Related Products
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About
Horovod was originally developed by Uber to make distributed deep learning fast and easy to use, bringing model training time down from days and weeks to hours and minutes. With Horovod, an existing training script can be scaled up to run on hundreds of GPUs in just a few lines of Python code. Horovod can be installed on-premise or run out-of-the-box in cloud platforms, including AWS, Azure, and Databricks. Horovod can additionally run on top of Apache Spark, making it possible to unify data processing and model training into a single pipeline. Once Horovod has been configured, the same infrastructure can be used to train models with any framework, making it easy to switch between TensorFlow, PyTorch, MXNet, and future frameworks as machine learning tech stacks continue to evolve.
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About
Zipher is an autonomous optimization platform specifically designed to improve the performance and cost efficiency of Databricks workloads by eliminating manual tuning and resource management and continuously adjusting clusters in real time. It uses proprietary machine learning models and the only Spark-aware scaler that actively learns and profiles workloads to adjust cluster resources, select optimal configurations for every job run, and dynamically tune settings like hardware, Spark configs, and availability zones to maximize efficiency and cut waste. Zipher continuously monitors evolving workloads to adapt configurations, optimize scheduling, and allocate shared compute resources to meet SLAs, while providing detailed cost visibility that breaks down Databricks and cloud provider costs so teams can identify key cost drivers. It integrates seamlessly with major cloud service providers including AWS, Azure, and Google Cloud and works with common orchestration and IaC tools.
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Platforms Supported
Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook
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Audience
Developers in need of a powerful Development Framework solution
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Audience
Data engineering and cloud infrastructure teams who run Databricks workloads and want to automate performance tuning and cost optimization with minimal manual effort
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Support
Phone Support
24/7 Live Support
Online
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Support
Phone Support
24/7 Live Support
Online
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API
Offers API
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API
Offers API
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Screenshots and Videos |
Screenshots and Videos |
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Pricing
Free
Free Version
Free Trial
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Pricing
No information available.
Free Version
Free Trial
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Reviews/
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Reviews/
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Training
Documentation
Webinars
Live Online
In Person
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Training
Documentation
Webinars
Live Online
In Person
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Company InformationHorovod
horovod.ai/
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Company InformationZipher
Founded: 2023
United States
zipher.cloud/
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Categories |
Categories |
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Integrations
Amazon Web Services (AWS)
Microsoft Azure
Apache Airflow
Azure Data Factory
Azure Databricks
Databricks Data Intelligence Platform
Flyte
Google Cloud Platform
Keras
MXNet
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Integrations
Amazon Web Services (AWS)
Microsoft Azure
Apache Airflow
Azure Data Factory
Azure Databricks
Databricks Data Intelligence Platform
Flyte
Google Cloud Platform
Keras
MXNet
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