In a landmark advancement for AI infrastructure, Cloudian has eliminated the traditional bottleneck between object storage and GPU computing. Working closely with NVIDIA, we’ve engineered the industry’s first GPUDirect for Object Storage solution—a breakthrough that enables GPUs to directly access object storage data through RDMA, completely bypassing both CPU overhead and HTTP protocol limitations.
As AI models grow exponentially and storage demands surge—with analysts forecasting a staggering 10X increase in storage requirements over the next decade—traditional infrastructure is reaching its breaking point. Cloudian’s revolutionary solution delivers:
- INDUSTRY FIRST: NVIDIA GPUDirect for Object Storage integration
- UNPRECEDENTED SPEED: 200+ GB/s sustained throughput (3X faster than non-RDMA flash)
- RESOURCE OPTIMIZATION: 45% reduction in GPU server CPU utilization
But the real story goes even further than breakthrough performance and efficiency metrics – it’s about transforming how organizations architect their AI infrastructure.
AI Drives New Storage Challenges
AI workflows have become increasingly complex, involving multiple steps from raw data ingestion through training to deployment. Traditional approaches require organizations to maintain separate storage tiers and constantly migrate data between them:
- Raw data repositories holding petabytes of information
- High-performance file systems for AI training
- Storage for checkpoints and trained models
- Vector databases for inference
- Query logs for compliance
Each storage silo adds cost, complexity, and delays to AI workflows.
Cloudian Consolidates AI Data
The Cloudian AI data lake consolidates AI data with a centralized, S3-compatible repository that seamlessly integrates with leading AI and machine learning frameworks. Through its native S3 API, Cloudian enables direct connectivity with popular AI tools including TensorFlow for deep learning, PyTorch for machine learning research and development, and Apache Spark for large-scale data processing. The platform also supports data streaming via Kafka and high-performance analytics through Apache Arrow, allowing organizations to build end-to-end AI workflows while maintaining data in a unified storage environment. This S3 API compatibility ensures AI teams can leverage familiar tools and frameworks while accessing the scalability and performance benefits of Cloudian’s object storage architecture.
Eliminate the Costly File Layer
Cloudian’s integration with NVIDIA GPUDirect Storage technology enables a fundamental simplification: direct data access between object storage and GPU memory.
This means:
- Elimination of expensive file storage layers
- No more complex data migrations between tiers
- A single, unified data lake for the entire AI workflow
- Direct, high-performance data access for GPU processing
How It Works
The technical innovation centers on creating a direct data path from object storage to GPUs:
- Data requests are initiated via the S3 API
- Instead of routing through system memory and CPU, data moves directly to GPU memory
- RDMA enables parallel transfer from multiple Cloudian nodes
Note: No kernel level modifications are required, maintaining security
Why Object Storage for AI?
As AI models grow exponentially more complex (consider the jump from GPT-3 to GPT-4), organizations need storage infrastructure that can scale accordingly. Object storage provides unique advantages:
- Limitless scalability to exabyte levels
- Enterprise-grade security for sensitive training data
- Superior economics at massive scale
- Simplified management through a single namespace
- Rich metadata support for enhanced data discovery
Real-World Impact
This breakthrough drives simplification and cost reduction, making the upcoming large-scale models accessible and affordable. This is particularly significant for organizations in:
- Financial services processing market data
- Healthcare analyzing genomic datasets
- Autonomous vehicle development
- Manufacturing optimization
- Retail recommendation systems
- Any organization implementing generative AI or RAG (Retrieval-Augmented Generation)
Future-Proofing Your Infrastructure for AI
As AI continues to transform industries, storage architecture decisions made today will impact organizations for years to come. Traditional storage silos weren’t built for AI training workloads, which require seamless access to vast amounts of data.
The path forward is clear: consolidate data into a scalable, AI-ready S3 API data lake that can directly feed GPU infrastructure. This approach not only solves today’s AI storage challenges but creates a foundation for future innovation.
To learn more about transforming your AI infrastructure with Cloudian’s GPUDirect for Object Storage capability, contact your Cloudian representative or get a free trial today.
