Accelerated Compute
GPU and accelerator servers, CPU/GPU balance, memory, topology and scale-up/scale-out architecture sized around the workload.
AI INFRASTRUCTURE & HPC
Infrastructure engineered for AI and high-performance computing.
Build scalable platforms for model training, inference, simulation, analytics and other data-intensive workloads by integrating accelerated compute, high-speed networking, storage, software, power and cooling as one architecture.
ARCHITECTURE
From accelerated servers to complete AI and HPC platforms
Successful AI and HPC environments depend on more than GPU performance. Compute, data movement, storage throughput, scheduling, facility capacity, resilience and operations must be designed together. Bi-Line helps organizations assess requirements, select and integrate technologies, validate performance and build an infrastructure foundation that can grow with new workloads.
CORE CAPABILITIES01 02 03 04 05 06 07 08
High-Speed Fabrics
Low-latency, high-throughput Ethernet or InfiniBand connectivity for compute nodes, storage and data pipelines.
High-Performance Storage
NVMe, scale-out and parallel file/object storage for datasets, checkpoints and data-intensive AI/HPC pipelines.
AI/HPC Software Stack
Operating system, containers, Kubernetes, HPC schedulers, driver/toolkit layers and monitoring for a manageable production platform.
Data Center Power & Cooling
Rack density, UPS, power delivery, air or liquid cooling and environmental monitoring for high-density AI/HPC infrastructure.
Security & Governance
Network segmentation, access control, secrets protection, workload isolation and data-protection policies across the platform.
Availability & Data Protection
Monitoring, checkpoint protection, backup/replication and recovery approaches for continuity of critical AI/HPC workloads.
Integration & Lifecycle Services
Assessment, proof of concept, deployment, integration, performance tuning, documentation, support and expansion planning.
WORKLOADS
Workloads we design for
The architecture is sized around the real workload, dataset, performance target and operating model.
- Generative AI and large language model training
- AI inference and serving
- Computer vision and deep learning
- Data science and advanced analytics
- Scientific and engineering simulation
- Digital twins and modeling
- Rendering and visualization
- Research and academic HPC
DELIVERY
An end-to-end delivery approach
We coordinate the infrastructure as one system rather than a collection of products.
01Assess workloads, data and facility constraints
02Design compute, fabric, storage and platform architecture
03Validate sizing and critical design assumptions
04Deploy, integrate and commission the environment
05Optimize performance, operations and lifecycle growth
Planning an AI or HPC project?
Talk to Bi-Line about workload sizing, GPU infrastructure, high-speed networking, storage, power, cooling and deployment.