Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
As of 6 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2301.00407.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-06T06:34:29.942622+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-03T11:05:03.061977Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-01T15:15:48.677216Z
Reference resolution
0 of 0 outbound references displayed
- verified exact0
- verified fuzzy0
- unresolved0
- parse uncertain0
- malformed identifier0
- metadata mismatch0
External citation measurements
No source-named external measurement is stored.
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 1324f576-8505-47b0-8e09-734a45f925c5 · inbound
Performance Isolation for Inference Processes in Edge GPU Systems cites this paper.
Performance Isolation for Inference Processes in Edge GPU Systems MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T11:05:03.061977Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1e1882bb-5b59-433d-b2be-b48b67713898 · inbound
A comprehensive evaluation of spatial co-execution on GPUs using MPS and MIG technologies cites this paper.
A comprehensive evaluation of spatial co-execution on GPUs using MPS and MIG technologies MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T20:16:08.221456Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 9cf7d007-1d80-4bca-adcc-4d4688fd800d · inbound
CompPow: A Case for Component-level GPU Power Management cites this paper.
CompPow: A Case for Component-level GPU Power Management MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
Reference 38
- Resolution
- verified exact
- arxiv_id, observed 2026-05-22T03:24:34.139142Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation 58bc68fe-143d-4ccc-9187-e5ce2d02c503 · inbound
SMART-MIG: A Learning Framework for Scalable and Energy-Efficient GPU Scheduling cites this paper.
SMART-MIG: A Learning Framework for Scalable and Energy-Efficient GPU Scheduling MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
Reference 25
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-06-30T16:14:54.103042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.
Observation e6ac6fdd-1063-4c44-a3d2-3d8b581dd312 · inbound
Energy-Aware Scheduling for Serverless LLM Serving on Shared GPUs cites this paper.
Energy-Aware Scheduling for Serverless LLM Serving on Shared GPUs MIGPerf: A Comprehensive Benchmark for Deep Learning Training and Inference Workloads on Multi-Instance GPUs
Reference 65
- Resolution
- verified exact
- arxiv_id, observed 2026-07-01T15:15:48.678652Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-06T06:34:29.942622+00:00.