{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2025:VCYOG57QQMMZOIVARMN7WK5QAV","short_pith_number":"pith:VCYOG57Q","canonical_record":{"source":{"id":"2502.15470","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-21T13:52:31Z","cross_cats_sorted":["cs.AI","cs.DC","cs.LG"],"title_canon_sha256":"485b0fca32489ede5ff34ba2a76da0034358aa2f075c3757ae0b3fc242cf656f","abstract_canon_sha256":"ba03e7b5599434d045bf7950189069574e15517d093873d2d259a136c9b6d7c4"},"schema_version":"1.0"},"canonical_sha256":"a8b0e377f083199722a08b1bfb2bb0056abbb7c41847000d3a2b8bb5f39c702f","source":{"kind":"arxiv","id":"2502.15470","version":2},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.15470","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"arxiv_version","alias_value":"2502.15470v2","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.15470","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"pith_short_12","alias_value":"VCYOG57QQMMZ","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"pith_short_16","alias_value":"VCYOG57QQMMZOIVA","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"pith_short_8","alias_value":"VCYOG57Q","created_at":"2026-07-05T10:20:44Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2025:VCYOG57QQMMZOIVARMN7WK5QAV","target":"record","payload":{"canonical_record":{"source":{"id":"2502.15470","kind":"arxiv","version":2},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-21T13:52:31Z","cross_cats_sorted":["cs.AI","cs.DC","cs.LG"],"title_canon_sha256":"485b0fca32489ede5ff34ba2a76da0034358aa2f075c3757ae0b3fc242cf656f","abstract_canon_sha256":"ba03e7b5599434d045bf7950189069574e15517d093873d2d259a136c9b6d7c4"},"schema_version":"1.0"},"canonical_sha256":"a8b0e377f083199722a08b1bfb2bb0056abbb7c41847000d3a2b8bb5f39c702f","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T10:20:44.724461Z","signature_b64":"iiMkShzCV43pWDZpaNuxQh8pdyccxrnJfQuMaRSZ0s8IAZZXc+ySg6Xl1XYVM6g8STe/2P5ea6hDjG7AN7f1Bw==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a8b0e377f083199722a08b1bfb2bb0056abbb7c41847000d3a2b8bb5f39c702f","last_reissued_at":"2026-07-05T10:20:44.723919Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T10:20:44.723919Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2502.15470","source_version":2,"attestation_state":"computed"},"signer":{"signer_id":"pith.science","signer_type":"pith_registry","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"created_at":"2026-07-05T10:20:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"eHKy7Pg6WPYs4jPC9TiEmBUJMewaySft5sr5782FBEQAmCExBQh1z1D40yTBwUWeO76jxVpeKSvwoUYV38a5Dg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:28:42.012569Z"},"content_sha256":"c8a0ef5b632c3d72e1a83822a1f9b285fa2c1ca60bbdee6864babb9baf0583d0","schema_version":"1.0","event_id":"sha256:c8a0ef5b632c3d72e1a83822a1f9b285fa2c1ca60bbdee6864babb9baf0583d0"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2025:VCYOG57QQMMZOIVARMN7WK5QAV","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.AI","cs.DC","cs.LG"],"primary_cat":"cs.AR","authors_text":"Christina Giannoula, Haiyu Mao, Huawei Li, Juan G\\'omez-Luna, Mohammad Sadrosadati, Onur Mutlu, Xiaowei Li, Ying Wang, Yintao He","submitted_at":"2025-02-21T13:52:31Z","abstract_excerpt":"Large language models (LLMs) are widely used for natural language understanding and text generation. An LLM model relies on a time-consuming step called LLM decoding to generate output tokens. Several prior works focus on improving the performance of LLM decoding using parallelism techniques, such as batching and speculative decoding. State-of-the-art LLM decoding has both compute-bound and memory-bound kernels. Some prior works statically identify and map these different kernels to a heterogeneous architecture consisting of both processing-in-memory (PIM) units and computation-centric acceler"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.15470","kind":"arxiv","version":2},"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/2502.15470/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":"2026-07-05T10:20:44Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"BYJKhD1X2gWn79tCd89Y285Q2wEtKghfIysf+P6w8guXcB1zhp29UAMh3Zh4rxRbOQZ+PlXcDYoKjNMKRvWJCg==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-08T19:28:42.012954Z"},"content_sha256":"a0564c7cdf7b9ee38520f06b4f47437bcdfab28d84677e2bc0e182d1a35972bb","schema_version":"1.0","event_id":"sha256:a0564c7cdf7b9ee38520f06b4f47437bcdfab28d84677e2bc0e182d1a35972bb"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VCYOG57QQMMZOIVARMN7WK5QAV/bundle.json","state_url":"https://pith.science/pith/VCYOG57QQMMZOIVARMN7WK5QAV/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VCYOG57QQMMZOIVARMN7WK5QAV/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":"2026-07-08T19:28:42Z","links":{"resolver":"https://pith.science/pith/VCYOG57QQMMZOIVARMN7WK5QAV","bundle":"https://pith.science/pith/VCYOG57QQMMZOIVARMN7WK5QAV/bundle.json","state":"https://pith.science/pith/VCYOG57QQMMZOIVARMN7WK5QAV/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VCYOG57QQMMZOIVARMN7WK5QAV/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2025:VCYOG57QQMMZOIVARMN7WK5QAV","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":"ba03e7b5599434d045bf7950189069574e15517d093873d2d259a136c9b6d7c4","cross_cats_sorted":["cs.AI","cs.DC","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-21T13:52:31Z","title_canon_sha256":"485b0fca32489ede5ff34ba2a76da0034358aa2f075c3757ae0b3fc242cf656f"},"schema_version":"1.0","source":{"id":"2502.15470","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2502.15470","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"arxiv_version","alias_value":"2502.15470v2","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2502.15470","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"pith_short_12","alias_value":"VCYOG57QQMMZ","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"pith_short_16","alias_value":"VCYOG57QQMMZOIVA","created_at":"2026-07-05T10:20:44Z"},{"alias_kind":"pith_short_8","alias_value":"VCYOG57Q","created_at":"2026-07-05T10:20:44Z"}],"graph_snapshots":[{"event_id":"sha256:a0564c7cdf7b9ee38520f06b4f47437bcdfab28d84677e2bc0e182d1a35972bb","target":"graph","created_at":"2026-07-05T10:20:44Z","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/2502.15470/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large language models (LLMs) are widely used for natural language understanding and text generation. An LLM model relies on a time-consuming step called LLM decoding to generate output tokens. Several prior works focus on improving the performance of LLM decoding using parallelism techniques, such as batching and speculative decoding. State-of-the-art LLM decoding has both compute-bound and memory-bound kernels. Some prior works statically identify and map these different kernels to a heterogeneous architecture consisting of both processing-in-memory (PIM) units and computation-centric acceler","authors_text":"Christina Giannoula, Haiyu Mao, Huawei Li, Juan G\\'omez-Luna, Mohammad Sadrosadati, Onur Mutlu, Xiaowei Li, Ying Wang, Yintao He","cross_cats":["cs.AI","cs.DC","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-21T13:52:31Z","title":"PAPI: Exploiting Dynamic Parallelism in Large Language Model Decoding with a Processing-In-Memory-Enabled Computing System"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2502.15470","kind":"arxiv","version":2},"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:c8a0ef5b632c3d72e1a83822a1f9b285fa2c1ca60bbdee6864babb9baf0583d0","target":"record","created_at":"2026-07-05T10:20:44Z","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":"ba03e7b5599434d045bf7950189069574e15517d093873d2d259a136c9b6d7c4","cross_cats_sorted":["cs.AI","cs.DC","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2025-02-21T13:52:31Z","title_canon_sha256":"485b0fca32489ede5ff34ba2a76da0034358aa2f075c3757ae0b3fc242cf656f"},"schema_version":"1.0","source":{"id":"2502.15470","kind":"arxiv","version":2}},"canonical_sha256":"a8b0e377f083199722a08b1bfb2bb0056abbb7c41847000d3a2b8bb5f39c702f","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a8b0e377f083199722a08b1bfb2bb0056abbb7c41847000d3a2b8bb5f39c702f","first_computed_at":"2026-07-05T10:20:44.723919Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T10:20:44.723919Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"iiMkShzCV43pWDZpaNuxQh8pdyccxrnJfQuMaRSZ0s8IAZZXc+ySg6Xl1XYVM6g8STe/2P5ea6hDjG7AN7f1Bw==","signature_status":"signed_v1","signed_at":"2026-07-05T10:20:44.724461Z","signed_message":"canonical_sha256_bytes"},"source_id":"2502.15470","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:c8a0ef5b632c3d72e1a83822a1f9b285fa2c1ca60bbdee6864babb9baf0583d0","sha256:a0564c7cdf7b9ee38520f06b4f47437bcdfab28d84677e2bc0e182d1a35972bb"],"state_sha256":"fd12c41d2f7382ac48fc0ccd7bd65c3d81ef90a0bcf3225df248e5c9da5988a1"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"qpV7nc1ruyfV5GLkXxOX/IvIwon8stdKvufa2oJv0WooaKKD8BsmkBqgOhLMMpNabVLS1aAi6eqIwYO6S/vdBw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-08T19:28:42.015047Z","bundle_sha256":"db739db4cff46d071d171c607584526a3191de69cc8dfd0d1a498f68e8ab6557"}}