Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

Average Ratings 0 Ratings

Total
ease
features
design
support

No User Reviews. Be the first to provide a review:

Write a Review

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 No 

API Access

Has API No 

Screenshots View All

Screenshots View All

Integrations

AWS Marketplace Yes 
Amazon Yes 
Amazon RDS Yes 
Google Cloud Platform Yes 
Kubernetes No 
Liquid AI No 
Microsoft Azure Yes 
MongoDB Yes 
MySQL Workbench Yes 
NVIDIA virtual GPU No 
Oracle Cloud Infrastructure FastConnect Yes 
Phind No 
Red Hat CloudForms Yes 
VMware Cloud No 

Integrations

AWS Marketplace No 
Amazon No 
Amazon RDS No 
Google Cloud Platform No 
Kubernetes Yes 
Liquid AI Yes 
Microsoft Azure No 
MongoDB No 
MySQL Workbench No 
NVIDIA virtual GPU Yes 
Oracle Cloud Infrastructure FastConnect No 
Phind Yes 
Red Hat CloudForms No 
VMware Cloud Yes 

Pricing Details

No price information available.
Free Trial No 
Free Version No 

Pricing Details

$1.48 per hour
Free Trial No 
Free Version No 

Deployment

Web-Based Yes 
On-Premises Yes 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Deployment

Web-Based Yes 
On-Premises No 
iPhone App No 
iPad App No 
Android App No 
Windows No 
Mac No 
Linux No 
Chromebook No 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Customer Support

Business Hours Yes 
Live Rep (24/7) No 
Online Support Yes 

Types of Training

Training Docs Yes 
Webinars Yes 
Live Training (Online) No 
In Person Yes 

Types of Training

Training Docs Yes 
Webinars No 
Live Training (Online) No 
In Person No 

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

Product Features

Product Features

Alternatives

xiRAID Reviews

xiRAID

Xinnor

Alternatives

NVMesh Reviews

NVMesh

Excelero
NVIDIA DOCA Reviews

NVIDIA DOCA

NVIDIA