Improve GPU utilisation
Allocate computing resources more precisely across different users and workloads, helping to reduce idle capacity and get more from valuable GPU infrastructure.
Get more from your AI infrastructure
with our Technology Partner
Optimised AI infrastructure, intelligently operated
Powerful AI infrastructure delivers more value when computing resources are easy to access, share and manage.
AlloComp designs and delivers the physical infrastructure, from GPU systems and storage to networking, power and cooling.
Lablup’s Backend.AI provides the operating and orchestration platform that helps organisations allocate resources, manage users and run AI workloads across shared infrastructure.
Together, AlloComp and Lablup can help you improve GPU utilisation, support more users and scale your AI environment with confidence.
Backend.AI brings resource allocation, workload scheduling, user access, monitoring and infrastructure management into one environment.
It supports AI experimentation, model training and inference across infrastructure ranging from individual GPU systems to multi-node clusters.
Backend.AI can be deployed on-premises, in the cloud or across hybrid environments, giving organisations the flexibility to choose where their AI workloads and data should run.
The value of AI infrastructure is not defined by the hardware alone, but by how effectively people can access and use it.
Make every resource count
Simplify resource management
Manage users, quotas, workload priorities and access policies from a common platform, with visibility into how infrastructure is being used.
Make infrastructure easier to share
Provide controlled access to shared computing resources across teams, departments, research groups or customers.
Retain control of AI and data
Run workloads on-premises or within a trusted regional facility, with support for private and air-gapped environments where required.
Support different AI workloads
Provide one environment for experimentation, model training, parallel computing and inference services.
Scale as demand grows
Start with an individual GPU system or small cluster and develop towards a larger shared platform without changing the fundamental way resources are accessed and managed.
DGX-Ready Software Partner
As NVIDIA DGX-Ready Software, Backend.AI delivers seamless operation with NVIDIA DGX systems and Grace Blackwell. Container-level GPU virtualization combined with the Sokovan orchestrator optimizes utilization for AI and HPC workloads, in various scales.
Infrastructure and orchestration, designed together
AlloComp can incorporate Backend.AI into the infrastructure design process, ensuring that compute, storage, networking and deployment architecture are aligned with the organisation’s users, workloads, data and plans for future growth.
Workload and infrastructure assessment
GPU workstations, servers and clusters
Compute, storage and networking integration
Power, cooling and facility planning
On-premises, colocation and hybrid design
Independent hardware selection
Deployment coordination and lifecycle support
AI infrastructure operating platform
Controlled access to shared computing resources
Workload scheduling and orchestration
Fine-grained resource allocation, user access, quotas and governance
Infrastructure usage and health monitoring
Support for different accelerator technologies
Together, AlloComp and Lablup help organisations get the most from their AI infrastructure by improving GPU utilisation and making powerful computing resources easier to access, share and manage across users, teams and workloads.
Where can
add value?
Enterprise AI development platform
Support experimentation, model training and inference across AI and data science teams, with controlled access, workload scheduling and resource allocation.
Industry accelerator hub
Give start-ups and innovation teams controlled access to shared AI infrastructure without requiring each organisation to procure and manage its own dedicated GPU systems.
Shared university AI platform
Give students, researchers and multiple faculties controlled access to centrally managed GPU infrastructure.
Resources can be allocated across different groups and workloads while the institution maintains visibility and control.
AI factory or regional GPU service
Allocate computing infrastructure across customers, projects and teams while monitoring usage and supporting growth in users, workloads and nodes.
Sovereign and private AI
Operate sensitive workloads within your own infrastructure or a trusted regional facility, helping maintain control of data, systems and access.
Planning shared AI infrastructure?
You do not have to begin with a large cluster
AlloComp can help you start with the infrastructure that meets today’s requirements, whether that is an individual GPU system, departmental server or small cluster.
Backend.AI provides a consistent operating layer that can support wider access and more complex resource management as users and workloads grow.
