{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2021:UVZIJ4RVJ37SP6XUHC2C4RW4K6","short_pith_number":"pith:UVZIJ4RV","schema_version":"1.0","canonical_sha256":"a57284f2354eff27faf438b42e46dc57af85e16ec0b78f7292a7cddcec008b32","source":{"kind":"arxiv","id":"2108.10701","version":1},"attestation_state":"computed","paper":{"title":"Sonic: A Sampling-based Online Controller for Streaming Applications","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","cs.PF","cs.SY","eess.SY"],"primary_cat":"cs.DC","authors_text":"Keshav Pingali, Yan Pei","submitted_at":"2021-08-15T18:51:02Z","abstract_excerpt":"Many applications in important problem domains such as machine learning and computer vision are streaming applications that take a sequence of inputs over time. It is challenging to find knob settings that optimize the run-time performance of such applications because the optimal knob settings are usually functions of inputs, computing platforms, time as well as user's requirements, which can be very diverse.\n  Most prior works address this problem by offline profiling followed by training models for control. However, profiling-based approaches incur large overhead before execution; it is also"},"verification_status":{"content_addressed":true,"pith_receipt":true,"author_attested":false,"weak_author_claims":0,"strong_author_claims":0,"externally_anchored":false,"storage_verified":false,"citation_signatures":0,"replication_records":0,"graph_snapshot":true,"references_resolved":false,"formal_links_present":false},"canonical_record":{"source":{"id":"2108.10701","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.DC","submitted_at":"2021-08-15T18:51:02Z","cross_cats_sorted":["cs.LG","cs.PF","cs.SY","eess.SY"],"title_canon_sha256":"e1f26fe3896075101b00fff6b900ee7c47e36c8c62338e9cbf72c07eb4f1bf0d","abstract_canon_sha256":"f23234dbc2e0d27b8578408471a99bc04fa6881690b0120ce575d134a3262e1a"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T03:08:39.262358Z","signature_b64":"cMXzk22R+OHp0mX43Wh2JEXoqtUefaXC8GEUtRVRRkITUHpCcmIlPYqwJmJVkz+NnoJDM1QtnZhsSIPj/Tk7Dg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a57284f2354eff27faf438b42e46dc57af85e16ec0b78f7292a7cddcec008b32","last_reissued_at":"2026-07-05T03:08:39.261980Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T03:08:39.261980Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Sonic: A Sampling-based Online Controller for Streaming Applications","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.LG","cs.PF","cs.SY","eess.SY"],"primary_cat":"cs.DC","authors_text":"Keshav Pingali, Yan Pei","submitted_at":"2021-08-15T18:51:02Z","abstract_excerpt":"Many applications in important problem domains such as machine learning and computer vision are streaming applications that take a sequence of inputs over time. It is challenging to find knob settings that optimize the run-time performance of such applications because the optimal knob settings are usually functions of inputs, computing platforms, time as well as user's requirements, which can be very diverse.\n  Most prior works address this problem by offline profiling followed by training models for control. However, profiling-based approaches incur large overhead before execution; it is also"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2108.10701","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/2108.10701/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"},"aliases":[{"alias_kind":"arxiv","alias_value":"2108.10701","created_at":"2026-07-05T03:08:39.262035+00:00"},{"alias_kind":"arxiv_version","alias_value":"2108.10701v1","created_at":"2026-07-05T03:08:39.262035+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2108.10701","created_at":"2026-07-05T03:08:39.262035+00:00"},{"alias_kind":"pith_short_12","alias_value":"UVZIJ4RVJ37S","created_at":"2026-07-05T03:08:39.262035+00:00"},{"alias_kind":"pith_short_16","alias_value":"UVZIJ4RVJ37SP6XU","created_at":"2026-07-05T03:08:39.262035+00:00"},{"alias_kind":"pith_short_8","alias_value":"UVZIJ4RV","created_at":"2026-07-05T03:08:39.262035+00:00"}],"events":[],"event_summary":{},"paper_claims":[],"inbound_citations":{"count":0,"internal_anchor_count":0,"sample":[]},"formal_canon":{"evidence_count":0,"sample":[],"anchors":[]},"links":{"html":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6","json":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6.json","graph_json":"https://pith.science/api/pith-number/UVZIJ4RVJ37SP6XUHC2C4RW4K6/graph.json","events_json":"https://pith.science/api/pith-number/UVZIJ4RVJ37SP6XUHC2C4RW4K6/events.json","paper":"https://pith.science/paper/UVZIJ4RV"},"agent_actions":{"view_html":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6","download_json":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6.json","view_paper":"https://pith.science/paper/UVZIJ4RV","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=2108.10701&json=true","fetch_graph":"https://pith.science/api/pith-number/UVZIJ4RVJ37SP6XUHC2C4RW4K6/graph.json","fetch_events":"https://pith.science/api/pith-number/UVZIJ4RVJ37SP6XUHC2C4RW4K6/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6/action/timestamp_anchor","attest_storage":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6/action/storage_attestation","attest_author":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6/action/author_attestation","sign_citation":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6/action/citation_signature","submit_replication":"https://pith.science/pith/UVZIJ4RVJ37SP6XUHC2C4RW4K6/action/replication_record"}},"created_at":"2026-07-05T03:08:39.262035+00:00","updated_at":"2026-07-05T03:08:39.262035+00:00"}