Alluxio, developer of open source cloud data orchestration software, has announced the integration of RAPIDS Accelerator for Apache Spark 3.0 with the Alluxio Data Orchestration Platform to accelerate data access on NVIDIA accelerated computing clusters for computation of both analytics and AI pipelines.
According to the companies, validation testing of the integration for caching of large datasets and data availability for NVIDIA GPU processing showed 2x faster acceleration for a data analytics and business intelligence workload. At the same time, NVIDIA GPU clusters with Alluxio demonstrated 70% better return on investment (ROI) compared to CPU clusters.
GPU-based processing drives higher data access throughput than a CPU-based cluster. With the separation of processing clusters for analytics and AI from data storage systems, accelerating data access allows for cost savings on agile business intelligence and data science workloads.
“With the advances made from the unrivaled processing power of NVIDIA’s software and hardware, the bottleneck for users is now storage access throughout the data pipeline,” said Haoyuan Li, founder and CEO, Alluxio. “From this integration, users now benefit from the separation of processing clusters for analytics and AI from data storage systems, accelerating data access within milliseconds to make critical decisions, find efficiencies, lower cost, and improve customer experience.”
“Accelerating data processing compute speeds means that data also needs to be accessed more quickly by data science and AI applications so that the entire pipeline works in harmony,” added Scott McClellan, senior director, data science product group, NVIDIA. “Alluxio’s integration of RAPIDS for Apache Spark, combined with the accelerated computing power of NVIDIA GPUs, means that Alluxio Data Orchestration customers will be able to boost the efficiency of their analytics and AI workloads without any code changes.”
Key highlights of the Alluxio with RAPIDS Accelerator for Apache Spark 3.0 integration, include:
- Data locality for I/O acceleration. Alluxio manages local storage resources on the GPU cluster and provides a high performance distributed cache to accelerate data access from a remote storage cluster.
- No code changes for ease of use. To use RAPIDS on GPU enabled clusters and Alluxio for storage access, no code changes are required. This makes adoption of the solution pain free for customers looking to migrate from their existing software stack.
- API flexibility. Multiple data access APIs are supported to enable the use of the most appropriate processing framework for each step of the data pipeline. The distributed cache is shared to allow for high performance even when data moves from one framework to another.
RAPIDS Accelerator for Apache Spark 3.0 with Alluxio Data Orchestration Platform integration is available now.
For more information, go to www.alluxio.io.