{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:4WGAB6MH55L4YRQWA5LIODH76G","short_pith_number":"pith:4WGAB6MH","canonical_record":{"source":{"id":"2502.02142","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-04T09:15:50Z","cross_cats_sorted":[],"title_canon_sha256":"7f499c2042620d70ba378e212ad4fbb2c528358f0b7899ada7b4fa9104148034","abstract_canon_sha256":"d68cfc02ee2c20005a064e2fbb29ad4169527695fe82e9821b60f0c4b2df42ed"},"schema_version":"1.0"},"canonical_sha256":"e58c00f987ef57cc46160756870cfff1a140295992ca902f917247d91123f5af","source":{"kind":"arxiv","id":"2502.02142","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02142","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02142v1","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02142","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_12","alias_value":"4WGAB6MH55L4","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_16","alias_value":"4WGAB6MH55L4YRQW","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_8","alias_value":"4WGAB6MH","created_at":"2026-07-05T10:09:24Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:4WGAB6MH55L4YRQWA5LIODH76G","target":"record","payload":{"canonical_record":{"source":{"id":"2502.02142","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-04T09:15:50Z","cross_cats_sorted":[],"title_canon_sha256":"7f499c2042620d70ba378e212ad4fbb2c528358f0b7899ada7b4fa9104148034","abstract_canon_sha256":"d68cfc02ee2c20005a064e2fbb29ad4169527695fe82e9821b60f0c4b2df42ed"},"schema_version":"1.0"},"canonical_sha256":"e58c00f987ef57cc46160756870cfff1a140295992ca902f917247d91123f5af","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:09:24.650353Z","signature_b64":"N4AVZ7KIK96UY+/BKTwR1nwCQGvV0PpkCtaq7uq+fR8XAXDhHo8q0SyWw+2g1s1H/spN+YJ8UI6KU+pcdaazCg==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e58c00f987ef57cc46160756870cfff1a140295992ca902f917247d91123f5af","last_reissued_at":"2026-07-05T10:09:24.649851Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:09:24.649851Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.02142","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":"2026-07-05T10:09:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"Z+EruYcqtwo9qdH8k8BPqSdOi4gmRkcyyTLUjDnakPwkJufrussm1vP+v5JSegL/M4hI8/P3Yb0wigV9yEjqBQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T07:25:38.070555Z"},"content_sha256":"c7494dfd61ea25cff579c2bfa28d9ae8547d206d7835251f96eb7ce1f38e9a41","schema_version":"1.0","event_id":"sha256:c7494dfd61ea25cff579c2bfa28d9ae8547d206d7835251f96eb7ce1f38e9a41"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:4WGAB6MH55L4YRQWA5LIODH76G","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Towards Efficient LUT-based PIM: A Scalable and Low-Power Approach for Modern Workloads","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":[],"primary_cat":"cs.AR","authors_text":"Antonio Gonz\\'alez, Bahareh Khabbazan, Marc Riera","submitted_at":"2025-02-04T09:15:50Z","abstract_excerpt":"Data movement in memory-intensive workloads, such as deep learning, incurs energy costs that are over three orders of magnitude higher than the cost of computation. Since these workloads involve frequent data transfers between memory and processing units, addressing data movement overheads is crucial for improving performance. Processing-using-memory (PuM) offers an effective solution by enabling in-memory computation, thereby minimizing data transfers. In this paper we propose Lama, a LUT-based PuM architecture designed to efficiently execute SIMD operations by supporting independent column a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02142","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/2502.02142/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":"2026-07-05T10:09:24Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"K2l0smedrp5fC2wOCMlSR3lZCbLTtabQZgFghIARPHbEoSdlSixionElHuSKMPbTMlPA4TqgY43YGfzUB4ShCA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-10T07:25:38.071117Z"},"content_sha256":"06af51339bbfc45cb2feacce42d290e5cfa5868c8464d67b87d90d6b6d760537","schema_version":"1.0","event_id":"sha256:06af51339bbfc45cb2feacce42d290e5cfa5868c8464d67b87d90d6b6d760537"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4WGAB6MH55L4YRQWA5LIODH76G/bundle.json","state_url":"https://pith.science/pith/4WGAB6MH55L4YRQWA5LIODH76G/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4WGAB6MH55L4YRQWA5LIODH76G/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":"2026-08-10T07:25:38Z","links":{"resolver":"https://pith.science/pith/4WGAB6MH55L4YRQWA5LIODH76G","bundle":"https://pith.science/pith/4WGAB6MH55L4YRQWA5LIODH76G/bundle.json","state":"https://pith.science/pith/4WGAB6MH55L4YRQWA5LIODH76G/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4WGAB6MH55L4YRQWA5LIODH76G/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:4WGAB6MH55L4YRQWA5LIODH76G","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":"d68cfc02ee2c20005a064e2fbb29ad4169527695fe82e9821b60f0c4b2df42ed","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-04T09:15:50Z","title_canon_sha256":"7f499c2042620d70ba378e212ad4fbb2c528358f0b7899ada7b4fa9104148034"},"schema_version":"1.0","source":{"id":"2502.02142","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.02142","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"arxiv_version","alias_value":"2502.02142v1","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.02142","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_12","alias_value":"4WGAB6MH55L4","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_16","alias_value":"4WGAB6MH55L4YRQW","created_at":"2026-07-05T10:09:24Z"},{"alias_kind":"pith_short_8","alias_value":"4WGAB6MH","created_at":"2026-07-05T10:09:24Z"}],"graph_snapshots":[{"event_id":"sha256:06af51339bbfc45cb2feacce42d290e5cfa5868c8464d67b87d90d6b6d760537","target":"graph","created_at":"2026-07-05T10:09:24Z","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/2502.02142/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Data movement in memory-intensive workloads, such as deep learning, incurs energy costs that are over three orders of magnitude higher than the cost of computation. Since these workloads involve frequent data transfers between memory and processing units, addressing data movement overheads is crucial for improving performance. Processing-using-memory (PuM) offers an effective solution by enabling in-memory computation, thereby minimizing data transfers. In this paper we propose Lama, a LUT-based PuM architecture designed to efficiently execute SIMD operations by supporting independent column a","authors_text":"Antonio Gonz\\'alez, Bahareh Khabbazan, Marc Riera","cross_cats":[],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-04T09:15:50Z","title":"Towards Efficient LUT-based PIM: A Scalable and Low-Power Approach for Modern Workloads"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.02142","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:c7494dfd61ea25cff579c2bfa28d9ae8547d206d7835251f96eb7ce1f38e9a41","target":"record","created_at":"2026-07-05T10:09:24Z","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":"d68cfc02ee2c20005a064e2fbb29ad4169527695fe82e9821b60f0c4b2df42ed","cross_cats_sorted":[],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-04T09:15:50Z","title_canon_sha256":"7f499c2042620d70ba378e212ad4fbb2c528358f0b7899ada7b4fa9104148034"},"schema_version":"1.0","source":{"id":"2502.02142","kind":"arxiv","version":1}},"canonical_sha256":"e58c00f987ef57cc46160756870cfff1a140295992ca902f917247d91123f5af","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e58c00f987ef57cc46160756870cfff1a140295992ca902f917247d91123f5af","first_computed_at":"2026-07-05T10:09:24.649851Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:09:24.649851Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"N4AVZ7KIK96UY+/BKTwR1nwCQGvV0PpkCtaq7uq+fR8XAXDhHo8q0SyWw+2g1s1H/spN+YJ8UI6KU+pcdaazCg==","signature_status":"signed_v1","signed_at":"2026-07-05T10:09:24.650353Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.02142","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c7494dfd61ea25cff579c2bfa28d9ae8547d206d7835251f96eb7ce1f38e9a41","sha256:06af51339bbfc45cb2feacce42d290e5cfa5868c8464d67b87d90d6b6d760537"],"state_sha256":"9aeaeaf42d302093e427aaae88c897ae5f5dc45ae8333b058187ca0234db0c34"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"9t4bjQSEhAW0K1nckBGStZuT9lKaJyLrleo5NonbTUt8hKWpvMqeF9BrhBye1GZL7LIXgnojs9wnuiPDqcIECw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-10T07:25:38.074767Z","bundle_sha256":"d7e53d1317e0e69f18a3a97188fda91c395f9530ce08812fa1b65dfe20e03d6c"}}