{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:YCGED7CCQO2GKCKIJA6GQ6AWMB","short_pith_number":"pith:YCGED7CC","schema_version":"1.0","canonical_sha256":"c08c41fc4283b4650948483c68781660606482ed5406bf656292aa448cfcb6d9","source":{"kind":"arxiv","id":"1710.06471","version":1},"attestation_state":"computed","paper":{"title":"Coded Fourier Transform","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT"],"primary_cat":"cs.DC","authors_text":"A. Salman Avestimehr, Mohammad Ali Maddah-Ali, Qian Yu","submitted_at":"2017-10-17T18:57:52Z","abstract_excerpt":"We consider the problem of computing the Fourier transform of high-dimensional vectors, distributedly over a cluster of machines consisting of a master node and multiple worker nodes, where the worker nodes can only store and process a fraction of the inputs. We show that by exploiting the algebraic structure of the Fourier transform operation and leveraging concepts from coding theory, one can efficiently deal with the straggler effects. In particular, we propose a computation strategy, named as coded FFT, which achieves the optimal recovery threshold, defined as the minimum number of workers"},"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":"1710.06471","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2017-10-17T18:57:52Z","cross_cats_sorted":["cs.IT","cs.LG","math.IT"],"title_canon_sha256":"d916c4aed3f321bce6e1876c5dd5d20843104a4c630f229319267e43ec6e7f81","abstract_canon_sha256":"454b44a2fea32f96eddbbd1f7fe6482582b5c78511806da5540b8733aa89c72c"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:32:33.593219Z","signature_b64":"R/IfpB+VPcLUSmhFqtRP7R6zW2auRdvcYM2PMIEaEfmsZ5DZfx84qSNf/PjTRWnZ6vv19Tj8jzBGrAligeebBw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"c08c41fc4283b4650948483c68781660606482ed5406bf656292aa448cfcb6d9","last_reissued_at":"2026-05-18T00:32:33.592498Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:32:33.592498Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Coded Fourier Transform","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.IT","cs.LG","math.IT"],"primary_cat":"cs.DC","authors_text":"A. Salman Avestimehr, Mohammad Ali Maddah-Ali, Qian Yu","submitted_at":"2017-10-17T18:57:52Z","abstract_excerpt":"We consider the problem of computing the Fourier transform of high-dimensional vectors, distributedly over a cluster of machines consisting of a master node and multiple worker nodes, where the worker nodes can only store and process a fraction of the inputs. We show that by exploiting the algebraic structure of the Fourier transform operation and leveraging concepts from coding theory, one can efficiently deal with the straggler effects. In particular, we propose a computation strategy, named as coded FFT, which achieves the optimal recovery threshold, defined as the minimum number of workers"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1710.06471","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":""},"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":"1710.06471","created_at":"2026-05-18T00:32:33.592610+00:00"},{"alias_kind":"arxiv_version","alias_value":"1710.06471v1","created_at":"2026-05-18T00:32:33.592610+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1710.06471","created_at":"2026-05-18T00:32:33.592610+00:00"},{"alias_kind":"pith_short_12","alias_value":"YCGED7CCQO2G","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_16","alias_value":"YCGED7CCQO2GKCKI","created_at":"2026-05-18T12:31:56.362134+00:00"},{"alias_kind":"pith_short_8","alias_value":"YCGED7CC","created_at":"2026-05-18T12:31:56.362134+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/YCGED7CCQO2GKCKIJA6GQ6AWMB","json":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB.json","graph_json":"https://pith.science/api/pith-number/YCGED7CCQO2GKCKIJA6GQ6AWMB/graph.json","events_json":"https://pith.science/api/pith-number/YCGED7CCQO2GKCKIJA6GQ6AWMB/events.json","paper":"https://pith.science/paper/YCGED7CC"},"agent_actions":{"view_html":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB","download_json":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB.json","view_paper":"https://pith.science/paper/YCGED7CC","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1710.06471&json=true","fetch_graph":"https://pith.science/api/pith-number/YCGED7CCQO2GKCKIJA6GQ6AWMB/graph.json","fetch_events":"https://pith.science/api/pith-number/YCGED7CCQO2GKCKIJA6GQ6AWMB/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB/action/timestamp_anchor","attest_storage":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB/action/storage_attestation","attest_author":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB/action/author_attestation","sign_citation":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB/action/citation_signature","submit_replication":"https://pith.science/pith/YCGED7CCQO2GKCKIJA6GQ6AWMB/action/replication_record"}},"created_at":"2026-05-18T00:32:33.592610+00:00","updated_at":"2026-05-18T00:32:33.592610+00:00"}