HPC Networking Solutions
We design and deploy lossless, low-latency network architectures that unlock the full potential of your GPU and CPU clusters.
Accelerate Discovery and Innovation with HPC
In the era of generative AI and large-scale simulation, organizations depend more than ever on the real-time insight and competitive advantage delivered by HPC applications. As the number of AI/ML/HPDA workloads running on HPC systems grows, the drive to expand computing capability runs straight into the limits of the network. Mevasis designs, deploys and validates networks that carry the most demanding HPC and AI workloads end to end — using InfiniBand and RoCE architectures, original NVIDIA interconnect hardware and field-proven configuration templates.
High-Performance Hardware
Advanced Technology & Software
Worry-Free Services
Featured Products
Enterprise-grade components for every layer of your HPC network. Products are listed for informational purposes — contact us for project-specific configuration and quotations.
InfiniBand Network
End-to-end NDR/XDR-class InfiniBand fabric
RoCE / Ethernet Network
400G/800G lossless Ethernet fabric
Structured Cabling
High-density fiber infrastructure
Power Infrastructure
Uninterruptible and observable energy
All products are listed for informational purposes — pricing is quoted per project. Browse the full catalogue →
HPC Networking Solution Architectures
We offer three network approaches depending on your cluster scale and workload profile. Every architecture is documented with its topology, bill of materials and acceptance test criteria.
InfiniBand Networking Solutions
The lowest latency for MPI and large-scale AI training
800G/400G NDR Fabric — H100/H200 GPU Clusters
- Ultra-high bandwidth that shortens data synchronization across GPU clusters
- Full bisection bandwidth with fat-tree topology; performance is preserved as the cluster grows
- End-to-end validated architecture with ConnectX-7 NICs and NDR switches
HDR 200G InfiniBand — MPI Workloads
- 1–2 µs latency for MPI-based applications such as CFD, FEA and molecular dynamics
- Stability in all-to-all traffic with adaptive routing and congestion control
- A gradual migration path to NDR that protects existing HDR investment
Rail-Optimized Multi-Rail Design
- Predictable NCCL traffic performance with a dedicated rail per GPU
- In-network computing for collective operations with SHARP support
- Rail-based monitoring and fault isolation
RoCE Networking Solutions
Lossless AI fabric on the open Ethernet ecosystem
800G RoCE Data Center Network
- Lossless RoCEv2 with PFC/ECN removes GPU network stalls and improves training efficiency
- High-density spine-leaf fabric scales AI clusters efficiently within limited racks and ports
- LPO optics cut power and cooling costs, reducing overall TCO
400G RoCE — Scalable AI Cluster
- High-bandwidth, low-latency and lossless connectivity for AI training and HPC workloads
- Flexible spine-leaf expansion simplifies scaling and reduces future upgrade complexity
- Easier deployment and unified management with open Ethernet architecture
Dual-Plane AI Compute Fabric
- Stable, low-latency, congestion-free cluster performance with RoCEv2 lossless networking
- Dual-plane architecture improves scalability, reliability and GPU communication efficiency
- A dedicated RDMA storage network isolates storage and compute traffic
Distributed Storage Networking
High I/O for NVMe-oF and parallel file systems
100/200G AI Storage Network
- Stable, low-latency, high-throughput storage traffic with PFC, ECN and DLB
- Flexible expansion and high availability with MLAG and redundant spine-leaf architecture
- End-to-end validated design with the BeeGFS parallel file system
Customer Success and Insights
Turbomachinery Simulation Cluster — CFD
A 384-core on-prem HPC cluster; end-to-end deployment and operations with Slurm, Lustre and a RoCE network.
Read the case study → 10× speedupGenomics Analysis Pipeline — Life Sciences
GPU-accelerated variant calling; 10× speedup on NVMe parallel storage with Nextflow + SLURM integration.
Read the case study → On-prem + CloudHybrid Capacity Model — Enterprise R&D
On-prem HPC plus cloud bursting; hybrid job management and elastic capacity behind a single scheduler.
Read the case study →Frequently Asked Questions
Should I choose InfiniBand or RoCE?
InfiniBand stands out for large-scale MPI workloads and tightly synchronized AI training thanks to the lowest latency, adaptive routing and in-network computing capabilities such as SHARP. RoCE is preferred for its open Ethernet ecosystem, existing data center operational knowledge and cost advantage. The decision is made together with workload analysis, based on workload profile, cluster scale, operational expertise and budget.
Is our existing Ethernet infrastructure sufficient for HPC?
Enterprise Ethernet switches typically operate in lossy mode and lack the PFC/ECN configuration required for RDMA traffic. In GPU clusters this leads to serious extensions in training times. We evaluate the suitability of your existing infrastructure in terms of port speed, buffer capacity and ECN/PFC support with a free preliminary analysis.
How does the network design process work?
First we profile the communication pattern of your workload (MPI collective patterns, NCCL traffic, I/O profile). Then we present a design document within 48 hours including topology selection (fat-tree, rail-optimized, dragonfly+), switch/NIC/cable sizing and VLAN/segmentation plan. After approval, we commission the network with installation, configuration and acceptance tests based on ib_write_bw, OSU and IMB.
Why is there no pricing information on the site?
HPC network hardware varies across a wide price range depending on port count, speed tier (HDR/NDR/XDR), optical/DAC preference and project scale. Instead of misleading list prices, we prepare a project-specific BOM and a competitive quotation. Simply fill in the request form; our team will get back to you within one business day at the latest.
What does post-installation support cover?
Under the SLA we provide 24/7 monitoring, fabric health checks, firmware updates and fault response. With the Prometheus + Grafana monitoring stack, port errors, temperature and bandwidth are tracked in real time, and capacity expansion needs are reported in advance.