Organize CPU, GPU and memory into schedulable resource pools.
Organize CPU, GPU and memory into schedulable resource pools.
05 / Virtualization, cloud and computing
GPU and high-performance computing
Build a scalable and verifiable enterprise HPC platform around GPU/CPU nodes, high-speed interconnects, shared storage, job scheduling, software environments, cooling and power.
Starting pointWorkloads / resources / dependencies
ArchitectureCompute / storage / network
Delivery resultValidation / handover / operations
Technical advantages
HPC advantage comes from coordinated compute, data paths and scheduling
GPU/CPU nodes only become an effective computing platform when high-speed interconnects, shared storage, job queues, software environments and operating records are designed together.
Allocate resources by job requirements, queues and business priority.
Allocate resources by job requirements, queues and business priority.
Match compute nodes, shared storage and network paths to actual data throughput.
Match compute nodes, shared storage and network paths to actual data throughput.
Keep job, resource, version, fault and result records for continuous optimization.
Keep job, resource, version, fault and result records for continuous optimization.
Technical boundary
Compute / storage / network / identity
Delivery focus
Assess / pilot / verify / handover
01
Define the high-performance computing scope before selecting products
Start with workloads, dependencies, access boundaries and operating requirements, then decide the platform shape.
Workloads and dependencies
Identify workloads, service dependencies, data paths and peak demand.
Access and ownership
Clarify identities, permissions, operating roles and support boundaries.
Capacity baseline
Confirm compute, storage, network and growth assumptions before delivery.
02
Connect the high-performance computing architecture layers
The platform is reliable only when compute, storage, network, identity and operations are designed as one delivery boundary.
Platform layer
Map hosts, clusters, pools, storage and network paths.
Policy layer
Use identity, placement, resource and service policies to control access.
Operations layer
Define monitoring, change, backup, incident and handover records.
03
Move from assessment to a verifiable delivery path
Use a staged path so compatibility, performance, access and rollback conditions are tested before wider adoption.
- 01
Assess
Inventory workloads, versions, dependencies, users and constraints.
- 02
Pilot
Validate representative workloads, policies, performance and user access.
- 03
Scale
Expand by business wave with change windows and a support path.
- 04
Verify
Close with test results, configuration records and operating ownership.
04
Keep capacity, policy and recovery visible after go-live
The handover baseline should make future expansion, troubleshooting and change decisions easier to trace.
Capacity and performance
Track utilization, headroom, latency and growth against the baseline.
Policy and change
Keep versions, permissions, configuration and approval records current.
Incident and recovery
Use monitoring, logs, runbooks and validation records to support recovery.
Questions
Questions specific to this solution
What should be confirmed before implementing high-performance computing?
Confirm workloads, dependencies, capacity, network paths, identities, support ownership, maintenance windows and rollback conditions.
Should the project start with a pilot?
A focused pilot is recommended when workloads, users or compatibility conditions differ. It makes experience and operating assumptions testable.
How is future expansion handled?
Reserve capacity, interfaces, network paths, operating space and documentation standards during the initial design.
Next step
Start with the current environment and a specific requirement
Share the current systems, site conditions, expected timing or issue so the practical scope can be reviewed.