Cloudera has partnered with NVIDIA to introduce native GPU acceleration for Apache Spark 4.1 in Cloudera Data Engineering, powered by NVIDIA’s CUDA-X library, cuDF.

The new capability is designed to help enterprises accelerate data processing and prepare AI-ready data faster without rewriting existing PySpark or SQL code. By using NVIDIA GPUs, organisations can speed up large-scale Spark workloads while reducing cloud infrastructure costs.

Cloudera said the GPU-accelerated environment can deliver up to 4x faster performance compared with traditional CPU infrastructure. The solution is designed to support faster ETL and data preparation, shorter compute runtimes and more efficient analytics and AI workflows.

The integration will be available through Cloudera Anywhere Cloud, enabling organisations to use GPU acceleration across public, private and sovereign clouds, as well as on-premises and edge environments.

The solution also provides built-in deployment without manual driver configuration while retaining enterprise security and governance through Cloudera’s Unified Data Fabric.

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The partnership addresses the growing infrastructure demands of enterprise AI. According to Cloudera’s Great Re-Architecture Survey, 84% of respondents said AI workloads have increased infrastructure costs.

By accelerating Spark pipelines without requiring changes to existing applications, Cloudera and NVIDIA aim to help data teams transform raw data into trusted, model-ready information faster while improving cost efficiency. 

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