The Alluxio Data Platform powers many of the most critical data-driven applications in the world.
Uniquely positioned between compute and storage, Alluxio provides a single pane of glass for enterprises to manage data and AI workloads across diverse infrastructure environments with ease. Alluxio Data Platform has two product offerings – Alluxio Enterprise Data and Alluxio Enterprise AI. Choose the product offering based on your workload’s needs, and enjoy epic performance, seamless data access, simplified data engineering, and cost savings.
Data and AI Infrastructure Challenges
Trusted by the World’s Leading Organizations
“Alluxio has proven to be a valuable solution in addressing the data access challenges of hybrid cloud for Comcast. It has provided us with faster data access, reduced egress costs, and streamlined data management, resulting in more efficient and effective data value creation for the organization.”
“At Uber, we run Alluxio to accelerate all sorts of business-critical analytics queries at a large scale. Alluxio provides consistent performance in our big data processing use cases. As compute-storage separation continues to be the trend along with containerization in big data, we believe a unified layer …”
“With the introduction of Alluxio, we are seeing better performance, increased manageability, and lowered costs. We plan to implement Alluxio as the default cross-region data access in all clusters in the main data lake.”
End-to-End Machine Learning Pipeline Demo
Alluxio’s Senior Solutions Engineer Tarik Bennett walks through a short end-to-end machine learning pipeline demo with Alluxio integrated. See how Alluxio can be provisioned or mounted as a local folder for the PyTorch dataloader, delivering 90%+ GPU utilization and dramatically accelerating data loading times.
1. Data Preparation
2. Setting up the Model
3. Setting up the PyTorch Profiler
4. Model Training
PyTorch Model Training & Performance Tuning
Solving the Data Loading Challenge for Machine Learning with Alluxio
Efficient Data Access Strategies For Large-scale AI
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