Jeanna
Open Source AI Infrastructure Integration Best Practices
Open source software gives organizations extraordinary flexibility when building AI infrastructure. It can reduce licensing costs, limit vendor lock-in and provide access to a rapidly evolving ecosystem of frameworks, libraries and management tools. But open source does not automatically mean...
Why Demo Systems Reduce HPC Procurement Risk
HPC procurement decisions increasingly involve more than comparing processor specifications, accelerator counts and theoretical performance. The real question is how a proposed architecture will perform with an organization’s actual workloads, software stack, and operating requirements. A well-equipped demo system transforms...
Building a Scalable AI Infrastructure Roadmap
Today’s AI infrastructure decisions can determine how easily an organization scales tomorrow. Adding GPUs may increase theoretical compute capacity, but sustainable growth requires an architecture where compute, storage, networking, power, cooling, and software can evolve together. The challenge is forecasting...
Recovering from HPC Cluster Performance Degradation | Nor-Tech
HPC clusters rarely lose performance because of a single obvious failure. More often, degradation develops incrementally as workloads, software, storage requirements and infrastructure evolve. The cluster may remain operational while job completion times increase, GPU or CPU utilization declines, or...
How to Evaluate an HPC Systems Integrator Before You Buy
Selecting high-performance computing hardware is only one aspect of a successful HPC deployment. Equally important is choosing the systems integrator responsible for designing, configuring, validating, and supporting the environment. Processor specifications, GPU counts, storage capacity… these are all important, but...
Designing Fault-Tolerant AI Infrastructure for Enterprise Workloads | Nor-Tech
As AI workloads continue to expand, infrastructure failures can interrupt model training, corrupt datasets, delay research, and disrupt production inference. Designing fault-tolerant AI infrastructure demands an integrated architecture engineered to maintain availability, performance, and data integrity. Otherwise, the consequences can...
What Happens During an HPC Cluster Burn-In and Validation Process? | Nor-Tech
An HPC cluster may be fully assembled, but that does not mean it is ready for production. Before supporting engineering simulations, AI training, scientific research, or mission-critical workloads, every system should undergo a comprehensive burn-in and validation process designed to...
How to Avoid Common HPC Cluster Integration Failures | Nor-Tech
Selecting high-performance computing hardware is only the first step in building a successful HPC environment. The greater challenge often lies in integrating up to 100s of interconnected technologies into a stable, high-performing system. Without careful planning and validation, integration issues...
Enterprise Linux AI Infrastructure Integrators: Building Production AI Platforms Beyond GPU Procurement – Nor-Tech
As institutions and enterprises accelerate AI adoption, many discover that acquiring GPUs is only the beginning of building a successful enterprise AI environment. Production AI infrastructure requires a carefully engineered Linux platform capable of supporting training, inference, simulation, data analytics,...
Open Source AI HPC Stack Integration: Why Software Architecture Matters More Than Hardware Specifications – Nor-Tech
Organizations investing in AI and HPC infrastructure often focus heavily on GPUs, interconnects, and benchmark performance. Yet many production deployments encounter performance limitations that have little to do with hardware. Instead, the primary challenges emerge from integrating increasingly complex open...