{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2019:T235RXOSKWUSD7IXOEDOCPU6WZ","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":"1f9d37e6904bcebb053eff975a5e8dcec069eddf958025f7b6ab2c07c55e3910","cross_cats_sorted":["cs.AR","cs.DC","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-08T13:45:33Z","title_canon_sha256":"12077a5adf6ae410ee0e922020ffac0cbffa705f72559681cd7898b5293699ca"},"schema_version":"1.0","source":{"id":"1908.03072","kind":"arxiv","version":2}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"1908.03072","created_at":"2026-07-04T23:59:34Z"},{"alias_kind":"arxiv_version","alias_value":"1908.03072v2","created_at":"2026-07-04T23:59:34Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.1908.03072","created_at":"2026-07-04T23:59:34Z"},{"alias_kind":"pith_short_12","alias_value":"T235RXOSKWUS","created_at":"2026-07-04T23:59:34Z"},{"alias_kind":"pith_short_16","alias_value":"T235RXOSKWUSD7IX","created_at":"2026-07-04T23:59:34Z"},{"alias_kind":"pith_short_8","alias_value":"T235RXOS","created_at":"2026-07-04T23:59:34Z"}],"graph_snapshots":[{"event_id":"sha256:60d2fca10366c69ba06444c78e3e81b20ba26d9b5ad5069b9b366ce8fe76dcdd","target":"graph","created_at":"2026-07-04T23:59:34Z","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/1908.03072/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Recent studies from several hyperscalars pinpoint to embedding layers as the most memory-intensive deep learning (DL) algorithm being deployed in today's datacenters. This paper addresses the memory capacity and bandwidth challenges of embedding layers and the associated tensor operations. We present our vertically integrated hardware/software co-design, which includes a custom DIMM module enhanced with near-data processing cores tailored for DL tensor operations. These custom DIMMs are populated inside a GPU-centric system interconnect as a remote memory pool, allowing GPUs to utilize for sca","authors_text":"Minsoo Rhu, Youngeun Kwon, Yunjae Lee","cross_cats":["cs.AR","cs.DC","cs.NE"],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-08T13:45:33Z","title":"TensorDIMM: A Practical Near-Memory Processing Architecture for Embeddings and Tensor Operations in Deep Learning"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"1908.03072","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:d351879ab168447dadb82495aea894456640bd4e0d656f53d9f2356f225a4bc5","target":"record","created_at":"2026-07-04T23:59:34Z","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":"1f9d37e6904bcebb053eff975a5e8dcec069eddf958025f7b6ab2c07c55e3910","cross_cats_sorted":["cs.AR","cs.DC","cs.NE"],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.LG","submitted_at":"2019-08-08T13:45:33Z","title_canon_sha256":"12077a5adf6ae410ee0e922020ffac0cbffa705f72559681cd7898b5293699ca"},"schema_version":"1.0","source":{"id":"1908.03072","kind":"arxiv","version":2}},"canonical_sha256":"9eb7d8ddd255a921fd177106e13e9eb65f9d528a46476675a81775386f0faa22","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"9eb7d8ddd255a921fd177106e13e9eb65f9d528a46476675a81775386f0faa22","first_computed_at":"2026-07-04T23:59:34.429287Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-04T23:59:34.429287Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rhqxRjTRWJJ8HtIltpuJKBw43uWTtrBDK7COIEFzhh9DXaGL+ahUGncgi1yRJZI9kuTpjdiAhP8j2TvnFkSCAw==","signature_status":"signed_v1","signed_at":"2026-07-04T23:59:34.429738Z","signed_message":"canonical_sha256_bytes"},"source_id":"1908.03072","source_kind":"arxiv","source_version":2}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:d351879ab168447dadb82495aea894456640bd4e0d656f53d9f2356f225a4bc5","sha256:60d2fca10366c69ba06444c78e3e81b20ba26d9b5ad5069b9b366ce8fe76dcdd"],"state_sha256":"0fe41227eca772c8f68d767168f752cd89616cffdbc18995d628eb7bd41b94a5"}