|
gptkbp:instance_of
|
gptkb:Performance_Monitoring
|
|
gptkbp:aims_to
|
encourage collaboration
provide fair comparisons
drive innovation in ML hardware
|
|
gptkbp:annual_event
|
gptkb:MLPerf_conference
|
|
gptkbp:developed_by
|
gptkb:MLCommons
|
|
gptkbp:first_released
|
gptkb:2018
|
|
gptkbp:focuses_on
|
machine learning performance
|
|
gptkbp:has_category
|
open division
closed division
cloud division
edge division
hpc division
|
|
gptkbp:has_documentation
|
guidelines for submissions
benchmarking methodologies
result reporting standards
|
|
gptkbp:has_impact_on
|
gptkb:AI_technology
software optimization
hardware development
|
|
gptkbp:has_part
|
gptkb:MLPerf_Cloud
gptkb:MLPerf_Edge
gptkb:MLPerf_HPC
gptkb:MLPerf_Inference
gptkb:MLPerf_Training
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
MLPerf
|
|
gptkbp:includes
|
inference benchmarks
training benchmarks
|
|
gptkbp:is_available_in
|
multiple languages
|
|
gptkbp:is_collaborative_with
|
open to contributions
|
|
gptkbp:is_evaluated_by
|
independent auditors
|
|
gptkbp:is_influenced_by
|
software frameworks
advancements in AI
hardware capabilities
|
|
gptkbp:is_part_of
|
gptkb:MLCommons_initiative
|
|
gptkbp:is_recognized_by
|
academic institutions
industry leaders
|
|
gptkbp:is_supported_by
|
gptkb:Alibaba
gptkb:Qualcomm
gptkb:Samsung
gptkb:Xilinx
gptkb:Baidu
gptkb:IBM
gptkb:Microsoft
gptkb:Oracle
gptkb:Amazon
gptkb:Google
gptkb:Nokia
gptkb:Cisco
gptkb:Dell
gptkb:Huawei
gptkb:Intel
gptkb:AMD
gptkb:NVIDIA
gptkb:Salesforce
gptkb:Tencent
gptkb:Facebook
Arm
major tech companies
|
|
gptkbp:is_updated_by
|
regularly
|
|
gptkbp:is_used_by
|
gptkb:researchers
industry professionals
|
|
gptkbp:provides
|
standardized performance metrics
|
|
gptkbp:releases_results
|
quarterly
|
|
gptkbp:bfsParent
|
gptkb:Tensor_Processing_Units_(TPUs)
gptkb:NVIDIA_DGX_A100
gptkb:NVIDIA_A100
gptkb:TPU_v2
gptkb:NVIDIA_P100_GPU
|
|
gptkbp:bfsLayer
|
5
|