|
gptkbp:instance_of
|
gptkb:Performance_Monitoring
|
|
gptkbp:available_on
|
Publicly
|
|
gptkbp:competes_with
|
Other benchmarks
|
|
gptkbp:composed_of
|
Multiple workloads
|
|
gptkbp:developed_by
|
gptkb:MLCommons
gptkb:AI_technology
|
|
gptkbp:encourages
|
Collaboration in AI research
|
|
gptkbp:evaluates
|
Hardware and software systems
|
|
gptkbp:first_released
|
gptkb:2018
|
|
gptkbp:focuses_on
|
gptkb:Deep_Learning
|
|
gptkbp:has_category
|
Closed, Open, and HPC
|
|
gptkbp:has_participants
|
Global organizations
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
MLPerf Training
|
|
gptkbp:includes
|
Training benchmarks
|
|
gptkbp:is_adopted_by
|
Cloud providers
|
|
gptkbp:is_collaborative_with
|
Industry partnerships
Community-driven
Open community
|
|
gptkbp:is_evaluated_by
|
Scalability
Performance and efficiency
Resource utilization
Independent reviewers
|
|
gptkbp:is_focused_on
|
Performance optimization
|
|
gptkbp:is_influential_in
|
AI development
AI benchmarking
|
|
gptkbp:is_open_source
|
gptkb:True
|
|
gptkbp:is_part_of
|
gptkb:ecosystem
gptkb:MLPerf
|
|
gptkbp:is_promoted_by
|
gptkb:MLCommons
|
|
gptkbp:is_recognized_by
|
Research institutions
Industry leaders
|
|
gptkbp:is_supported_by
|
Open-source tools
Major tech companies
Hardware vendors
|
|
gptkbp:is_updated_by
|
Regularly
|
|
gptkbp:is_used_for
|
Comparative analysis
Performance comparison
|
|
gptkbp:is_utilized_by
|
Data scientists
|
|
gptkbp:is_utilized_in
|
Academic research
|
|
gptkbp:latest_version
|
gptkb:2.0
|
|
gptkbp:measures
|
Machine Learning performance
|
|
gptkbp:performance
|
gptkb:AI_technology
AI workloads
Training efficiency
Training tasks
|
|
gptkbp:provides
|
Performance metrics
Standardized results
|
|
gptkbp:reported_by
|
gptkb:Annual_reports
Research papers
|
|
gptkbp:supports
|
Multiple frameworks
|
|
gptkbp:used_by
|
gptkb:Industry
gptkb:researchers
|
|
gptkbp:bfsParent
|
gptkb:MLPerf
|
|
gptkbp:bfsLayer
|
6
|