Samsung SmartSSD CSD EB1 Computational Storage Drive 4TB

The Samsung SmartSSD CSD EB1 represents a paradigm shift in enterprise storage architecture by embedding a Xilinx Kintex UltraScale+ FPGA directly within a 4TB NVMe SSD form factor. This computational storage device offloads data-intensive workloads—particularly compression, filtering, and pattern matching—from host CPUs to the storage device itself, dramatically reducing data movement across the PCIe fabric and network interfaces. The architecture combines high-speed NAND flash with dedicated reconfigurable computing, enabling real-time data transformation at line rate before data traverses to system memory or network boundaries.

Designed explicitly for AI/ML pipelines and telco edge computing environments, the CSD EB1 accelerates bottlenecked operations including feature extraction, data preprocessing, and lossy/lossless compression in streaming analytics and video surveillance workloads. The FPGA substrate supports custom algorithmic implementations deployed via OpenAccel framework and vendor-agnostic programming models, allowing enterprises to tailor data reduction logic to specific domain requirements without modifying application code.

This novel computational storage category gained rapid enterprise traction in 2024-2025 as organizations confront data explosion in edge intelligence and cloud-native ML deployments. The CSD EB1 addresses the critical bottleneck of PCIe and network saturation by performing intelligent data pruning and feature extraction at microsecond latencies, achieving significant TCO improvements in bandwidth-constrained environments.

Ideal for

• Real-time video analytics pipelines in smart city and surveillance deployments, compressing and filtering frames before transmission to edge gateways or cloud ingestion
• High-frequency financial data preprocessing, filtering market data feeds and extracting relevant signals at the storage layer to reduce downstream compute load
• Genomic sequence analysis and bioinformatics workflows, performing pattern matching and data deduplication on multi-terabyte datasets during ingestion phases
• Time-series IoT sensor data reduction in industrial telemetry, applying statistical filtering and anomaly detection before persisting to data lakes
• Machine learning feature engineering for inference pipelines, accelerating data normalization, encoding, and dimensionality reduction at storage speeds
• Telco network traffic analysis and deep packet inspection, offloading signature matching and protocol parsing to reduce CPU utilization on edge nodes

Technical specifications

Available from Omnixon Global. Submit an RFQ and our team will confirm configuration and availability for your order.