{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2020:VSASXWB3Q7L4EU6JFQUDHXUBXA","short_pith_number":"pith:VSASXWB3","canonical_record":{"source":{"id":"2008.06741","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2020-08-15T15:49:50Z","cross_cats_sorted":["cs.ET"],"title_canon_sha256":"08b6195e5b93ce45c40c67ed373c474373037055a5e0e44f901a3a9f3edd853a","abstract_canon_sha256":"0cdf79be9c8112447a2781003d8510a23e86a6d9fceb2313536cbafeaeb8fb10"},"schema_version":"1.0"},"canonical_sha256":"ac812bd83b87d7c253c92c2833de81b8369623d21af153fc1125e0defbfe6e38","source":{"kind":"arxiv","id":"2008.06741","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.06741","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"arxiv_version","alias_value":"2008.06741v1","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.06741","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"pith_short_12","alias_value":"VSASXWB3Q7L4","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"pith_short_16","alias_value":"VSASXWB3Q7L4EU6J","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"pith_short_8","alias_value":"VSASXWB3","created_at":"2026-07-05T01:27:31Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2020:VSASXWB3Q7L4EU6JFQUDHXUBXA","target":"record","payload":{"canonical_record":{"source":{"id":"2008.06741","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2020-08-15T15:49:50Z","cross_cats_sorted":["cs.ET"],"title_canon_sha256":"08b6195e5b93ce45c40c67ed373c474373037055a5e0e44f901a3a9f3edd853a","abstract_canon_sha256":"0cdf79be9c8112447a2781003d8510a23e86a6d9fceb2313536cbafeaeb8fb10"},"schema_version":"1.0"},"canonical_sha256":"ac812bd83b87d7c253c92c2833de81b8369623d21af153fc1125e0defbfe6e38","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T01:27:31.758197Z","signature_b64":"owx87aRrKB9kryEqZkZPu5bk9I41yZp+A206aGj05qII679PDgdUGLqvWtpNHTjCJs1w4GxBfai25AylYQrOCA==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"ac812bd83b87d7c253c92c2833de81b8369623d21af153fc1125e0defbfe6e38","last_reissued_at":"2026-07-05T01:27:31.757828Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T01:27:31.757828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2008.06741","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":"2026-07-05T01:27:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"3hxBP3XBHpuPdutm1J0TuT4ZCbXpRajjEQFLyU2nL8Pj7k7AEYyDi1L71GxqIN+9h2nSqBTb+af+L83klNW/CQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T18:22:13.546982Z"},"content_sha256":"eb26ea5ba48b1034c343fc6b313f665fc117ae0024a9da6901213da0df2c37eb","schema_version":"1.0","event_id":"sha256:eb26ea5ba48b1034c343fc6b313f665fc117ae0024a9da6901213da0df2c37eb"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2020:VSASXWB3Q7L4EU6JFQUDHXUBXA","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Breaking Barriers: Maximizing Array Utilization for Compute In-Memory Fabrics","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":["cs.ET"],"primary_cat":"cs.AR","authors_text":"Arijit Raychowdhury, Brian Crafton, Gauthaman Murali, Samuel Spetalnick, Sung-Kyu Lim, Tushar Krishna","submitted_at":"2020-08-15T15:49:50Z","abstract_excerpt":"Compute in-memory (CIM) is a promising technique that minimizes data transport, the primary performance bottleneck and energy cost of most data intensive applications. This has found wide-spread adoption in accelerating neural networks for machine learning applications. Utilizing a crossbar architecture with emerging non-volatile memories (eNVM) such as dense resistive random access memory (RRAM) or phase change random access memory (PCRAM), various forms of neural networks can be implemented to greatly reduce power and increase on chip memory capacity. However, compute in-memory faces its own"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.06741","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/2008.06741/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":"2026-07-05T01:27:31Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"ZNehIbRWlPvw0XdxUNwhpeijtSrtNIbrBoYRSLBwGZHAQ87Mft90mJJxklnaoyZbMQmXjdxcU+Qm5JAIRezsDw==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-07-26T18:22:13.547374Z"},"content_sha256":"40e06623735a8ef5623c78d66303fe0ea8f0c1e3354313c4b3657afbee9e4c73","schema_version":"1.0","event_id":"sha256:40e06623735a8ef5623c78d66303fe0ea8f0c1e3354313c4b3657afbee9e4c73"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/VSASXWB3Q7L4EU6JFQUDHXUBXA/bundle.json","state_url":"https://pith.science/pith/VSASXWB3Q7L4EU6JFQUDHXUBXA/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/VSASXWB3Q7L4EU6JFQUDHXUBXA/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":"2026-07-26T18:22:13Z","links":{"resolver":"https://pith.science/pith/VSASXWB3Q7L4EU6JFQUDHXUBXA","bundle":"https://pith.science/pith/VSASXWB3Q7L4EU6JFQUDHXUBXA/bundle.json","state":"https://pith.science/pith/VSASXWB3Q7L4EU6JFQUDHXUBXA/state.json","well_known_bundle":"https://pith.science/.well-known/pith/VSASXWB3Q7L4EU6JFQUDHXUBXA/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2020:VSASXWB3Q7L4EU6JFQUDHXUBXA","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":"0cdf79be9c8112447a2781003d8510a23e86a6d9fceb2313536cbafeaeb8fb10","cross_cats_sorted":["cs.ET"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2020-08-15T15:49:50Z","title_canon_sha256":"08b6195e5b93ce45c40c67ed373c474373037055a5e0e44f901a3a9f3edd853a"},"schema_version":"1.0","source":{"id":"2008.06741","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2008.06741","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"arxiv_version","alias_value":"2008.06741v1","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2008.06741","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"pith_short_12","alias_value":"VSASXWB3Q7L4","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"pith_short_16","alias_value":"VSASXWB3Q7L4EU6J","created_at":"2026-07-05T01:27:31Z"},{"alias_kind":"pith_short_8","alias_value":"VSASXWB3","created_at":"2026-07-05T01:27:31Z"}],"graph_snapshots":[{"event_id":"sha256:40e06623735a8ef5623c78d66303fe0ea8f0c1e3354313c4b3657afbee9e4c73","target":"graph","created_at":"2026-07-05T01:27:31Z","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/2008.06741/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Compute in-memory (CIM) is a promising technique that minimizes data transport, the primary performance bottleneck and energy cost of most data intensive applications. This has found wide-spread adoption in accelerating neural networks for machine learning applications. Utilizing a crossbar architecture with emerging non-volatile memories (eNVM) such as dense resistive random access memory (RRAM) or phase change random access memory (PCRAM), various forms of neural networks can be implemented to greatly reduce power and increase on chip memory capacity. However, compute in-memory faces its own","authors_text":"Arijit Raychowdhury, Brian Crafton, Gauthaman Murali, Samuel Spetalnick, Sung-Kyu Lim, Tushar Krishna","cross_cats":["cs.ET"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2020-08-15T15:49:50Z","title":"Breaking Barriers: Maximizing Array Utilization for Compute In-Memory Fabrics"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2008.06741","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:eb26ea5ba48b1034c343fc6b313f665fc117ae0024a9da6901213da0df2c37eb","target":"record","created_at":"2026-07-05T01:27:31Z","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":"0cdf79be9c8112447a2781003d8510a23e86a6d9fceb2313536cbafeaeb8fb10","cross_cats_sorted":["cs.ET"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.AR","submitted_at":"2020-08-15T15:49:50Z","title_canon_sha256":"08b6195e5b93ce45c40c67ed373c474373037055a5e0e44f901a3a9f3edd853a"},"schema_version":"1.0","source":{"id":"2008.06741","kind":"arxiv","version":1}},"canonical_sha256":"ac812bd83b87d7c253c92c2833de81b8369623d21af153fc1125e0defbfe6e38","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"ac812bd83b87d7c253c92c2833de81b8369623d21af153fc1125e0defbfe6e38","first_computed_at":"2026-07-05T01:27:31.757828Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T01:27:31.757828Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"owx87aRrKB9kryEqZkZPu5bk9I41yZp+A206aGj05qII679PDgdUGLqvWtpNHTjCJs1w4GxBfai25AylYQrOCA==","signature_status":"signed_v1","signed_at":"2026-07-05T01:27:31.758197Z","signed_message":"canonical_sha256_bytes"},"source_id":"2008.06741","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:eb26ea5ba48b1034c343fc6b313f665fc117ae0024a9da6901213da0df2c37eb","sha256:40e06623735a8ef5623c78d66303fe0ea8f0c1e3354313c4b3657afbee9e4c73"],"state_sha256":"398c6fa0c9b21a83feba55096f8790d90a5235610e02d53e8956258345356858"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"HAMaLrUn7/FUCafQjMsW7zcQ1sgrlYgc5qb12eKWIvdp4nr+tRNrlRGCtrWAZWK/7mZliop3CWX6wzn+Mm/4AQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-07-26T18:22:13.549564Z","bundle_sha256":"8b0fa2e2c7fca6326aa1a97b1bc0ff2e336c2d4d20e08591780e6ccfba79b989"}}