GPU-accelerated Block Device
Enables low cost high-density data storage
Create DAS arrays with hundreds of parallel storage devices
High performance even with massive degradation
GPU computing on storage nodes with minimal data movement
Compatible with all Linux filesystems and applications
Say Hello to NSULATE™
RAID was standardized in 1993 in an era of single-core computing. For exascale computing, RAID is obsolete and an obstacle to higher performance and resilience. NSULATE revolutionises the role of the storage controller by replacing a fixed-function RAID controller with a powerful general-purpose GPU. Using a GPU as a storage controller inserts an enormous amount of general purpose processing power directly into the storage pipeline, enabling modern HPC storage appliances to deliver unprecedented speed, scale, security, storage efficiency and intelligence in real-time.
NSULATE offers extreme resilience. It uses a GPU to generate huge parity calculations to enable automatic data recovery on scales impossible with a RAID card or a CPU. As a Linux block device, it is compatible with existing Linux filesystems and applications.
While traditional RAID and erasure coding solutions support parity calculations up to 8, NSULATE supports up to 128 parity. Stable I/O throughput can be maintained even while experiencing dozens of simultaneous device failures and corruption events across an array.
NSULATE is compatible with Nyriad's NCRYPT™ suite of GPU-accelerated, NIST compliant cryptographic algorithms. NCRYPT includes real-time blockchain generation APIs that can apply any appropriate combination of encryption, hashing and cryptographic signature generation modules to all storage transactions. Integrated with NSULATE, NCRYPT enables all storage transactions to be encrypted, auditable for correctness/integrity and signed by any number of authenticated trust contracts. A Merkle DAG can be generated in real-time and linked to a private or public blockchain ledger for independent verification and proof of data integrity.
NSULATE can further reduce infrastructure requirements by sharing GPU resources for compute and storage on the same physical node. Storage nodes can be configured to double as processing nodes for I/O bound computing steps. This further accelerates big data and HPC processing and storage access by reducing the distance between GPU resources and storage.