|
gptkbp:instanceOf
|
gptkb:software
|
|
gptkbp:announced
|
2023
|
|
gptkbp:category
|
gptkb:compilation_album
gptkb:software
machine learning infrastructure
runtime environment
|
|
gptkbp:developedBy
|
gptkb:Apple
gptkb:Google
gptkb:Microsoft
gptkb:Hugging_Face
gptkb:AMD
gptkb:Alibaba
gptkb:NVIDIA
gptkb:Amazon_Web_Services
gptkb:Intel
gptkb:Meta
gptkb:Arm
gptkb:Graphcore
gptkb:Stability_AI
|
|
gptkbp:domain
|
gptkb:artificial_intelligence
gptkb:machine_learning
|
|
gptkbp:enables
|
performance optimization
cross-framework ML model deployment
hardware portability
|
|
gptkbp:feature
|
modular design
community-driven development
open governance
pluggable backends
|
|
gptkbp:hasComponent
|
gptkb:IREE
XLA
PJRT
StableHLO
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
OpenXLA
|
|
gptkbp:license
|
gptkb:Apache_License_2.0
|
|
gptkbp:purpose
|
accelerate machine learning workloads
optimize ML model performance
|
|
gptkbp:relatedTo
|
gptkb:MLIR
gptkb:ONNX
TVM
|
|
gptkbp:repository
|
https://github.com/openxla
|
|
gptkbp:supports
|
gptkb:TensorFlow
gptkb:JAX
gptkb:PyTorch
multiple hardware backends
|
|
gptkbp:usedBy
|
academia
enterprises
AI researchers
cloud providers
hardware vendors
ML engineers
|
|
gptkbp:website
|
https://openxla.org
|
|
gptkbp:bfsParent
|
gptkb:IREE
gptkb:Multi-Level_Intermediate_Representation
|
|
gptkbp:bfsLayer
|
7
|