{"as_of":"2026-08-07T05:42:00Z","caps":{"database_statements":6,"inbound":100,"outbound":100},"context_digest":"sha256:5f2066a72f9341841924094ed18659ce2419be89dfea9aa6afd290ce1e6e87a9","coverage":[{"denominator":0,"lane":"reference_resolution","note":"Typed states for the displayed outbound observations.","records_observed":0,"source":"paper_references, paper_reference_links","source_observed_at":null,"state":"measured"},{"denominator":22,"lane":"standing_notices","note":"One-hop event checks from named stored sources.","records_observed":22,"source":"scholarly_work_events, retraction_status_cache","source_observed_at":"2026-08-06T06:34:29.942622+00:00","state":"measured"},{"denominator":22,"lane":"inbound_itemization","note":"Pith citing papers itemized under the disclosed page cap.","records_observed":22,"source":"paper_references, paper_reference_links","source_observed_at":"2026-08-06T17:31:26.627631Z","state":"measured"},{"denominator":1,"lane":"external_citation_measurements","note":"A source-named dated measurement, never combined with another source.","records_observed":0,"source":"pith","source_observed_at":"2026-07-10T06:15:00.866473Z","state":"measured"}],"external_citation_measurements":[],"inbound":[{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"1907.02894","last_updated":"2019-07-05T15:30:04Z","snapshot_observed_at":"2026-07-31T19:37:39.869321Z","submitted_at":"2019-07-05T15:30:04Z","title":"RegDem: Increasing GPU Performance via Shared Memory Register Spilling","version":1},"reference_index":16,"source":"pdf_text","source_observed_at":"2026-05-25T01:57:46.860601Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/1907.02894"},"observation_digest":"sha256:61cb8abf54b85fd4209370f5d384a643b80b0786100835007334581dffc1316d","observation_id":"08440cbe-6057-494a-99de-2578b06cf6e8","resolution":{"observed_at":"2026-05-25T02:00:12.232719Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2205.14135","last_updated":"2022-06-23T17:53:32Z","snapshot_observed_at":"2026-07-06T13:14:48.753329Z","submitted_at":"2022-05-27T17:53:09Z","title":"FlashAttention: Fast and Memory-Efficient Exact Attention with IO-Awareness","version":2},"reference_index":45,"source":"pdf_text","source_observed_at":"2026-05-12T16:22:08.801066Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2205.14135"},"observation_digest":"sha256:7b7c20fde3ec9f606fc2cd7dd2b2381fd1f5dbe24b676d53ff5e67b77e892f06","observation_id":"ec0647a6-d7d5-4af9-bd87-db8223e30404","resolution":{"observed_at":"2026-05-12T16:22:09.024426Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2307.08691","last_updated":"2023-07-17T17:50:36Z","snapshot_observed_at":"2026-07-06T02:11:23.670680Z","submitted_at":"2023-07-17T17:50:36Z","title":"FlashAttention-2: Faster Attention with Better Parallelism and Work Partitioning","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-11T02:39:44.770344Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2307.08691"},"observation_digest":"sha256:a31b3b557bd1a5d073895c2eeb41fea9ddd7af810ca88c507a86e7ebba1b037b","observation_id":"aa9075db-eb78-4889-8848-ac14c9a5c83a","resolution":{"observed_at":"2026-05-11T02:39:44.843582Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-08-06T17:31:26.627631Z","title":"Dissecting the NVIDIA volta GPU architecture via microbenchmarking,","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2507.10789","last_updated":"2025-07-21T19:31:37Z","snapshot_observed_at":"2026-08-06T17:22:44.239952Z","submitted_at":"2025-07-14T20:38:09Z","title":"Dissecting the NVIDIA Blackwell Architecture with Microbenchmarks","version":2},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-06T17:31:26.627631Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2507.10789"},"observation_digest":"sha256:bf8c498f81dd5cab748165f1c159c82fa291f3ee9bc95072260e47cf6aaddb46","observation_id":"3c8887ad-961f-4d04-bde3-65fe63aeaf23","resolution":{"observed_at":"2026-08-06T17:31:26.627631Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2511.17031","last_updated":"2026-05-12T19:37:16Z","snapshot_observed_at":"2026-07-31T06:45:43.083670Z","submitted_at":"2025-11-21T08:12:47Z","title":"Energy Scaling Laws for Diffusion Models: Quantifying Compute in Image Generation","version":2},"reference_index":12,"source":"pdf_text","source_observed_at":"2026-05-17T21:08:23.500137Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2511.17031"},"observation_digest":"sha256:b8d2972d3b72b980de02b471088cca283ba9b249b0e4cc78efbe4dc5cad3d2f0","observation_id":"347d6d97-2ac6-4159-8266-2bd4f0d3c79d","resolution":{"observed_at":"2026-05-17T21:10:16.424075Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2512.00053","last_updated":"2026-06-11T16:28:07Z","snapshot_observed_at":"2026-08-03T21:26:14.912869Z","submitted_at":"2025-11-19T15:57:09Z","title":"Ten-Four: An Open-Source Fused Dot Product Unit for Mixed-Precision GPGPU Tensor Cores","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-17T20:36:28.314778Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2512.00053"},"observation_digest":"sha256:c4806db90d999fa684c16bc25ee33e0d8338b244787904083114c8e1e704a79f","observation_id":"4893eb4a-9994-4704-b426-f98cd40fda77","resolution":{"observed_at":"2026-05-17T20:40:15.016887Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-08-03T21:26:16.082986Z","title":"Scarpazza","venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2512.00053","last_updated":"2026-06-11T16:28:07Z","snapshot_observed_at":"2026-08-03T21:26:14.912869Z","submitted_at":"2025-11-19T15:57:09Z","title":"Ten-Four: An Open-Source Fused Dot Product Unit for Mixed-Precision GPGPU Tensor Cores","version":3},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-08-03T21:26:16.082986Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2512.00053"},"observation_digest":"sha256:574537508017b9e5c3e0f75e9cb3f78ccb0dc2d6c52fb9afe3fdb0a203521d80","observation_id":"07d3f984-48b6-4ee7-9173-ffb4d9b8a021","resolution":{"observed_at":"2026-08-03T21:26:16.082986Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2512.22168","last_updated":"2026-05-12T10:39:26Z","snapshot_observed_at":"2026-08-06T23:53:06.139614Z","submitted_at":"2025-12-17T11:26:58Z","title":"TileLoom: Automatic Dataflow Planning for Tile-Based Languages on Spatial Dataflow Accelerators","version":2},"reference_index":25,"source":"pdf_text","source_observed_at":"2026-05-16T21:55:59.146697Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2512.22168"},"observation_digest":"sha256:0b0bc98898acd9ffeb0ce3cf15821b23feffd7d992e433cf3086663ecafeb22c","observation_id":"feeb1c8e-1287-4588-b2c7-2cd1e043acf2","resolution":{"observed_at":"2026-05-16T21:58:35.792860Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2604.02473","last_updated":"2026-04-02T19:08:47Z","snapshot_observed_at":"2026-07-06T22:51:48.992363Z","submitted_at":"2026-04-02T19:08:47Z","title":"Analyzing Reverse Address Translation Overheads in Multi-GPU Scale-Up Pods","version":1},"reference_index":53,"source":"pdf_text","source_observed_at":"2026-05-13T20:37:49.558450Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2604.02473"},"observation_digest":"sha256:fa65d6c5e675e4d552ad8f7bd3d6187d880fabe91a73693a5becbbf083862432","observation_id":"8c52cd65-df55-4e72-bfcc-89b4451eaf4a","resolution":{"observed_at":"2026-05-13T20:38:14.391040Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2604.15180","last_updated":"2026-04-16T16:03:13Z","snapshot_observed_at":"2026-07-06T23:02:49.302337Z","submitted_at":"2026-04-16T16:03:13Z","title":"AdaSplash-2: Faster Differentiable Sparse Attention","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-05-10T11:19:13.934756Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2604.15180"},"observation_digest":"sha256:812c4deff687d7dc5d543dc8c6112ce19167a9e5337ec90dd7b3c19d0b84e7e2","observation_id":"e4b1609c-55b0-4128-88aa-55981b48059e","resolution":{"observed_at":"2026-05-10T11:20:10.059580Z","resolver_source":"arxiv_id","status":"metadata_mismatch"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2604.17862","last_updated":"2026-04-20T06:19:30Z","snapshot_observed_at":"2026-07-06T23:04:50.935335Z","submitted_at":"2026-04-20T06:19:30Z","title":"M100: An Orchestrated Dataflow Architecture Powering General AI Computing","version":1},"reference_index":34,"source":"pdf_text","source_observed_at":"2026-05-10T05:50:06.986471Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2604.17862"},"observation_digest":"sha256:bc3ed445cee45fe9a1fa77f6e6d36919fee1135787a371f76d57b15a761bca02","observation_id":"a43d099d-e40a-48ea-9626-59cd57442f6c","resolution":{"observed_at":"2026-05-10T05:51:09.774369Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2604.19004","last_updated":"2026-04-21T02:46:07Z","snapshot_observed_at":"2026-07-06T23:05:44.499005Z","submitted_at":"2026-04-21T02:46:07Z","title":"Ocean: Fast Estimation-Based Sparse General Matrix-Matrix Multiplication on GPU","version":1},"reference_index":24,"source":"pdf_text","source_observed_at":"2026-05-10T02:38:08.805896Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2604.19004"},"observation_digest":"sha256:5d68a862b5962842fd6ccc0d7913c4a5f690697ad89528025cd1a720324f3536","observation_id":"e7f2e3c6-71fb-48bb-a415-a1798bcfc562","resolution":{"observed_at":"2026-05-10T02:38:17.318545Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2604.25422","last_updated":"2026-04-29T06:39:29Z","snapshot_observed_at":"2026-07-06T23:11:16.247497Z","submitted_at":"2026-04-28T09:29:53Z","title":"CUDA Kernel Optimization and Counter-Free Performance Analysis for Depthwise Convolution in Cloud Environments","version":2},"reference_index":8,"source":"pdf_text","source_observed_at":"2026-05-07T15:26:41.301014Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2604.25422"},"observation_digest":"sha256:6e82402d8bafd4cf4d688df0287ecf9fb0a58826083d52fe5075ecc141ccac66","observation_id":"6ccbac46-e780-4ab8-8589-cd809d50ee03","resolution":{"observed_at":"2026-05-12T00:26:13.763035Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2604.27808","last_updated":"2026-04-30T12:51:12Z","snapshot_observed_at":"2026-08-02T18:06:42.846535Z","submitted_at":"2026-04-30T12:51:12Z","title":"AME-PIM: Can Memory be Your Next Tensor Accelerator?","version":1},"reference_index":9,"source":"pdf_text","source_observed_at":"2026-05-07T06:37:17.349312Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2604.27808"},"observation_digest":"sha256:58e4a99dcbdab9db831e0e41547d641fcd15fbf74ddeac4feb6393fc47fc4f89","observation_id":"96b08911-3b34-4380-a176-cc0eaaeb7d10","resolution":{"observed_at":"2026-05-12T10:21:28.290656Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2605.04178","last_updated":"2026-05-05T18:17:13Z","snapshot_observed_at":"2026-08-02T20:24:54.544573Z","submitted_at":"2026-05-05T18:17:13Z","title":"Microbenchmark-Driven Analytical Performance Modeling Across Modern GPU Architectures","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-05-08T18:23:44.730845Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2605.04178"},"observation_digest":"sha256:c94cb017d78e5183a01aca7ff05900c0c3f4907c3e66d51ff180dfb4c8152dc7","observation_id":"fd7ff87e-225c-4b4c-8be6-d0bcbb6bf7dd","resolution":{"observed_at":"2026-05-09T06:30:42.803738Z","resolver_source":"arxiv_id","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2606.12765","last_updated":"2026-06-11T00:10:23Z","snapshot_observed_at":"2026-07-06T23:51:35.904251Z","submitted_at":"2026-06-11T00:10:23Z","title":"Rigel: Reverse-Engineering the Metal 4.1 Tensor Compute Path on the Apple M4 Max GPU","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-27T07:14:52.640891Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2606.12765"},"observation_digest":"sha256:f85b07d636d30dc0fc00159abc68b02bb2981b47ba3b07bb8f2346c78c18de06","observation_id":"c0e3aaa3-52b3-471f-8e6d-4845caee57ab","resolution":{"observed_at":"2026-07-03T14:08:21.725116Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2606.22588","last_updated":"2026-06-21T16:50:45Z","snapshot_observed_at":"2026-08-04T23:11:31.471702Z","submitted_at":"2026-06-21T16:50:45Z","title":"Non-Uniform L2 Cache Latency Across the Streaming Multiprocessors of an NVIDIA L40","version":1},"reference_index":3,"source":"pdf_text","source_observed_at":"2026-06-26T09:35:42.284568Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2606.22588"},"observation_digest":"sha256:c79027ef24b79ff41a2773c2470fe6607bcdbb13fa60e18a556dec2b669e9773","observation_id":"ac4c459f-45b7-4f63-99b6-39470febe5da","resolution":{"observed_at":"2026-07-04T09:49:43.792881Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2606.24934","last_updated":"2026-06-22T11:33:12Z","snapshot_observed_at":"2026-08-06T06:46:50.402056Z","submitted_at":"2026-06-22T11:33:12Z","title":"Unprivileged Topology Certificates for Cloud GPU Attestation","version":1},"reference_index":6,"source":"pdf_text","source_observed_at":"2026-06-26T08:01:11.527450Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2606.24934"},"observation_digest":"sha256:2ad903382845c3ee95f2ae1f209a6473486d78118c54c9c9bf916406ceacc122","observation_id":"f3568636-2d93-4e58-922a-85d19dd62d37","resolution":{"observed_at":"2026-07-04T11:19:50.742344Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2606.24934","last_updated":"2026-06-22T11:33:12Z","snapshot_observed_at":"2026-08-06T06:46:50.402056Z","submitted_at":"2026-06-22T11:33:12Z","title":"Unprivileged Topology Certificates for Cloud GPU Attestation","version":1},"reference_index":7,"source":"pdf_text","source_observed_at":"2026-06-26T08:01:11.527450Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2606.24934"},"observation_digest":"sha256:1c08299671ca1c393885e4422b9a0666018aac31f4a82f93b7ac93fc3e883ee9","observation_id":"0d732189-3db8-4618-ab1e-1c4cf82f11a1","resolution":{"observed_at":"2026-06-26T08:49:15.939674Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2606.28565","last_updated":"2026-07-02T09:24:03Z","snapshot_observed_at":"2026-08-03T10:20:30.500902Z","submitted_at":"2026-06-26T19:43:38Z","title":"KernelSight-LM: A Kernel-Level LLM Inference Simulator","version":1},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-06-30T00:48:19.207465Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2606.28565"},"observation_digest":"sha256:6e1b3e7aca49dd36a36eef86900674b528b7b74cb7791a898519fb24937f33d3","observation_id":"50cd40d0-3d4c-4514-b840-8f47131953ec","resolution":{"observed_at":"2026-06-30T00:54:06.291293Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":"1804.06826","doi":"10.48550/arxiv.1804.06826","metadata_source":"pith","pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-07-10T06:15:00.866473Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","venue":"cs.DC","work_id":"8d6b9608-b887-4405-b38c-0e2725997256","year":2018},"citing_paper":{"arxiv_id":"2606.28565","last_updated":"2026-07-02T09:24:03Z","snapshot_observed_at":"2026-08-03T10:20:30.500902Z","submitted_at":"2026-06-26T19:43:38Z","title":"KernelSight-LM: A Kernel-Level LLM Inference Simulator","version":2},"reference_index":19,"source":"pdf_text","source_observed_at":"2026-07-03T23:09:38.092583Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2606.28565"},"observation_digest":"sha256:63ce0109b622035f3b69c43434b58dbe4919477e96b44061a3863f7c437ac43c","observation_id":"e94042d1-9e3d-411b-a0a5-d2b58262e0bb","resolution":{"observed_at":"2026-07-03T23:19:02.223677Z","resolver_source":"local_arxiv","status":"verified_exact"},"standing_notice":{"events":[],"observation":"No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.","reason":null,"source_receipts":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"state":"measured"}},{"citation":{"cited_paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking","version":1},"cited_work":{"arxiv_id":null,"doi":null,"metadata_source":null,"pith_arxiv_id":"1804.06826","snapshot_observed_at":"2026-08-01T11:22:36.766856Z","title":null,"venue":null,"work_id":null,"year":2018},"citing_paper":{"arxiv_id":"2607.19922","last_updated":"2026-07-22T08:53:09Z","snapshot_observed_at":"2026-08-06T04:07:26.205368Z","submitted_at":"2026-07-22T08:53:09Z","title":"DGNA: Dissecting GPU NUMA Architecture through Microbenchmarking and Data Analysis","version":1},"reference_index":20,"source":"pdf_text","source_observed_at":"2026-08-01T11:22:36.766856Z"},"links":{"cited_paper":"/paper/1804.06826","citing_paper":"/paper/2607.19922"},"observation_digest":"sha256:4dc3826af5a9c1eaf748d1500d73145f1f1f4c978f295ebb2dcd2d5848fef8d1","observation_id":"07539891-7b71-4c8d-86ec-12878f1dd380","resolution":{"observed_at":"2026-08-01T11:22:36.766856Z","resolver_source":null,"status":"unresolved"},"standing_notice":{"events":[],"reason":"canonical_work_link_unavailable","source_receipts":[],"state":"unavailable"}}],"links":{"evidence":"/evidence","html":"/paper/1804.06826/citation-record","integrity":"/paper/1804.06826/integrity","json":"/paper/1804.06826/citation-record.json","paper":"/paper/1804.06826"},"outbound":[],"paper":{"arxiv_id":"1804.06826","last_updated":"2018-04-18T17:25:13Z","latest_version":1,"primary_category":"cs.DC","snapshot_observed_at":"2026-08-04T11:46:31.128381Z","submitted_at":"2018-04-18T17:25:13Z","title":"Dissecting the NVIDIA Volta GPU Architecture via Microbenchmarking"},"reference_resolution":{"displayed":0,"state_counts":{"malformed_identifier":0,"metadata_mismatch":0,"parse_uncertain":0,"unresolved":0,"verified_exact":0,"verified_fuzzy":0},"total_outbound_references":0},"refusal":"A citation records a reference. It does not transfer a finding from one paper to another.","schema":"pith.paper-citation-record.v1","standing_sources":[{"observed_at":"2026-08-06T06:34:29.942622+00:00","source":"crossref"},{"observed_at":"2026-08-06T06:34:23.284952+00:00","source":"retraction_watch"}],"thesis":"As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 22 inbound Pith citation observations for arXiv:1804.06826."}