{"record_type":"pith_number_record","schema_url":"https://pith.science/schemas/pith-number/v1.json","pith_number":"pith:2017:JWJMNK74UDQ7QFLD6FGXBDT6TI","short_pith_number":"pith:JWJMNK74","schema_version":"1.0","canonical_sha256":"4d92c6abfca0e1f81563f14d708e7e9a08923baf3c7a4a826d8a2f523c891bc9","source":{"kind":"arxiv","id":"1706.00504","version":1},"attestation_state":"computed","paper":{"title":"Dynamic Stripes: Exploiting the Dynamic Precision Requirements of Activation Values in Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NE","authors_text":"Alberto Delmas, Andreas Moshovos, Patrick Judd, Sayeh Sharify","submitted_at":"2017-06-01T21:57:32Z","abstract_excerpt":"Stripes is a Deep Neural Network (DNN) accelerator that uses bit-serial computation to offer performance that is proportional to the fixed-point precision of the activation values. The fixed-point precisions are determined a priori using profiling and are selected at a per layer granularity. This paper presents Dynamic Stripes, an extension to Stripes that detects precision variance at runtime and at a finer granularity. This extra level of precision reduction increases performance by 41% over Stripes."},"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":"1706.00504","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.NE","submitted_at":"2017-06-01T21:57:32Z","cross_cats_sorted":["cs.LG"],"title_canon_sha256":"5aa01e76982961114db77d56946f3adac542d5800dd9868b4aec412944f780ec","abstract_canon_sha256":"20f17f74d7161335880edf21a74399b6412d525fa82d7dc68ce20481c5fc2e55"},"schema_version":"1.0"},"receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-05-18T00:43:12.825668Z","signature_b64":"cKsZtXdtGvCpK+GL9mni6fBDUAHxiXi1fpdvO1j19woEQ+6mAowrDjeA7wJHoU/O2SD9uM793NtnkGKZm1QbCQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"4d92c6abfca0e1f81563f14d708e7e9a08923baf3c7a4a826d8a2f523c891bc9","last_reissued_at":"2026-05-18T00:43:12.825110Z","signature_status":"signed_v1","first_computed_at":"2026-05-18T00:43:12.825110Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"graph_snapshot":{"paper":{"title":"Dynamic Stripes: Exploiting the Dynamic Precision Requirements of Activation Values in Neural Networks","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.LG"],"primary_cat":"cs.NE","authors_text":"Alberto Delmas, Andreas Moshovos, Patrick Judd, Sayeh Sharify","submitted_at":"2017-06-01T21:57:32Z","abstract_excerpt":"Stripes is a Deep Neural Network (DNN) accelerator that uses bit-serial computation to offer performance that is proportional to the fixed-point precision of the activation values. The fixed-point precisions are determined a priori using profiling and are selected at a per layer granularity. This paper presents Dynamic Stripes, an extension to Stripes that detects precision variance at runtime and at a finer granularity. This extra level of precision reduction increases performance by 41% over Stripes."},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1706.00504","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":"1706.00504","created_at":"2026-05-18T00:43:12.825192+00:00"},{"alias_kind":"arxiv_version","alias_value":"1706.00504v1","created_at":"2026-05-18T00:43:12.825192+00:00"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1706.00504","created_at":"2026-05-18T00:43:12.825192+00:00"},{"alias_kind":"pith_short_12","alias_value":"JWJMNK74UDQ7","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_16","alias_value":"JWJMNK74UDQ7QFLD","created_at":"2026-05-18T12:31:24.725408+00:00"},{"alias_kind":"pith_short_8","alias_value":"JWJMNK74","created_at":"2026-05-18T12:31:24.725408+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/JWJMNK74UDQ7QFLD6FGXBDT6TI","json":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI.json","graph_json":"https://pith.science/api/pith-number/JWJMNK74UDQ7QFLD6FGXBDT6TI/graph.json","events_json":"https://pith.science/api/pith-number/JWJMNK74UDQ7QFLD6FGXBDT6TI/events.json","paper":"https://pith.science/paper/JWJMNK74"},"agent_actions":{"view_html":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI","download_json":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI.json","view_paper":"https://pith.science/paper/JWJMNK74","resolve_alias":"https://pith.science/api/pith-number/resolve?arxiv=1706.00504&json=true","fetch_graph":"https://pith.science/api/pith-number/JWJMNK74UDQ7QFLD6FGXBDT6TI/graph.json","fetch_events":"https://pith.science/api/pith-number/JWJMNK74UDQ7QFLD6FGXBDT6TI/events.json","actions":{"anchor_timestamp":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI/action/timestamp_anchor","attest_storage":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI/action/storage_attestation","attest_author":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI/action/author_attestation","sign_citation":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI/action/citation_signature","submit_replication":"https://pith.science/pith/JWJMNK74UDQ7QFLD6FGXBDT6TI/action/replication_record"}},"created_at":"2026-05-18T00:43:12.825192+00:00","updated_at":"2026-05-18T00:43:12.825192+00:00"}