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Description
Create a robust NVMe over Fabrics high-performance shared storage solution with MayaScale that allows for the integration of directly attached NVMe resources into a unified storage pool. This solution enables the flexible provisioning of NVMe namespaces to clients who require high performance with minimal latency. After usage, clients have the option to return NVMe storage back to the shared pool, eliminating issues associated with over-provisioning or unutilized NVMe storage typical of direct-attached setups. The network-agnostic architecture employs RDMA for on-premises deployments and standard TCP for cloud environments, ensuring versatility. Clients can access true NVMe devices using a conventional NVMe driver stack, negating the need for any proprietary drivers. You can easily configure and implement NVMe over Fabrics SAN infrastructure at rack scale in your data center by aggregating diverse NVMe devices through RDMA-compatible connections, such as ROCE, iWARP, or Infiniband. Furthermore, even in public cloud settings, users can harness the benefits of NVMe over Fabrics via the standard TCP/IP protocol, which eliminates the requirement for specialized RDMA hardware or SRIOV virtualization. This innovative approach optimizes resource utilization while maintaining high performance across various deployment scenarios.
Description
SF Compute serves as a marketplace platform providing on-demand access to extensive GPU clusters, enabling users to rent high-performance computing resources by the hour without the need for long-term commitments or hefty upfront investments. Users have the flexibility to select either virtual machine nodes or Kubernetes clusters equipped with InfiniBand for rapid data transfer, allowing them to determine the number of GPUs, desired duration, and start time according to their specific requirements. The platform offers adaptable "buy blocks" of computing power; for instance, clients can request a set of 256 NVIDIA H100 GPUs for a three-day period at a predetermined hourly price, or they can adjust their resource allocation depending on their budgetary constraints. When it comes to Kubernetes clusters, deployment is incredibly swift, taking approximately half a second, while virtual machines require around five minutes to become operational. Furthermore, SF Compute includes substantial storage options, featuring over 1.5 TB of NVMe and upwards of 1 TB of RAM, and notably, there are no fees for data transfers in or out, meaning users incur no costs for data movement. The underlying architecture of SF Compute effectively conceals the physical infrastructure, leveraging a real-time spot market and a dynamic scheduling system to optimize resource allocation. This setup not only enhances usability but also maximizes efficiency for users looking to scale their computing needs.
API Access
Has API
API Access
Has API
Integrations
AWS Marketplace
Amazon
Amazon RDS
Google Cloud Platform
Kubernetes
Liquid AI
Microsoft Azure
MongoDB
MySQL Workbench
NVIDIA virtual GPU
Integrations
AWS Marketplace
Amazon
Amazon RDS
Google Cloud Platform
Kubernetes
Liquid AI
Microsoft Azure
MongoDB
MySQL Workbench
NVIDIA virtual GPU
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
$1.48 per hour
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
ZettaLane Systems
Founded
2018
Website
www.zettalane.com/maya-nvmeof-linux-rdma-tcp.html
Vendor Details
Company Name
SF Compute
Country
United States
Website
sfcompute.com