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DCS Global

High Performance Computing (HPC) Infrastructure — Clusters, InfiniBand & Parallel Storage

Edge & Cloud

High-Performance Computing

HPC clusters engineered for scientific research, engineering simulation, and defense workloads — with InfiniBand interconnects, parallel storage, and SLURM job scheduling.

HPC Infrastructure Capabilities

Heterogeneous Compute

CPU, GPU, and FPGA nodes in a unified cluster — SLURM job scheduler routes workloads to the right compute resource based on job requirements and resource availability.

Low-Latency Interconnect

InfiniBand HDR and NDR fabric delivers 200–400 Gb/s per port with sub-microsecond MPI latency — critical for tightly coupled parallel simulations.

Parallel File Systems

Lustre, GPFS, and BeeGFS parallel storage delivering hundreds of GB/s of sustained I/O throughput for checkpoint-heavy and data-intensive workloads.

Energy Efficiency

Liquid cooling and high-efficiency power infrastructure reduce HPC facility PUE to 1.15–1.25, cutting energy costs for compute-intensive workloads.

Performance Tuning

MPI library optimization, NUMA topology tuning, network buffer sizing, and storage I/O tuning to maximize application performance on the delivered hardware.

Secure HPC Environments

NIST 800-171, ITAR, and FedRAMP-compliant HPC environments for defense, aerospace, and government research workloads requiring controlled unclassified information (CUI) handling.

Industries

HPC Verticals

Scientific Research

Climate modeling, genomics, molecular dynamics, and computational chemistry workloads at national laboratory and university research scales.

Engineering Simulation

CFD, FEA, crash simulation, and electromagnetic modeling for aerospace, automotive, and industrial engineering applications.

Defense & Government

ITAR-compliant and NIST 800-171 HPC environments for defense research, intelligence analysis, and government scientific computing.

Financial Modeling

Monte Carlo simulation, risk analytics, and quantitative modeling workloads requiring deterministic performance and low-latency storage.

Delivery Process

HPC Cluster Build Phases

01

Workload Characterization

Application profiling, MPI communication patterns, storage I/O analysis, and memory bandwidth requirements to right-size the cluster.

02

Cluster Architecture

Node configuration, interconnect topology, storage architecture, job scheduler design, and software stack selection.

03

Facility Design

Power infrastructure, cooling system, network entry, and physical layout optimized for the cluster architecture.

04

Integration & Testing

Hardware integration, OS deployment, software stack installation, and acceptance testing against benchmark workloads.

05

Performance Optimization

MPI tuning, storage I/O optimization, network parameter tuning, and application-specific performance validation.

06

Operations Handover

Administrator training, runbook documentation, monitoring configuration, and optional managed operations engagement.

Technical Specifications

Compute NodesCPU, GPU, FPGA, and hybrid nodes
InterconnectInfiniBand HDR/NDR, 100/200/400 GbE
Parallel StorageLustre, GPFS, BeeGFS, WekaFS
Job SchedulingSLURM, PBS Pro, LSF, OpenPBS
CoolingAir, direct liquid, rear-door HX
Power Density10 kW – 80 kW per rack
OS & SoftwareRHEL, Rocky Linux, OpenHPC stack
ComplianceNIST 800-171, ITAR, FedRAMP (GovCloud)

Frequently Asked Questions

What distinguishes HPC infrastructure from standard data center infrastructure?

HPC infrastructure is optimized for tightly coupled parallel workloads that require low-latency interconnects (InfiniBand), high-throughput parallel storage (Lustre, GPFS), and job scheduling software (SLURM). Standard data center infrastructure is optimized for independent workloads with standard Ethernet networking and block or object storage.

What job scheduling software do you deploy?

We primarily deploy SLURM (Simple Linux Utility for Resource Management), which is the dominant scheduler in academic and research HPC. For commercial environments, we also deploy IBM Spectrum LSF and Altair PBS Pro. We configure fair-share scheduling, QOS policies, and accounting for multi-user environments.

How do you handle storage for large-scale HPC workloads?

We deploy parallel file systems — Lustre, IBM Spectrum Scale (GPFS), BeeGFS, or WekaFS — that stripe data across multiple storage nodes to deliver hundreds of GB/s of aggregate throughput. We size the storage system based on dataset size, checkpoint frequency, and required I/O bandwidth.

Can you build ITAR-compliant HPC environments?

Yes. We have experience building HPC environments subject to ITAR, EAR, and NIST 800-171 requirements. This includes physical access controls, network segmentation, audit logging, and documentation packages required for compliance.

What is the typical timeline for an HPC cluster build?

A mid-scale HPC cluster (100–500 nodes) typically takes 12–20 weeks from contract to acceptance testing — including hardware procurement, facility preparation, integration, and software stack deployment. Larger clusters or those requiring facility construction take longer.

Why Organizations Act

Business Challenges We Solve

Application-Specific Architecture Requirements

CFD, molecular dynamics, seismic processing, and genomics each have distinct CPU, memory, interconnect, and storage profiles. Generic server configurations deliver 40–60% of theoretical peak performance.

MPI Latency and Bandwidth Sensitivity

Tightly coupled parallel applications require sub-microsecond MPI latency. Standard Ethernet introduces 10–100x more latency than InfiniBand, collapsing parallel efficiency at scale.

Parallel File System Throughput

HPC workloads require sustained read/write throughput of 100–500 GB/s. Inadequate parallel file system design is the most common cause of poor HPC application performance.

Cluster Utilization and Job Scheduling

Without proper workload management, HPC clusters run at 40–60% utilization. Slurm and PBS Pro require expert configuration to maximize throughput and enforce fair-share scheduling.

Power and Cooling Density

High-core-count CPU nodes and GPU accelerators push rack densities to 20–40 kW. Most enterprise data centers are designed for 5–10 kW per rack and cannot support HPC without infrastructure upgrades.

Software Stack Complexity

HPC environments require MPI libraries, compilers, math libraries (MKL, BLAS), and application-specific software. Version conflicts and dependency management create significant operational overhead.

Vendor-Neutral Expertise

Technology Ecosystem

DCS Global is vendor-neutral and works with the leading platforms in the industry. We recommend the right technology for your requirements — not the vendor with the best margin.

CPU Platform

AMD EPYC 9004 Series
Intel Xeon Scalable

GPU Accelerators

NVIDIA H100 / A100
AMD MI300X

Interconnect

NVIDIA Quantum-2 InfiniBand
Cornelis Networks OPX

Job Scheduling

Slurm Workload Manager
IBM Spectrum LSF
Altair PBS Professional

Parallel Storage

IBM Spectrum Scale (GPFS)
Lustre File System
WEKA Data Platform

MPI Libraries

Intel MPI / OpenMPI

Math Libraries

Intel oneAPI / MKL

Containers

Singularity / Apptainer

Vendor-Neutral Advisory

DCS Global holds no exclusive reseller agreements that would bias our recommendations. Our engineers are certified across multiple platforms and will specify the solution that best fits your technical requirements, budget, and long-term roadmap.

Trusted Advisor Framework

HPC Infrastructure Buyer\'s Guide

Use this framework to evaluate your requirements before engaging vendors. Organizations that complete this analysis make faster decisions and achieve better outcomes.

What are your target HPC applications and their computational profiles?

CFD requires high memory bandwidth and fast interconnects. Genomics requires high core counts and fast local storage. Seismic processing requires GPU acceleration. Application profiling drives every hardware decision.

What is your target cluster size and expected utilization?

Cluster size determines interconnect topology, job scheduler configuration, and parallel file system design. Expected utilization drives the ROI calculation and procurement strategy.

Do you require on-premises, cloud, or hybrid HPC?

On-premises HPC delivers maximum performance and data control for sustained workloads. Cloud HPC provides elasticity for burst workloads. Hybrid architectures serve both patterns but require careful data movement design.

What are your parallel file system throughput requirements?

Throughput requirements are calculated from application I/O patterns, node count, and job concurrency. Undersized storage is the most common cause of poor HPC application performance.

What are your compliance and data classification requirements?

Defense, energy, and pharmaceutical HPC workloads often carry ITAR, CUI, or GxP classification requirements that mandate specific security controls, audit logging, and data handling procedures.

What is your existing IT team's HPC operational expertise?

HPC clusters require specialized skills in MPI, job scheduling, parallel file systems, and application optimization. Gaps in expertise directly reduce cluster utilization and increase time-to-results.

Not sure where to start? Our solutions advisors can walk you through this framework in a 30-minute discovery call.

Schedule an Infrastructure Assessment

Decision Framework

On-Premises HPC vs. Cloud HPC

Use this framework to evaluate whether building on-premises HPC infrastructure or using cloud HPC services is the right decision for your research and engineering workloads.

CriterionOn-Premises HPCCloud HPC (AWS, Azure, GCP)Best For
MPI LatencySub-microsecond InfiniBand — optimal for tightly coupled jobs10–100x higher latency — limits parallel efficiency at scaleOn-Premises HPC
Parallel File System ThroughputDedicated Lustre/GPFS — 100–500 GB/s sustainedShared storage — throughput varies, often insufficientOn-Premises HPC
Upfront CapitalHigh — $2M+ for a 100-node clusterZero — pure OpExCloud HPC (AWS, Azure, GCP)
Cost for Sustained WorkloadsLower TCO at high utilization over 3+ yearsHigher — cloud HPC costs 3–5x on-prem at sustained useOn-Premises HPC
Data SovereigntyComplete — data never leaves your facilityDepends on provider controls and regionOn-Premises HPC
Burst CapacityFixed — scale requires procurement lead timeElastic — burst to thousands of cores in minutesCloud HPC (AWS, Azure, GCP)
Operational BurdenFull operational responsibility on your teamManaged infrastructure — lower ops burdenCloud HPC (AWS, Azure, GCP)
Application OptimizationFull control over hardware and software stackLimited by provider instance types and configurationsOn-Premises HPC

This comparison is a general framework. The right choice depends on your specific requirements, existing environment, and business objectives. DCS Global can help you evaluate the options for your situation.

Next Step

Build Your HPC Environment

Share your application workloads, scale requirements, and compliance needs. We will design an HPC cluster that delivers the performance your research demands.

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Build Your HPC Environment

Share your application workloads, scale requirements, and compliance needs. We will design an HPC cluster that delivers the performance your research demands.