Horovod

E760433
distributed deep learning framework open-source software

Horovod is an open-source distributed deep learning framework designed to make training models across multiple GPUs and machines fast and easy.

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Statements (48)

Predicate Object
instanceOf distributed deep learning framework ⓘ
open-source software ⓘ
category deep learning software ⓘ
distributed computing ⓘ
machine learning infrastructure ⓘ
designGoal make distributed deep learning easy to use ⓘ
make distributed deep learning fast ⓘ
developedBy Uber NERFINISHED ⓘ
feature fault-tolerant training with elastic mode ⓘ
hierarchical allreduce ⓘ
integration with Apache Spark ⓘ
mixed-precision training support ⓘ
ring-allreduce algorithm for gradient averaging ⓘ
timeline profiling for performance debugging ⓘ
initialReleaseDate 2017 ⓘ
keyOperation allgather ⓘ
allreduce ⓘ
broadcast ⓘ
license Apache License 2.0 ⓘ
notableUser Uber NERFINISHED ⓘ
optimizedFor multi-GPU training ⓘ
multi-node training ⓘ
parallelismType data parallelism ⓘ
primaryUse distributed training of deep learning models ⓘ
programmingLanguage C++ ⓘ
CUDA NERFINISHED ⓘ
Python ⓘ
repository https://github.com/horovod/horovod ⓘ
supportsFramework Apache MXNet NERFINISHED ⓘ
Keras NERFINISHED ⓘ
PyTorch NERFINISHED ⓘ
TensorFlow NERFINISHED ⓘ
XGBoost NERFINISHED ⓘ
supportsHardware CPU ⓘ
GPU ⓘ
multi-GPU systems ⓘ
multi-node clusters ⓘ
supportsLanguage Apache MXNet NERFINISHED ⓘ
Keras NERFINISHED ⓘ
PyTorch NERFINISHED ⓘ
Spark ML NERFINISHED ⓘ
TensorFlow NERFINISHED ⓘ
supportsPlatform cloud environments ⓘ
on-premise clusters ⓘ
usesCommunicationBackend Gloo NERFINISHED ⓘ
MPI NERFINISHED ⓘ
NCCL NERFINISHED ⓘ
website https://horovod.ai ⓘ

Referenced by (1)

Full triples — surface form annotated when it differs from this entity's canonical label.

NCCL → usedBy → Horovod ⓘ