📝 Guest post: Burst Compute: Scaling Workloads Across Thousands of GPUs in the Cloud, Instantly*
Was this email forwarded to you? Sign up here The smartest companies are evolving toward more flexible, on-demand cloud infrastructure using a technique called burst compute, which provides enterprises with accessible, efficient, and cost-effective computing. What is Burst Compute?Burst compute is a use case that requires GPUs to be spun up to run workloads as needed, and spun down when they finish. Examples include batch simulations that can be run in parallel across thousands of GPUs, online (or batch) inference that scales GPUs up and down in response to end-user demand, and VFX rendering to deliver projects on a short timeline. Unlike the traditional definition of cloud bursting, which directs overflow traffic onto the public cloud to avoid interruptions in service, bursting on modern, specialized cloud infrastructure – like CoreWeave – allows companies who need high-performance NVIDIA GPUs to scale up and down across hundreds or thousands of GPUs instantly – saving up to 80% at a critical time when every IT department needs to batten down the hatches. Accessing On-Demand GPUs at Scale on Legacy Cloud Infrastructure Has Been Virtually ImpossibleWhether you’re consistently deploying workloads across thousands of GPUs or just need a few instances, there’s an increasing challenge in the industry: it is extremely difficult to access the compute you need, when you need it, on legacy cloud infrastructure. When you are able to access compute, legacy providers often charge exorbitant fees for ingress/egress, which can be debilitating for many clients. Businesses that rely on on-demand cloud infrastructure, like AI start-ups, VFX and animation studios, biotech companies, and Metaverse platforms, often need to scale up and down across hundreds or thousands of GPUs for short periods of time, but too often find themselves stuck without this option. The result? Paying for idle compute cycles you don’t need, to make sure you can access it when you do. CoreWeave Cloud is designed to address availability constraints, making it dead simple to scale up when your workloads require it, and scale down when they don’t. We care deeply about making sure our clients have practical access to scale, and built our Kubernetes-native infrastructure to make sure you can consume it efficiently. The solution? Scaling seamlessly across the industry's broadest range of NVIDIA GPUs on CoreWeave Cloud, only paying for the compute you need, when you need it. And zero charges for ingress or egress. Thanks to integrations with open-source Kubernetes projects – like Knative, Keda, and ArgoWorkflows, and industry standard software – like Determined.AI, Scalable Pixel Streaming, Zeet and Deadline, our clients regularly:
Modern Infrastructure for the Most Intensive, Scalable WorkloadsCoreWeave’s Kubernetes native environment is purpose-built for large-scale NVIDIA GPU-accelerated workloads. Each component of our infrastructure has been carefully designed to help clients access both the volume and the variety of compute they need in real-time, with responsive auto-scaling across thousands of GPUs. For clients, this means dramatically faster spin-up times, no delays when running parallel jobs across different geographies, teams and models, and zero spend on idle time. Thanks to container image caching and specialized schedulers, workloads on CoreWeave can be up and running in as little as 5 seconds. Lightning-fast spin-up times mean you can scale elastically and access massive amounts of resources in the same cluster, instantly. Examples of Compute-Intensive Workloads We SupportMachine LearningCoreWeave is optimized for natural language processing and speech AI, utilizing containerized workloads with streaming responses and context aware load-balancing. On CoreWeave, you can deploy inference with a single YAML.
VFX, Animation & RenderingAccelerate artist workflows by eliminating the render queue, leveraging container auto-scaling across virtually unlimited render capacity.
Drug DiscoveryRun thousands of NVIDIA GPUs for parallel simulations, leveraging our Kubernetes orchestration tools such as Argo Workflows to run and manage the lifecycle of parallel processing pipelines.
Metaverse & Pixel StreamingWhether your Unreal Engine experience runs in VMs or containers, lightning-fast spin-up times and responsive auto-scaling mean you can serve users in real-time, rather than spinning up and paying for idle compute.
No Charges for Ingress / EgressAnother prohibiting factor to running burst compute workloads on other cloud providers is data transfer, which carries alarmingly high rates for ingress and egress. Anytime you transfer data into the cloud, move data between regions, access your data remotely or send something you're storing to a client, you are charged what is effectively a tax per GB of data you move. These costs are prohibitively expensive and can lock clients into unfavorable contracts. At CoreWeave, we don’t charge for ingress or egress. The cost of bursting on CoreWeave Cloud is limited to the compute you use and the storage volumes you allocate. That's it. Solve Tomorrow’s Problems TodayAt CoreWeave, you won’t be forced into a box. We meet clients where they are, and provide economics that empowers them to scale. Our modern infrastructure helps clients reach maximum efficiency, saving between 50-80% compared with legacy clouds. We’d love to help you too! Get started by speaking with one of our engineers. *This post was written by the CoreWeave Team. We thank CoreWeave for their ongoing support of TheSequence.You’re on the free list for TheSequence Scope and TheSequence Chat. For the full experience, become a paying subscriber to TheSequence Edge. Trusted by thousands of subscribers from the leading AI labs and universities. |
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