As rendering technologies develop, rapidly reducing rendering costs and improving efficiency are the paramount factors in raising competitiveness. Enterprises offering rendering services are perplexed by the following challenges in using on-premises traditional data centers:
▪ High initial investment: A render farm (compute clusters) is considered an asset-heavy profile requiring large initial investment and a long build period. This approach is unable to yield the flexibility modern enterprises require.
▪ Low resource utilization: Bulk of resources remain idle during light service load periods and become strained during peak hours and events.
▪ High maintenance costs: Enterprises usually need to invest heavily in the maintenance of the render farm. Manual maintenance is tedious and error-prone. Enterprise cannot focus its IT personnel on business innovations because they are always putting out fires in the layout.
▪ High OPEX: On-premises equipment rooms entail enormous fees, including the construction costs, utilities, and system management fees.
Cloud-based rendering services have become an inevitable trend. Compute operations can be performed and data can be stored on the cloud. With on-cloud resources, customers can order up the services they need whenever they need them while alleviating themselves from the constraints of an asset-heavy profile and cumbersome maintenance workload. Customers can now focus their energies on revenue-generating items and value creation.
Difficult in Predicting Needed Resources and High Costs of Self-Built Centers
The rendering services fluctuate drastically. When the services are idle, resources are wasted; during service peaks, resources become insufficient. In addition, constructing a local render farm requires a large number of IT resources, incurring high costs.
A single rendering task takes dozens of hours on general-purpose servers. When the render farm is overloaded, the task will take much more time.
Various Storage Specifications
The servers in a render farm need to access the shared storage concurrently, so the shared storage bandwidth must be high. In addition, storing large volumes of data requires low-cost storage.
Inefficient Delivery and Complicated O&M
The construction period is long, the installation and deployment are complicated, and O&M as well as capacity expansion are difficult. Monitoring and alarm management involve large quantity of physical servers. These types of mashups are complicated to manage and consume a lot of manpower.
The rendering service is one of the important application fields of high performance computing. The rendering and compute requirements vary with the service scenario. Huawei HPC solution provides end-to-end compute services for enterprises.
Flexible High-Performance Cloud Server
Fat nodes of dozens of specifications, such as ECS and BMS compute instances, are supported to meet the various compute to memory ratio requirements of HPC applications.
BMSs provide excellent compute performance as the dedicated physical servers. The service provides the optimal performance without any virtualization loss. Users can use the management console to automatically provision BMSs, thereby meeting HPC service requirements for on-demand elasticity.
Distributed Scalable Block Storage Service
Block Storage Service (BSS) is based on the distributed architecture and flexibly scalable. Users can attach EVS disks to an ECS as required to provide storage space for computing and storage nodes. Each disk provides up to 32 TB capacity, 30,000 IOPS, and 1 TB/s throughput.
Extended Capabilities and Flexible Choice in Billing
The solution provides APIs and SDKs for customers to flexibly manage the compute, storage, and network resources on the cloud. Data Express Service (DES) allows customers to import and export data to and from the cloud. Customers can choose the billing model most suitable to them; with pay-per-use convenience so they only pay for the resources they need or they can sign up for a subscription package for even bigger savings.
Provides high-performance, reliable, and easy-to-use compute, storage, and network services to meet performance requirements in various rendering scenarios, shortening the rendering period and increasing the benefit for the enterprise.
Industry-leading performance, providing 100GE InfiniBand compute networks; local 3.2 TB enterprise-level SSD disks, local cache disks with the largest capacity in cloud services; fat node with 96 cores and 2 TB memory
Various Deployment Modes
Support for both ECSs and BMSs, meeting various deployment requirements
Based on OpenStack
Comprehensive security protection at seven layers (access, transmission, infrastructure, network, virtualization, data, and management), three-layer Anti-DDoS traffic cleaning, secure network isolation provided by VPC, and access permission control by IAM