{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2022:U72OQR4EUGIKY52RSWYNAYG2Z6","short_pith_number":"pith:U72OQR4E","canonical_record":{"source":{"id":"2210.15255","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2022-10-27T08:18:25Z","cross_cats_sorted":[],"title_canon_sha256":"b2ceed727abb8302bcbb319e8cc773584744df9925722aa765a7587cb7ace39a","abstract_canon_sha256":"081f415545b0e7018b6746929d10e282778d3dc70bba09b1e69392121dd2b2da"},"schema_version":"1.0"},"canonical_sha256":"a7f4e84784a190ac775195b0d060dacf887afb8f615c25566290e4db9110b8d7","source":{"kind":"arxiv","id":"2210.15255","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.15255","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"arxiv_version","alias_value":"2210.15255v1","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.15255","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"pith_short_12","alias_value":"U72OQR4EUGIK","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"pith_short_16","alias_value":"U72OQR4EUGIKY52R","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"pith_short_8","alias_value":"U72OQR4E","created_at":"2026-07-05T05:11:04Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2022:U72OQR4EUGIKY52RSWYNAYG2Z6","target":"record","payload":{"canonical_record":{"source":{"id":"2210.15255","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2022-10-27T08:18:25Z","cross_cats_sorted":[],"title_canon_sha256":"b2ceed727abb8302bcbb319e8cc773584744df9925722aa765a7587cb7ace39a","abstract_canon_sha256":"081f415545b0e7018b6746929d10e282778d3dc70bba09b1e69392121dd2b2da"},"schema_version":"1.0"},"canonical_sha256":"a7f4e84784a190ac775195b0d060dacf887afb8f615c25566290e4db9110b8d7","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T05:11:04.311908Z","signature_b64":"NDCGeWjfK6bQS/BQMkHdNkhfQrT4VYaTQ2Fcv+UXSZIGU/A/sOR2/CiXbKXbC1UiSU/AmUUCDJJmMmBQh+CFBQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a7f4e84784a190ac775195b0d060dacf887afb8f615c25566290e4db9110b8d7","last_reissued_at":"2026-07-05T05:11:04.311308Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T05:11:04.311308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2210.15255","source_version":1,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T05:11:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"RBuqpIqSvVjgKfzaUx5PafTGL8Vbd1dggJS469rxW/EktaOUWTXbMrGXWaml32v+wwzfHrGOkh8eEaKPB/SLDQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T07:46:47.015218Z"},"content_sha256":"c0933ed6e5d2d48392cfd92ebc987ab5558f338ad4e5ac822229228df1e6023e","schema_version":"1.0","event_id":"sha256:c0933ed6e5d2d48392cfd92ebc987ab5558f338ad4e5ac822229228df1e6023e"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2022:U72OQR4EUGIKY52RSWYNAYG2Z6","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.AR","authors_text":"Chengyang Gu, Fangxin Liu, Li Jiang, Mingyu Gao, Naifeng Jing, Qidong Tang, Tao Yang, Xiaoyao Liang, Yilong Zhao","submitted_at":"2022-10-27T08:18:25Z","abstract_excerpt":"The second-order training methods can converge much faster than first-order optimizers in DNN training. This is because the second-order training utilizes the inversion of the second-order information (SOI) matrix to find a more accurate descent direction and step size. However, the huge SOI matrices bring significant computational and memory overheads in the traditional architectures like GPU and CPU. On the other side, the ReRAM-based process-in-memory (PIM) technology is suitable for the second-order training because of the following three reasons: First, PIM's computation happens in memory"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.15255","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/2210.15255/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":"2026-07-05T05:11:04Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"EUf1LbhYbfqTo08GvdFPicMZUx1ES0Pg3NWmWeerKZA8A5qEBWqXFKmW8jR9VoMfja0itLwrbm88IpBJfOCEAA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-20T07:46:47.015725Z"},"content_sha256":"9d2010c4cf196981ead44e34d78a1c25b62c59aa3dadc8764010dbf7a3206050","schema_version":"1.0","event_id":"sha256:9d2010c4cf196981ead44e34d78a1c25b62c59aa3dadc8764010dbf7a3206050"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/U72OQR4EUGIKY52RSWYNAYG2Z6/bundle.json","state_url":"https://pith.science/pith/U72OQR4EUGIKY52RSWYNAYG2Z6/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/U72OQR4EUGIKY52RSWYNAYG2Z6/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":"2026-08-20T07:46:47Z","links":{"resolver":"https://pith.science/pith/U72OQR4EUGIKY52RSWYNAYG2Z6","bundle":"https://pith.science/pith/U72OQR4EUGIKY52RSWYNAYG2Z6/bundle.json","state":"https://pith.science/pith/U72OQR4EUGIKY52RSWYNAYG2Z6/state.json","well_known_bundle":"https://pith.science/.well-known/pith/U72OQR4EUGIKY52RSWYNAYG2Z6/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2022:U72OQR4EUGIKY52RSWYNAYG2Z6","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":"081f415545b0e7018b6746929d10e282778d3dc70bba09b1e69392121dd2b2da","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2022-10-27T08:18:25Z","title_canon_sha256":"b2ceed727abb8302bcbb319e8cc773584744df9925722aa765a7587cb7ace39a"},"schema_version":"1.0","source":{"id":"2210.15255","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2210.15255","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"arxiv_version","alias_value":"2210.15255v1","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2210.15255","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"pith_short_12","alias_value":"U72OQR4EUGIK","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"pith_short_16","alias_value":"U72OQR4EUGIKY52R","created_at":"2026-07-05T05:11:04Z"},{"alias_kind":"pith_short_8","alias_value":"U72OQR4E","created_at":"2026-07-05T05:11:04Z"}],"graph_snapshots":[{"event_id":"sha256:9d2010c4cf196981ead44e34d78a1c25b62c59aa3dadc8764010dbf7a3206050","target":"graph","created_at":"2026-07-05T05:11:04Z","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/2210.15255/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"The second-order training methods can converge much faster than first-order optimizers in DNN training. This is because the second-order training utilizes the inversion of the second-order information (SOI) matrix to find a more accurate descent direction and step size. However, the huge SOI matrices bring significant computational and memory overheads in the traditional architectures like GPU and CPU. On the other side, the ReRAM-based process-in-memory (PIM) technology is suitable for the second-order training because of the following three reasons: First, PIM's computation happens in memory","authors_text":"Chengyang Gu, Fangxin Liu, Li Jiang, Mingyu Gao, Naifeng Jing, Qidong Tang, Tao Yang, Xiaoyao Liang, Yilong Zhao","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2022-10-27T08:18:25Z","title":"RePAST: A ReRAM-based PIM Accelerator for Second-order Training of DNN"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2210.15255","kind":"arxiv","version":1},"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:c0933ed6e5d2d48392cfd92ebc987ab5558f338ad4e5ac822229228df1e6023e","target":"record","created_at":"2026-07-05T05:11:04Z","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":"081f415545b0e7018b6746929d10e282778d3dc70bba09b1e69392121dd2b2da","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2022-10-27T08:18:25Z","title_canon_sha256":"b2ceed727abb8302bcbb319e8cc773584744df9925722aa765a7587cb7ace39a"},"schema_version":"1.0","source":{"id":"2210.15255","kind":"arxiv","version":1}},"canonical_sha256":"a7f4e84784a190ac775195b0d060dacf887afb8f615c25566290e4db9110b8d7","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a7f4e84784a190ac775195b0d060dacf887afb8f615c25566290e4db9110b8d7","first_computed_at":"2026-07-05T05:11:04.311308Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T05:11:04.311308Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"NDCGeWjfK6bQS/BQMkHdNkhfQrT4VYaTQ2Fcv+UXSZIGU/A/sOR2/CiXbKXbC1UiSU/AmUUCDJJmMmBQh+CFBQ==","signature_status":"signed_v1","signed_at":"2026-07-05T05:11:04.311908Z","signed_message":"canonical_sha256_bytes"},"source_id":"2210.15255","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c0933ed6e5d2d48392cfd92ebc987ab5558f338ad4e5ac822229228df1e6023e","sha256:9d2010c4cf196981ead44e34d78a1c25b62c59aa3dadc8764010dbf7a3206050"],"state_sha256":"44c0caced30fe8e9f48d57b435e5b9856e5ba80ca7e80b8742f41083e9bc37fb"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"kUFKtfEApjBTmW/WHATCrU+bej2bXHAW4P6wkaZdOr4dX8+qpvgsz+pbiIo6Vk6DfrkaX/RTi7N4JcRwtEGMDA==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-20T07:46:47.019491Z","bundle_sha256":"a9994cb7bc1d8cc9084cf18a872103f43463ba523cf9a63ff494fa236a6f873d"}}