{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2024:4B7JXVAOOGNPV2GTCAXIYEAUHD","short_pith_number":"pith:4B7JXVAO","canonical_record":{"source":{"id":"2401.09890","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2024-01-18T11:05:03Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"ab02a08745ef376c6f6ba8c20090c9d80a3ddb7e929262f2062d1e160ca6ca33","abstract_canon_sha256":"7f2ce284ec4b2c6b3341bba9fed64b5dba182f05b2fb961a4ed4de555bb07a80"},"schema_version":"1.0"},"canonical_sha256":"e07e9bd40e719afae8d3102e8c101438cdc0e9a5dfc53c158072d7052fe80821","source":{"kind":"arxiv","id":"2401.09890","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.09890","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"arxiv_version","alias_value":"2401.09890v1","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.09890","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"pith_short_12","alias_value":"4B7JXVAOOGNP","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"pith_short_16","alias_value":"4B7JXVAOOGNPV2GT","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"pith_short_8","alias_value":"4B7JXVAO","created_at":"2026-07-05T09:59:13Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2024:4B7JXVAOOGNPV2GTCAXIYEAUHD","target":"record","payload":{"canonical_record":{"source":{"id":"2401.09890","kind":"arxiv","version":1},"metadata":{"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2024-01-18T11:05:03Z","cross_cats_sorted":["cs.CL","cs.LG"],"title_canon_sha256":"ab02a08745ef376c6f6ba8c20090c9d80a3ddb7e929262f2062d1e160ca6ca33","abstract_canon_sha256":"7f2ce284ec4b2c6b3341bba9fed64b5dba182f05b2fb961a4ed4de555bb07a80"},"schema_version":"1.0"},"canonical_sha256":"e07e9bd40e719afae8d3102e8c101438cdc0e9a5dfc53c158072d7052fe80821","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T09:59:13.980519Z","signature_b64":"g6Zd1bzXVsD0cw/Z3nt6r08v1hNCI/j/23ChkctX0hiMOzLpwO1fw5/B6PTJQhmRYmtVIsdeV/JhgkyarBleAA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"e07e9bd40e719afae8d3102e8c101438cdc0e9a5dfc53c158072d7052fe80821","last_reissued_at":"2026-07-05T09:59:13.980098Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T09:59:13.980098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2401.09890","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":"2026-07-05T09:59:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"lHH7JlyEeUEvEcMd/u2UQFGQSRd1+PYPwq/vDz0pdH8a3MIITRPDfMGSeQnUrHoqfWi+V3Ci0dHhHmeKs9ekBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T10:24:41.939782Z"},"content_sha256":"91820f604539d9b3095e5ef63a5ce73b9bdfb0cca8dc69607d9bcf056236bcec","schema_version":"1.0","event_id":"sha256:91820f604539d9b3095e5ef63a5ce73b9bdfb0cca8dc69607d9bcf056236bcec"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2024:4B7JXVAOOGNPV2GTCAXIYEAUHD","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"A Survey on Hardware Accelerators for Large Language Models","license":"http://creativecommons.org/licenses/by/4.0/","headline":"","cross_cats":["cs.CL","cs.LG"],"primary_cat":"cs.AR","authors_text":"Christoforos Kachris","submitted_at":"2024-01-18T11:05:03Z","abstract_excerpt":"Large Language Models (LLMs) have emerged as powerful tools for natural language processing tasks, revolutionizing the field with their ability to understand and generate human-like text. As the demand for more sophisticated LLMs continues to grow, there is a pressing need to address the computational challenges associated with their scale and complexity. This paper presents a comprehensive survey on hardware accelerators designed to enhance the performance and energy efficiency of Large Language Models. By examining a diverse range of accelerators, including GPUs, FPGAs, and custom-designed a"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.09890","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/2401.09890/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":"2026-07-05T09:59:13Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"iRw78oTUGYfMVu26OkybWdhKWJqjMoUKD8Ya1OyNxuTuj/qfgcbJlum21ZaFe+4OvTw9CH2+8W7aSIpD35a3DA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-08T10:24:41.940294Z"},"content_sha256":"4ef6e416c8d61837613fb6856dbd15ec433be6a4b1dea8272e3b71fe6637ca6b","schema_version":"1.0","event_id":"sha256:4ef6e416c8d61837613fb6856dbd15ec433be6a4b1dea8272e3b71fe6637ca6b"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/4B7JXVAOOGNPV2GTCAXIYEAUHD/bundle.json","state_url":"https://pith.science/pith/4B7JXVAOOGNPV2GTCAXIYEAUHD/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/4B7JXVAOOGNPV2GTCAXIYEAUHD/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":"2026-08-08T10:24:41Z","links":{"resolver":"https://pith.science/pith/4B7JXVAOOGNPV2GTCAXIYEAUHD","bundle":"https://pith.science/pith/4B7JXVAOOGNPV2GTCAXIYEAUHD/bundle.json","state":"https://pith.science/pith/4B7JXVAOOGNPV2GTCAXIYEAUHD/state.json","well_known_bundle":"https://pith.science/.well-known/pith/4B7JXVAOOGNPV2GTCAXIYEAUHD/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2024:4B7JXVAOOGNPV2GTCAXIYEAUHD","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":"7f2ce284ec4b2c6b3341bba9fed64b5dba182f05b2fb961a4ed4de555bb07a80","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2024-01-18T11:05:03Z","title_canon_sha256":"ab02a08745ef376c6f6ba8c20090c9d80a3ddb7e929262f2062d1e160ca6ca33"},"schema_version":"1.0","source":{"id":"2401.09890","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2401.09890","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"arxiv_version","alias_value":"2401.09890v1","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2401.09890","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"pith_short_12","alias_value":"4B7JXVAOOGNP","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"pith_short_16","alias_value":"4B7JXVAOOGNPV2GT","created_at":"2026-07-05T09:59:13Z"},{"alias_kind":"pith_short_8","alias_value":"4B7JXVAO","created_at":"2026-07-05T09:59:13Z"}],"graph_snapshots":[{"event_id":"sha256:4ef6e416c8d61837613fb6856dbd15ec433be6a4b1dea8272e3b71fe6637ca6b","target":"graph","created_at":"2026-07-05T09:59:13Z","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/2401.09890/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Large Language Models (LLMs) have emerged as powerful tools for natural language processing tasks, revolutionizing the field with their ability to understand and generate human-like text. As the demand for more sophisticated LLMs continues to grow, there is a pressing need to address the computational challenges associated with their scale and complexity. This paper presents a comprehensive survey on hardware accelerators designed to enhance the performance and energy efficiency of Large Language Models. By examining a diverse range of accelerators, including GPUs, FPGAs, and custom-designed a","authors_text":"Christoforos Kachris","cross_cats":["cs.CL","cs.LG"],"headline":"","license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2024-01-18T11:05:03Z","title":"A Survey on Hardware Accelerators for Large Language Models"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2401.09890","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":"sha256:91820f604539d9b3095e5ef63a5ce73b9bdfb0cca8dc69607d9bcf056236bcec","target":"record","created_at":"2026-07-05T09:59:13Z","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":"7f2ce284ec4b2c6b3341bba9fed64b5dba182f05b2fb961a4ed4de555bb07a80","cross_cats_sorted":["cs.CL","cs.LG"],"license":"http://creativecommons.org/licenses/by/4.0/","primary_cat":"cs.AR","submitted_at":"2024-01-18T11:05:03Z","title_canon_sha256":"ab02a08745ef376c6f6ba8c20090c9d80a3ddb7e929262f2062d1e160ca6ca33"},"schema_version":"1.0","source":{"id":"2401.09890","kind":"arxiv","version":1}},"canonical_sha256":"e07e9bd40e719afae8d3102e8c101438cdc0e9a5dfc53c158072d7052fe80821","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"e07e9bd40e719afae8d3102e8c101438cdc0e9a5dfc53c158072d7052fe80821","first_computed_at":"2026-07-05T09:59:13.980098Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T09:59:13.980098Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"g6Zd1bzXVsD0cw/Z3nt6r08v1hNCI/j/23ChkctX0hiMOzLpwO1fw5/B6PTJQhmRYmtVIsdeV/JhgkyarBleAA==","signature_status":"signed_v1","signed_at":"2026-07-05T09:59:13.980519Z","signed_message":"canonical_sha256_bytes"},"source_id":"2401.09890","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:91820f604539d9b3095e5ef63a5ce73b9bdfb0cca8dc69607d9bcf056236bcec","sha256:4ef6e416c8d61837613fb6856dbd15ec433be6a4b1dea8272e3b71fe6637ca6b"],"state_sha256":"f0b95557b50e5ad1a6341c95b452922ca54377c2e0a8c37f1172f8cff39308b7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"oHhpR1k9bbiLZOUM/GRu138LMwtA5v6cOqSm4pE9vzYJ5GUKrjl+DwwMYxmjp3Sik/hsRDN2Y9XSCcJ2F6VZCw==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-08T10:24:41.944229Z","bundle_sha256":"6dd826835c77bde1e34192513dbb0e39735cdf9addb5bca34bef60f4ec7f4055"}}