SF Compute 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.
SF Compute Alternatives
Compute Engine (IaaS), a platform from Google that allows organizations to create and manage cloud-based virtual machines, is an infrastructure as a services (IaaS).
Computing infrastructure in predefined sizes or custom machine shapes to accelerate cloud transformation. General purpose machines (E2, N1,N2,N2D) offer a good compromise between price and performance. Compute optimized machines (C2) offer high-end performance vCPUs for compute-intensive workloads. Memory optimized (M2) systems offer the highest amount of memory and are ideal for in-memory database applications. Accelerator optimized machines (A2) are based on A100 GPUs, and are designed for high-demanding applications. Integrate Compute services with other Google Cloud Services, such as AI/ML or data analytics. Reservations can help you ensure that your applications will have the capacity needed as they scale. You can save money by running Compute using the sustained-use discount, and you can even save more when you use the committed-use discount.
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Servers.com by Nexcess delivers hybrid bare metal cloud hosting solutions that give businesses greater control over their infrastructure while maintaining the flexibility needed to grow. Its portfolio includes Scalable Bare Metal for on-demand capacity, Enterprise Bare Metal for customized deployments, AI Compute for GPU-powered workloads, and Managed Kubernetes for containerized applications. The platform is built to accommodate organizations that require reliable performance, security, and predictable infrastructure management. Through a network of data centers across multiple continents, customers can deploy services closer to their users and minimize latency. Businesses in industries such as gaming, financial services, advertising technology, streaming, SaaS, and Web3 rely on the platform to support high-demand operations. The infrastructure is designed to handle traffic spikes, intensive computing requirements, and geographically distributed workloads. Advanced networking capabilities and direct connectivity options help optimize application responsiveness and uptime. Organizations can combine different infrastructure offerings to create environments that align with their operational and budget requirements. By providing scalable and customizable bare metal solutions, Servers.com helps businesses maintain performance while adapting to changing market demands.
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OneSource Cloud
OneSource Cloud specializes in the design, construction, and management of sovereign AI infrastructure tailored for organizations in regulated sectors that cannot utilize public cloud for sensitive operations, such as healthcare and life sciences, financial services, government and defense, energy, legal, and research sectors.
Our services include the provision of dedicated GPU compute as a managed offering, encompassing cluster design, hardware acquisition, data center colocation, deployment, and ongoing maintenance. The clusters are equipped with NVIDIA GPUs connected via InfiniBand for efficient multi-node training and inference, complemented by high-performance storage solutions and dedicated private networking. Each client benefits from a unique, isolated environment that ensures their data and models do not share hardware with other users, safeguarding their confidentiality.
Our managed services extend to capacity planning, provisioning, workload scheduling, system monitoring, patching, and customer support. Each environment is meticulously configured to meet the client’s compliance standards, including regulations such as NIST 800-171 and specific data residency requirements.
Currently, we operate over 20,000 GPUs across more than 96 data centers, ensuring robust support for our clients' complex needs in an increasingly data-sensitive landscape. This extensive infrastructure positions us as a leader in providing secure AI solutions for organizations facing strict regulatory demands.
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Nebius
A robust platform optimized for training is equipped with NVIDIA® H100 Tensor Core GPUs, offering competitive pricing and personalized support. Designed to handle extensive machine learning workloads, it allows for efficient multihost training across thousands of H100 GPUs interconnected via the latest InfiniBand network, achieving speeds of up to 3.2Tb/s per host. Users benefit from significant cost savings, with at least a 50% reduction in GPU compute expenses compared to leading public cloud services*, and additional savings are available through GPU reservations and bulk purchases. To facilitate a smooth transition, we promise dedicated engineering support that guarantees effective platform integration while optimizing your infrastructure and deploying Kubernetes. Our fully managed Kubernetes service streamlines the deployment, scaling, and management of machine learning frameworks, enabling multi-node GPU training with ease. Additionally, our Marketplace features a variety of machine learning libraries, applications, frameworks, and tools designed to enhance your model training experience. New users can take advantage of a complimentary one-month trial period, ensuring they can explore the platform's capabilities effortlessly. This combination of performance and support makes it an ideal choice for organizations looking to elevate their machine learning initiatives.
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Pricing
Pricing Starts At:
$1.48 per hour
Integrations
Company Details
Company:
SF Compute
Headquarters:
United States
Website:
sfcompute.com
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Web-Based
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Online Support
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