":"OLJKZO3Y","created_at":"2026-07-05T04:44:21Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:OLJKZO3YDMUMGD5ODKIFE7DULT","target":"record","payload":{"canonical_record":{"source":{"id":"2207.11434","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2022-07-23T06:45:14Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5ca53dd093d4feac696b4d72f56f43b8814df768e11dbc81142a9477c682f991","abstract_canon_sha256":"9ad3aac0a0c3e48374bcd1b880d6e0e0156ca51c06655cbb6a2359ece656f59b"},"schema_version":"1.0"},"canonical_sha256":"72d2acbb781b28c30fae1a90527c745cd1db9069bcbf2de5ba1eb6973056dfa7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T04:44:21.908725Z","signature_b64":"yyJtHmlaqhA8JDxYrY27JT61xUmunSWwubTbW4pdjURA3oheh9L9QsA6dovBwrN7WAtRPVyVuQkieV2CKjNSAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"72d2acbb781b28c30fae1a90527c745cd1db9069bcbf2de5ba1eb6973056dfa7","last_reissued_at":"2026-07-05T04:44:21.908236Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T04:44:21.908236Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2207.11434","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":"2026-07-05T04:44:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eNO4EUnW9seaY3DaT4EVINhy2C8KIllOSzhY0KMKSmqqpD58oLklO9BlHy9dEGr3ef2uOSiGLeGo5MZaNlXwDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:23:30.578038Z"},"content_sha256":"8c82108b212e20d86474ca7dfe82f8e0a8dea77da389e68833d08d3babd742bd","schema_version":"1.0","event_id":"sha256:8c82108b212e20d86474ca7dfe82f8e0a8dea77da389e68833d08d3babd742bd"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:OLJKZO3YDMUMGD5ODKIFE7DULT","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instances","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.DC","authors_text":"Baolin Li, Devesh Tiwari, Karen Gettings, Rohan Basu Roy, Tirthak Patel, Vijay Gadepally","submitted_at":"2022-07-23T06:45:14Z","abstract_excerpt":"Deep learning model inference is a key service in many businesses and scientific discovery processes. This paper introduces RIBBON, a novel deep learning inference serving system that meets two competing objectives: quality-of-service (QoS) target and cost-effectiveness. The key idea behind RIBBON is to intelligently employ a diverse set of cloud computing instances (heterogeneous instances) to meet the QoS target and maximize cost savings. RIBBON devises a Bayesian Optimization-driven strategy that helps users build the optimal set of heterogeneous instances for their model inference service "},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.11434","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/2207.11434/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":"2026-07-05T04:44:21Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"IFPyiZiD9qC9Cz5wTKeM2yu2t3lEEZDpy5iuIpqVBfCgJw2i53P891+B+H+G1dqiwEWkP8dPjGIbl3rQtn6UAw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-06T19:23:30.578435Z"},"content_sha256":"947c18f13d6a662eb390cf17b591816ebeb17a3d6845f87e7214be49b8523140","schema_version":"1.0","event_id":"sha256:947c18f13d6a662eb390cf17b591816ebeb17a3d6845f87e7214be49b8523140"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/OLJKZO3YDMUMGD5ODKIFE7DULT/bundle.json","state_url":"https://pith.science/pith/OLJKZO3YDMUMGD5ODKIFE7DULT/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/OLJKZO3YDMUMGD5ODKIFE7DULT/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":"2026-07-06T19:23:30Z","links":{"resolver":"https://pith.science/pith/OLJKZO3YDMUMGD5ODKIFE7DULT","bundle":"https://pith.science/pith/OLJKZO3YDMUMGD5ODKIFE7DULT/bundle.json","state":"https://pith.science/pith/OLJKZO3YDMUMGD5ODKIFE7DULT/state.json","well_known_bundle":"https://pith.science/.well-known/pith/OLJKZO3YDMUMGD5ODKIFE7DULT/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:OLJKZO3YDMUMGD5ODKIFE7DULT","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":"9ad3aac0a0c3e48374bcd1b880d6e0e0156ca51c06655cbb6a2359ece656f59b","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2022-07-23T06:45:14Z","title_canon_sha256":"5ca53dd093d4feac696b4d72f56f43b8814df768e11dbc81142a9477c682f991"},"schema_version":"1.0","source":{"id":"2207.11434","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2207.11434","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"arxiv_version","alias_value":"2207.11434v2","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2207.11434","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"pith_short_12","alias_value":"OLJKZO3YDMUM","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"pith_short_16","alias_value":"OLJKZO3YDMUMGD5O","created_at":"2026-07-05T04:44:21Z"},{"alias_kind":"pith_short_8","alias_value":"OLJKZO3Y","created_at":"2026-07-05T04:44:21Z"}],"graph_snapshots":[{"event_id":"sha256:947c18f13d6a662eb390cf17b591816ebeb17a3d6845f87e7214be49b8523140","target":"graph","created_at":"2026-07-05T04:44:21Z","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/2207.11434/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep learning model inference is a key service in many businesses and scientific discovery processes. This paper introduces RIBBON, a novel deep learning inference serving system that meets two competing objectives: quality-of-service (QoS) target and cost-effectiveness. The key idea behind RIBBON is to intelligently employ a diverse set of cloud computing instances (heterogeneous instances) to meet the QoS target and maximize cost savings. RIBBON devises a Bayesian Optimization-driven strategy that helps users build the optimal set of heterogeneous instances for their model inference service ","authors_text":"Baolin Li, Devesh Tiwari, Karen Gettings, Rohan Basu Roy, Tirthak Patel, Vijay Gadepally","cross_cats":["cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2022-07-23T06:45:14Z","title":"RIBBON: Cost-Effective and QoS-Aware Deep Learning Model Inference using a Diverse Pool of Cloud Computing Instances"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2207.11434","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":"sha256:8c82108b212e20d86474ca7dfe82f8e0a8dea77da389e68833d08d3babd742bd","target":"record","created_at":"2026-07-05T04:44:21Z","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":"9ad3aac0a0c3e48374bcd1b880d6e0e0156ca51c06655cbb6a2359ece656f59b","cross_cats_sorted":["cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2022-07-23T06:45:14Z","title_canon_sha256":"5ca53dd093d4feac696b4d72f56f43b8814df768e11dbc81142a9477c682f991"},"schema_version":"1.0","source":{"id":"2207.11434","kind":"arxiv","version":2}},"canonical_sha256":"72d2acbb781b28c30fae1a90527c745cd1db9069bcbf2de5ba1eb6973056dfa7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"72d2acbb781b28c30fae1a90527c745cd1db9069bcbf2de5ba1eb6973056dfa7","first_computed_at":"2026-07-05T04:44:21.908236Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T04:44:21.908236Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"yyJtHmlaqhA8JDxYrY27JT61xUmunSWwubTbW4pdjURA3oheh9L9QsA6dovBwrN7WAtRPVyVuQkieV2CKjNSAA==","signature_status":"signed_v1","signed_at":"2026-07-05T04:44:21.908725Z","signed_message":"canonical_sha256_bytes"},"source_id":"2207.11434","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:8c82108b212e20d86474ca7dfe82f8e0a8dea77da389e68833d08d3babd742bd","sha256:947c18f13d6a662eb390cf17b591816ebeb17a3d6845f87e7214be49b8523140"],"state_sha256":"2f4286b5aa820b14308b4c3d5a0cb19c3bf8eccca1b597d3c04755025c871d41"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BYUunfIdudvMGu2GlKwaFTKBclBKSqjEMTM4/Q+BmsHIi+l4F5V6SvSwtKonYggaugM5cMOIw7A805jVztziBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-06T19:23:30.580366Z","bundle_sha256":"ac4cd3f5b5b4f3d3636b709f2f97aa8151feaa1417e4f0c72540bed99b6f85b6"}}