{"bundle_type":"pith_open_graph_bundle","bundle_version":"1.0","pith_number":"pith:2023:UXBSMMS3NUIF6R2FBIGJIPUH6U","short_pith_number":"pith:UXBSMMS3","canonical_record":{"source":{"id":"2312.12621","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-12-19T21:56:42Z","cross_cats_sorted":[],"title_canon_sha256":"c1a2dc61794ce31a93df58529d22d24226fbab2c2ebb36e8b9c949edef3eb2f8","abstract_canon_sha256":"e1eda8a52a8b83ee8a2def4c528db7f5e034a8a29a1a6a495655684757949b0c"},"schema_version":"1.0"},"canonical_sha256":"a5c326325b6d105f47450a0c943e87f52d41870b12d238294ef3f2cd2fda3146","source":{"kind":"arxiv","id":"2312.12621","version":1},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.12621","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"2312.12621v1","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.12621","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"UXBSMMS3NUIF","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"pith_short_16","alias_value":"UXBSMMS3NUIF6R2F","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"pith_short_8","alias_value":"UXBSMMS3","created_at":"2026-07-05T07:26:23Z"}],"events":[{"event_type":"record_created","subject_pith_number":"pith:2023:UXBSMMS3NUIF6R2FBIGJIPUH6U","target":"record","payload":{"canonical_record":{"source":{"id":"2312.12621","kind":"arxiv","version":1},"metadata":{"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-12-19T21:56:42Z","cross_cats_sorted":[],"title_canon_sha256":"c1a2dc61794ce31a93df58529d22d24226fbab2c2ebb36e8b9c949edef3eb2f8","abstract_canon_sha256":"e1eda8a52a8b83ee8a2def4c528db7f5e034a8a29a1a6a495655684757949b0c"},"schema_version":"1.0"},"canonical_sha256":"a5c326325b6d105f47450a0c943e87f52d41870b12d238294ef3f2cd2fda3146","receipt":{"kind":"pith_receipt","key_id":"pith-v1-2026-05","algorithm":"ed25519","signed_at":"2026-07-05T07:26:23.845019Z","signature_b64":"rbnb2BWHe0rtpZyqVuIeJGJBYEYWM8K/N0NFqu0aQoySMWTkiByQ4DhHqwBwxh8xLUPZYw4fXbcLSN6CYFwUDQ==","signed_message":"canonical_sha256_bytes","builder_version":"pith-number-builder-2026-05-17-v1","receipt_version":"0.3","canonical_sha256":"a5c326325b6d105f47450a0c943e87f52d41870b12d238294ef3f2cd2fda3146","last_reissued_at":"2026-07-05T07:26:23.844580Z","signature_status":"signed_v1","first_computed_at":"2026-07-05T07:26:23.844580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54"},"source_kind":"arxiv","source_id":"2312.12621","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":"2026-07-05T07:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zoWOQVgTpjg7xmud+mUPrctP0jgjR/lQst5TvRPsCa3IEuSncjKiZP/VEV+7TOMoGHk6iQQUfVFLkl6f+WLsCQ==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T03:01:50.699369Z"},"content_sha256":"934c4e34eb7164f2039b65cf285acf293de7d0280181a1af1acee1eb2509b072","schema_version":"1.0","event_id":"sha256:934c4e34eb7164f2039b65cf285acf293de7d0280181a1af1acee1eb2509b072"},{"event_type":"graph_snapshot","subject_pith_number":"pith:2023:UXBSMMS3NUIF6R2FBIGJIPUH6U","target":"graph","payload":{"graph_snapshot":{"paper":{"title":"Blox: A Modular Toolkit for Deep Learning Schedulers","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","headline":"","cross_cats":[],"primary_cat":"cs.DC","authors_text":"Amar Phanishayee, Saurabh Agarwal, Shivaram Venkataraman","submitted_at":"2023-12-19T21:56:42Z","abstract_excerpt":"Deep Learning (DL) workloads have rapidly increased in popularity in enterprise clusters and several new cluster schedulers have been proposed in recent years to support these workloads. With rapidly evolving DL workloads, it is challenging to quickly prototype and compare scheduling policies across workloads. Further, as prior systems target different aspects of scheduling (resource allocation, placement, elasticity etc.), it is also challenging to combine these techniques and understand the overall benefits. To address these challenges we propose Blox, a modular toolkit which allows develope"},"claims":{"count":0,"items":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.12621","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/2312.12621/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":"2026-07-05T07:26:23Z","supersedes":[],"prev_event":null,"signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"zenz9JSmT8jMdAwGNwQOM+1T/nVvzYhmUWfOUH2o01fjLS24qfLeYwnUJqVvZg4yifGJSCWBUaHAzz1mjFdTBA==","signed_message":"open_graph_event_sha256_bytes","signed_at":"2026-08-12T03:01:50.700230Z"},"content_sha256":"90ef8d9a83b13b7283b02c04e7fc98552e02896e2f3974a7d7441b825224eaed","schema_version":"1.0","event_id":"sha256:90ef8d9a83b13b7283b02c04e7fc98552e02896e2f3974a7d7441b825224eaed"}],"timestamp_proofs":[],"mirror_hints":[{"mirror_type":"https","name":"Pith Resolver","base_url":"https://pith.science","bundle_url":"https://pith.science/pith/UXBSMMS3NUIF6R2FBIGJIPUH6U/bundle.json","state_url":"https://pith.science/pith/UXBSMMS3NUIF6R2FBIGJIPUH6U/state.json","well_known_bundle_url":"https://pith.science/.well-known/pith/UXBSMMS3NUIF6R2FBIGJIPUH6U/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":"2026-08-12T03:01:50Z","links":{"resolver":"https://pith.science/pith/UXBSMMS3NUIF6R2FBIGJIPUH6U","bundle":"https://pith.science/pith/UXBSMMS3NUIF6R2FBIGJIPUH6U/bundle.json","state":"https://pith.science/pith/UXBSMMS3NUIF6R2FBIGJIPUH6U/state.json","well_known_bundle":"https://pith.science/.well-known/pith/UXBSMMS3NUIF6R2FBIGJIPUH6U/bundle.json"},"state":{"state_type":"pith_open_graph_state","state_version":"1.0","pith_number":"pith:2023:UXBSMMS3NUIF6R2FBIGJIPUH6U","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":"e1eda8a52a8b83ee8a2def4c528db7f5e034a8a29a1a6a495655684757949b0c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-12-19T21:56:42Z","title_canon_sha256":"c1a2dc61794ce31a93df58529d22d24226fbab2c2ebb36e8b9c949edef3eb2f8"},"schema_version":"1.0","source":{"id":"2312.12621","kind":"arxiv","version":1}},"source_aliases":[{"alias_kind":"arxiv","alias_value":"2312.12621","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"arxiv_version","alias_value":"2312.12621v1","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"doi","alias_value":"10.48550/arxiv.2312.12621","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"pith_short_12","alias_value":"UXBSMMS3NUIF","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"pith_short_16","alias_value":"UXBSMMS3NUIF6R2F","created_at":"2026-07-05T07:26:23Z"},{"alias_kind":"pith_short_8","alias_value":"UXBSMMS3","created_at":"2026-07-05T07:26:23Z"}],"graph_snapshots":[{"event_id":"sha256:90ef8d9a83b13b7283b02c04e7fc98552e02896e2f3974a7d7441b825224eaed","target":"graph","created_at":"2026-07-05T07:26:23Z","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/2312.12621/integrity.json","findings":[],"snapshot_sha256":"c28c3603d3b5d939e8dc4c7e95fa8dfce3d595e45f758748cecf8e644a296938","summary":{"advisory":0,"by_detector":{},"critical":0,"informational":0}},"paper":{"abstract_excerpt":"Deep Learning (DL) workloads have rapidly increased in popularity in enterprise clusters and several new cluster schedulers have been proposed in recent years to support these workloads. With rapidly evolving DL workloads, it is challenging to quickly prototype and compare scheduling policies across workloads. Further, as prior systems target different aspects of scheduling (resource allocation, placement, elasticity etc.), it is also challenging to combine these techniques and understand the overall benefits. To address these challenges we propose Blox, a modular toolkit which allows develope","authors_text":"Amar Phanishayee, Saurabh Agarwal, Shivaram Venkataraman","cross_cats":[],"headline":"","license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-12-19T21:56:42Z","title":"Blox: A Modular Toolkit for Deep Learning Schedulers"},"references":{"count":0,"internal_anchors":0,"resolved_work":0,"sample":[],"snapshot_sha256":"258153158e38e3291e3d48162225fcdb2d5a3ed65a07baac614ab91432fd4f57"},"source":{"id":"2312.12621","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":"sha256:934c4e34eb7164f2039b65cf285acf293de7d0280181a1af1acee1eb2509b072","target":"record","created_at":"2026-07-05T07:26:23Z","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":"e1eda8a52a8b83ee8a2def4c528db7f5e034a8a29a1a6a495655684757949b0c","cross_cats_sorted":[],"license":"http://arxiv.org/licenses/nonexclusive-distrib/1.0/","primary_cat":"cs.DC","submitted_at":"2023-12-19T21:56:42Z","title_canon_sha256":"c1a2dc61794ce31a93df58529d22d24226fbab2c2ebb36e8b9c949edef3eb2f8"},"schema_version":"1.0","source":{"id":"2312.12621","kind":"arxiv","version":1}},"canonical_sha256":"a5c326325b6d105f47450a0c943e87f52d41870b12d238294ef3f2cd2fda3146","receipt":{"algorithm":"ed25519","builder_version":"pith-number-builder-2026-05-17-v1","canonical_sha256":"a5c326325b6d105f47450a0c943e87f52d41870b12d238294ef3f2cd2fda3146","first_computed_at":"2026-07-05T07:26:23.844580Z","key_id":"pith-v1-2026-05","kind":"pith_receipt","last_reissued_at":"2026-07-05T07:26:23.844580Z","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","receipt_version":"0.3","signature_b64":"rbnb2BWHe0rtpZyqVuIeJGJBYEYWM8K/N0NFqu0aQoySMWTkiByQ4DhHqwBwxh8xLUPZYw4fXbcLSN6CYFwUDQ==","signature_status":"signed_v1","signed_at":"2026-07-05T07:26:23.845019Z","signed_message":"canonical_sha256_bytes"},"source_id":"2312.12621","source_kind":"arxiv","source_version":1}}},"equivocations":[],"invalid_events":[],"applied_event_ids":["sha256:934c4e34eb7164f2039b65cf285acf293de7d0280181a1af1acee1eb2509b072","sha256:90ef8d9a83b13b7283b02c04e7fc98552e02896e2f3974a7d7441b825224eaed"],"state_sha256":"9c0b953236b6555395e5452ffa6659027c7dab91eb461edaa30bd179b26de9a7"},"bundle_signature":{"signature_status":"signed_v1","algorithm":"ed25519","key_id":"pith-v1-2026-05","public_key_fingerprint":"8d4b5ee74e4693bcd1df2446408b0d54","signature_b64":"D/vF3cL1NJGSZo7hbc53ompRQ/V1Mwrqg6ds0I4wZRZssgVdUgePvqYnNuT3YfAjQGeNWKZSJVNpjwL7mQOwAQ==","signed_message":"bundle_sha256_bytes","signed_at":"2026-08-12T03:01:50.705486Z","bundle_sha256":"1d37662a2495b2aeb83327739a8ddc09283d08c19c9408a75f1293081ac5148d"}}