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Category: Whitepaper

  • GPU Cloud Platform Guide featuring key fundamentals for GPUaaS vendors, including GPU multi-tenancy, infrastructure flexibility, and service provider strategies.

    GPU Cloud Platform Guide

    GPU CLOUD PLATFORM GUIDE

    Five fundamentals to discuss with your
    GPU cloud platform provider

    Traditional service providers need to evolve their offering from IaaS to GPUaaS. Neoclouds need to build the platform right, first time, to ensure a successful future. The GPU orchestration platform / control plane you choose is critical.

    This guide helps you assess GPU cloud platform features against the success criteria of multi-tenant service providers (neoclouds, CSPs, hosts, telcos).

    GPU Cloud Platform Guide cover featuring title "Five fundamentals to discuss with your GPU cloud platform vendor," with a grid background and graphical elements illustrating GPU multi-tenancy and service provider concepts.

    How to use this guide

    Each section of the guide provides questions you can ask platform vendors about five fundamental feature categories that determine those success criteria:

    Success criteria:

    Control of service design, deployment model, branding, access, location

    Flexible pricing – ability to price GPUaaS tiers for specific customer segments

    Inference ready – enabling GPU to flex and scale like cloud for variable workloads

    Ecosystem integration – ability to slot into existing provider workloads and tools

    Profitability – optimal utilization, minimal operational overheads, maximum margins

    Simple UX for admins and customers – easy management and consumption

    GPU cloud platform fundamentals:

    GPU cloud deployment model

    GPU multi-tenancy

    GPU utilization

    GPU metering + billing

    End-user experience

    Download now

  • Neocloud Survival Guide cover featuring the title "How to 5x your GPU revenue + margin," emphasizing profitability challenges in the GPU market, with grid background and logo elements.

    Neocloud Survival Guide

    NEOCLOUD SURVIVAL GUIDE

    How to 5x your GPU revenue + margin

    Most Neoclouds have a problem: it’s hard to see a future where the business is actually profitable.

    Some companies in this space have already folded. Many more are struggling to make the numbers add up, because super-high GPU capex + low utilization + price erosion + commoditization = little or no ROI.

    Cash flow chart over five years showing total revenue of $3.31M, total net income of -$2.36M, average margin of -71.3%, and total cash flow of -$0.36M, illustrating financial challenges for GPUaaS businesses.

    Let’s fix that.

    Everyone agrees that AI is the future, but how do you build an infrastructure business for AI that will still be in business next year, let alone in five years’ time?

    Get your copy of the Neocloud Survival Guide, and learn how to 5x your GPU revenue and margin.

    Neocloud Survival Guide cover featuring "How to 5x your GPU revenue + margin," with contents list including profitability issues and ROI strategies, emphasizing GPU as a Service solutions.

    Contents

    The Neocloud profitability problem

    Rethink the madness: change 4 things

    Your new game plan

    5x ROI illustrated

    Next steps

  • Software-Defined GPU whitepaper cover, highlighting GPUaaS benefits for service providers and AI hosting, with title and key topics on virtualization.

    Software-Defined GPU

    Software-Defined GPU

    Making GPUaaS work for service providers and the mainstream AI hosting market

    Software-Defined GPU whitepaper cover, highlighting GPUaaS for service providers and AI hosting, featuring title and key points on GPU virtualization methods.

    You’re not virtualizing GPU the wrong way – you’re just not doing it the optimal way for maximum utilization, flexibility and ROI from your hardware investments.

    This high-level whitepaper explains the difference between GPU virtualization and true GPU as a Service (GPUaaS).

    It explores the benefits and drawbacks of GPU passthrough, instancing and slicing, and explains why service provider GPUaaS requires a different approach – especially for AI inference workloads. To get your free copy, just fill out the form.

    Contents

    Why GPU virtualization ≠ GPUaaS

    What does service provider GPUaaS need?

    Software-Defined GPU requirements

    hosted·ai GPUaaS architecture

    hosted·ai hyperconverged platform

    Standalone GPUaaS with hosted·ai

    More information