NVIDIA and Cloudera Expand Partnership to Accelerate Enterprise Digital Transformation NVIDIA and Cloudera have expanded their partnership to provide more capabilities for GPU, machine learning, and AI, in order to accelerate enterprise digital transformation. Cloudera continues to support NVIDIA's advanced AI technology, offering top-notch applications for enterprise digital transformation. The company's support for NVIDIA's key technologies in public and private cloud environments aims to help customers efficiently build and deploy AI applications. The new phase of collaboration between Cloudera and NVIDIA, utilizing NVIDIA GPUs, will enhance data engineering, machine learning, and AI with next-generation GPU capabilities. This partnership expansion comes at a time when NVIDIA is affected by US restrictions on AI chips in China, where the market accounts for 25% of the company's chip revenue. Committed to Accelerating AI and Machine Learning Workloads Cloudera Machine Learning (CML) is the leading service of Cloudera's data platform, empowering enterprises to create their own AI applications. By leveraging proprietary data assets to create secure and accurate responses, the company helps customers unlock the potential of open-source large language models (LLM). When it comes to the data platform, Anthony Behan, Cloudera's representative, told AI Magazine, "Cloudera's data platform helps drive innovation" and provides "choices designed for the data services lifecycle, from edge to AI, whether it's streaming large amounts of data or deploying and monitoring next-generation AI and ML models." Cloudera's CML service now focuses on supporting NVIDIA H100 GPUs in public clouds and data centers. This next-generation acceleration aims to enhance Cloudera's data platform, enabling faster insights and more efficient generative AI workloads. The result may be the ability to fine-tune models on larger datasets and host larger models in production. The enterprise-level security and governance of CML mean that businesses can harness the power of NVIDIA GPUs without compromising data security. NVIDIA Partnership Continues to Strengthen Global AI Operations Another key benefit is that users can utilize GPU-accelerated data pipelines in Cloudera's private cloud. Through Cloudera Data Engineering, users can build production-ready data pipelines from various sources. By integrating NVIDIA Spark RAPIDS into CDE, users can accelerate extract, transform, and load (ETL) workloads without the need for refactoring. Existing Spark ETL applications can seamlessly benefit from GPU acceleration, achieving up to 7 times overall speedup and up to 16 times speedup for selected queries. This allows NVIDIA customers to better leverage GPUs in their upstream data processing pipelines. The goal is to increase the utilization of these GPUs and provide higher return on investment. "GPU acceleration applies to all stages of the AI application lifecycle - from data pipeline ingestion and management, data preparation, model development and tuning, to inference and model serving," said Priyank Patel, Vice President of Product Management at Cloudera. "NVIDIA's leadership in AI computing perfectly complements Cloudera's leadership in data management, providing customers with a complete solution to harness the power of GPUs throughout the AI lifecycle." NVIDIA is committed to expanding data centers to help enterprises stay ahead in generative AI development. This week, it also announced a partnership with Dell Technologies as a "blueprint" for the next generation of large-scale AI clusters. Michael Dell, CEO of Dell Technologies, stated that their new design will "help meet the needs of LLM and GenAI applications, creating one of the fastest AI systems in the world," equipped with "2048 NVIDIA H100 Tensor Core GPUs, 256 Dell PowerEdge XE9680 AI servers, and powerful Spectrum-X Ethernet AI networks."