{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2026:VVAIBSG4L2TTDXL67ABHWYQURE","short_pith_number":"pith:VVAIBSG4","canonical_record":{"source":{"id":"2606.22812","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-06-22T03:41:12Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"077400832ee557875b5c6a54aec57afb094aceac30a27b774bd452d0a262a5ec","abstract_canon_sha256":"74384c142a3596e22ecdfa79501d4a2cc199975ff0748d129b2f4ef6f47a96bc"},"schema_version":"1.0"},"canonical_sha256":"ad4080c8dc5ea731dd7ef8027b6214890280e9c2336498b427a773df232e4b35","source":{"kind":"arxiv","id":"2606.22812","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.22812","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"arxiv_version","alias_value":"2606.22812v1","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.22812","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"pith_short_12","alias_value":"VVAIBSG4L2TT","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"pith_short_16","alias_value":"VVAIBSG4L2TTDXL6","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"pith_short_8","alias_value":"VVAIBSG4","created_at":"2026-06-23T02:14:00Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2026:VVAIBSG4L2TTDXL67ABHWYQURE","target":"record","payload":{"canonical_record":{"source":{"id":"2606.22812","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-06-22T03:41:12Z","cross_cats_sorted":["cs.DC"],"title_canon_sha256":"077400832ee557875b5c6a54aec57afb094aceac30a27b774bd452d0a262a5ec","abstract_canon_sha256":"74384c142a3596e22ecdfa79501d4a2cc199975ff0748d129b2f4ef6f47a96bc"},"schema_version":"1.0"},"canonical_sha256":"ad4080c8dc5ea731dd7ef8027b6214890280e9c2336498b427a773df232e4b35","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-06-23T02:14:00.089290Z","signature_b64":"GrND52MU6SCNtXa9cRwODU3wuy55O/lq7hV7fo5hjhnsTJykQj7oUVK8c5mQic31wjMdEoGa3HySj3CrF3XeDA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ad4080c8dc5ea731dd7ef8027b6214890280e9c2336498b427a773df232e4b35","last_reissued_at":"2026-06-23T02:14:00.088841Z","signature_status":"signed_v1","first_computed_at":"2026-06-23T02:14:00.088841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2606.22812","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":"2026-06-23T02:14:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1krDtNDc21wy0Os7rj8rB9tpY4OWmqNKn62HmC2xvMPHFJoFzYmNIUo45DOFdclC9EjVLOZj0ksgHtS1anJ7Aw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T16:35:52.621895Z"},"content_sha256":"dd9161d9a6b9adf3098b67655f34975429c382c93471f29baeed7b0de52a31fb","schema_version":"1.0","event_id":"sha256:dd9161d9a6b9adf3098b67655f34975429c382c93471f29baeed7b0de52a31fb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2026:VVAIBSG4L2TTDXL67ABHWYQURE","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Clutch: High Performance Vector-Scalar Comparison using DRAM via Chunked Temporal Coding","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.DC"],"primary_cat":"cs.AR","authors_text":"Abdullah Giray Ya\\u{g}l{\\i}k\\c{c}{\\i}, Ataberk Olgun, Daichi Tokuda, Geraldo F. Oliveira, Haocong Luo, Ismail Emir Yuksel, Mohammad Sadrosadati, Onur Mutlu, Shinya Takamaeda-Yamazaki, Tatsuya Kubo, Tomoya Nagatani","submitted_at":"2026-06-22T03:41:12Z","abstract_excerpt":"Vector-scalar comparison is a fundamental computation primitive that compares each element in a vector against a single scalar value. It is widely used in various data-intensive workloads from databases to machine learning. Due to its low computational intensity, its execution tends to be memory-bound, limiting the utilization of compute resources. Processing-using-DRAM (PuD) is an emerging computing paradigm that performs massively parallel bitwise operations directly inside DRAM arrays, alleviating off-chip data movement. Existing PuD-based approaches require many DRAM commands because the c"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22812","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/2606.22812/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":"2026-06-23T02:14:00Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"dVO/r4DMjQFzESIOxa/bC/bma26armZhWsQ4zLDO5OrzzOIWzolSi16mf1Q4LCUxL8uS3FRRLSRMUCGPK6gqBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-06-26T16:35:52.622278Z"},"content_sha256":"66e239ccd73b8cfe4882c81efcaca6766a0f0e46818615c1c56bbe602a1272a8","schema_version":"1.0","event_id":"sha256:66e239ccd73b8cfe4882c81efcaca6766a0f0e46818615c1c56bbe602a1272a8"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VVAIBSG4L2TTDXL67ABHWYQURE/bundle.json","state_url":"https://pith.science/pith/VVAIBSG4L2TTDXL67ABHWYQURE/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VVAIBSG4L2TTDXL67ABHWYQURE/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":"2026-06-26T16:35:52Z","links":{"resolver":"https://pith.science/pith/VVAIBSG4L2TTDXL67ABHWYQURE","bundle":"https://pith.science/pith/VVAIBSG4L2TTDXL67ABHWYQURE/bundle.json","state":"https://pith.science/pith/VVAIBSG4L2TTDXL67ABHWYQURE/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VVAIBSG4L2TTDXL67ABHWYQURE/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2026:VVAIBSG4L2TTDXL67ABHWYQURE","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":"74384c142a3596e22ecdfa79501d4a2cc199975ff0748d129b2f4ef6f47a96bc","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-06-22T03:41:12Z","title_canon_sha256":"077400832ee557875b5c6a54aec57afb094aceac30a27b774bd452d0a262a5ec"},"schema_version":"1.0","source":{"id":"2606.22812","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2606.22812","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"arxiv_version","alias_value":"2606.22812v1","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2606.22812","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"pith_short_12","alias_value":"VVAIBSG4L2TT","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"pith_short_16","alias_value":"VVAIBSG4L2TTDXL6","created_at":"2026-06-23T02:14:00Z"},{"alias_kind":"pith_short_8","alias_value":"VVAIBSG4","created_at":"2026-06-23T02:14:00Z"}],"graph_snapshots":[{"event_id":"sha256:66e239ccd73b8cfe4882c81efcaca6766a0f0e46818615c1c56bbe602a1272a8","target":"graph","created_at":"2026-06-23T02:14:00Z","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/2606.22812/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Vector-scalar comparison is a fundamental computation primitive that compares each element in a vector against a single scalar value. It is widely used in various data-intensive workloads from databases to machine learning. Due to its low computational intensity, its execution tends to be memory-bound, limiting the utilization of compute resources. Processing-using-DRAM (PuD) is an emerging computing paradigm that performs massively parallel bitwise operations directly inside DRAM arrays, alleviating off-chip data movement. Existing PuD-based approaches require many DRAM commands because the c","authors_text":"Abdullah Giray Ya\\u{g}l{\\i}k\\c{c}{\\i}, Ataberk Olgun, Daichi Tokuda, Geraldo F. Oliveira, Haocong Luo, Ismail Emir Yuksel, Mohammad Sadrosadati, Onur Mutlu, Shinya Takamaeda-Yamazaki, Tatsuya Kubo, Tomoya Nagatani","cross_cats":["cs.DC"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-06-22T03:41:12Z","title":"Clutch: High Performance Vector-Scalar Comparison using DRAM via Chunked Temporal Coding"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2606.22812","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:dd9161d9a6b9adf3098b67655f34975429c382c93471f29baeed7b0de52a31fb","target":"record","created_at":"2026-06-23T02:14:00Z","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":"74384c142a3596e22ecdfa79501d4a2cc199975ff0748d129b2f4ef6f47a96bc","cross_cats_sorted":["cs.DC"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2026-06-22T03:41:12Z","title_canon_sha256":"077400832ee557875b5c6a54aec57afb094aceac30a27b774bd452d0a262a5ec"},"schema_version":"1.0","source":{"id":"2606.22812","kind":"arxiv","version":1}},"canonical_sha256":"ad4080c8dc5ea731dd7ef8027b6214890280e9c2336498b427a773df232e4b35","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ad4080c8dc5ea731dd7ef8027b6214890280e9c2336498b427a773df232e4b35","first_computed_at":"2026-06-23T02:14:00.088841Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-06-23T02:14:00.088841Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"GrND52MU6SCNtXa9cRwODU3wuy55O/lq7hV7fo5hjhnsTJykQj7oUVK8c5mQic31wjMdEoGa3HySj3CrF3XeDA==","signature_status":"signed_v1","signed_at":"2026-06-23T02:14:00.089290Z","signed_message":"canonical_sha256_bytes"},"source_id":"2606.22812","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:dd9161d9a6b9adf3098b67655f34975429c382c93471f29baeed7b0de52a31fb","sha256:66e239ccd73b8cfe4882c81efcaca6766a0f0e46818615c1c56bbe602a1272a8"],"state_sha256":"780ee79e8c79db7cb03ef1a70a0bbec7c891c53202ea70313332b154343e711f"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"1hJlm4mOYNr12K1711f1o7VmKugLcsDWd/TIGnKQDz0ty/WAC6WR5IeJVoULlCiiA5W8I9b300x6Z9ZalBWdDg==","signed_message":"bundle_sha256_bytes","signed_at":"2026-06-26T16:35:52.624391Z","bundle_sha256":"52ed79a6bb452b72aef3307fa493400ce085a51e0c092eeeda4017422f8e0c01"}}