HPE Cray XD670 AI Server with 8× NVIDIA H100 GPUs: Special Offer
- diyasjournal
- 13 minutes ago
- 4 min read
The HPE Cray XD670 is a high-density AI server designed for large-scale AI training and HPC workloads. Systems like this are typically very expensive; however, in this case the availability of a fixed configuration allows us to offer these servers under special conditions.
NVIDIA HGX H100 SXM5 8-GPU AI Server
✔️ 5-Year Warranty – No Risk: Pay Only After Testing
HPE Cray XD670 AI Server: 8× NVIDIA H100 SXM – Configuration Overview
The HPE Cray XD670 is a 5U, high-density AI and HPC server built around an NVIDIA HGX platform with 8× NVIDIA H100 SXM GPUs.
It is designed for:
Sustained, high-load operation
Large multi-GPU workloads
Scale-out cluster deployments
The servers we are offering are based on a fixed, fully supported configuration available as a special offer. This is not a maximum-spec or showcase build. Component choices such as CPU generation and memory speed reflect commonly deployed, fully validated options.
Full configuration – HPE Cray XD670 AI Server with 8× NVIDIA H100 GPUs
Base system: HPE Cray XD670 AI Server with 8× NVIDIA H100 GPUs
Component | Details | Why it matters |
Server | HPE Cray XD670 CTO Server / Chassis | Purpose-built AI/HPC platform |
Form factor | 5U | Required for 8× SXM GPUs |
Part numbers | P60537-B21 / P60537-B21#ABA | Standard XD670 CTO base |
The XD670 chassis is engineered for:
Very high power density
High-volume airflow or direct liquid cooling (DLC)
Rack-scale cluster deployment
GPUs: 8× NVIDIA H100 SXM
Component | Details | Why it matters |
GPUs | 8× NVIDIA H100 SXM | High-end AI training performance |
GPU memory | 80 GB HBM3 per GPU | Large model and batch capacity |
Interconnect | NVLink / NVSwitch | High GPU-to-GPU bandwidth |
This system uses SXM GPUs, not PCIe cards. The SXM form factor enables:
Significantly higher inter-GPU bandwidth
Lower latency for collective operations
Better scaling for large models and multi-GPU jobs
The XD670 platform also supports NVIDIA H200 SXM GPUs in newer configurations, offering higher HBM capacity and bandwidth.
CPUs: 2× Intel Xeon Platinum 8462Y+
Component | Details | Why it matters |
CPUs | 2× Intel Xeon Platinum 8462Y+ | Provides CPU compute for data preprocessing, orchestration, and I/O coordination |
Generation | 4th Gen Intel Xeon (Sapphire Rapids) | Fully supported platform for H100-based XD670 systems |
Part number | P56397-B21 | Enterprise-grade processor validated by HPE |
These CPUs handle system-level tasks such as data ingestion, preprocessing, job scheduling, and I/O coordination. In GPU-heavy systems like the XD670, the CPUs support the GPUs rather than act as the primary compute engine. It also provides stable performance and full platform compatibility for H100-based deployments.
Memory: 32× 64 GB DDR5 RDIMM
Component | Details | Why it matters |
Memory | 32× 64 GB DDR5 RDIMM | Provides high-capacity system memory for large datasets and preprocessing |
Total capacity | 2048 GB (2 TB) | Meets and exceeds HPE minimum memory requirements for H100 systems |
Speed | DDR5-4800 MT/s | Balanced memory speed for stable operation with this CPU generation |
Part number | P46970-H21 | HPE-qualified enterprise memory |
This memory configuration supports large datasets, CPU-side preprocessing, and stable multi-GPU operation.
Storage: 1× 960 GB NVMe RI SSD
Component | Details | Why it matters |
OS drive | 1× 960 GB NVMe RI SSD | Separates operating system from data workloads for stability |
Part number | P60528-H21 | Enterprise NVMe drive validated by HPE |
Data drives | 8× 7.68 TB NVMe RI U.2 SSD | Provides very high local throughput for data staging and checkpoints |
Use | Data staging, checkpoints | Reduces I/O bottlenecks during training |
Part number | P62560-H21 | High-endurance NVMe storage for sustained workloads |
The XD670 supports up to 8 SFF NVMe drives. Primary datasets are typically stored on external parallel or object storage systems.
NVMe / M.2 expansion: 4-port PCIe M.2 RAID adapter
Component | Details | Why it matters |
Adapter | 4-port PCIe M.2 RAID adapter | Enables flexible high-speed storage for boot redundancy, caching, or system separation |
Part number | P62966-B21 | HPE-validated adapter for enterprise systems |
Networking: InfiniBand NDR200 / Ethernet
Component | Details | Why it matters |
Adapter | InfiniBand NDR200 / Ethernet | Enables low-latency, high-bandwidth cluster communication |
Ports | Dual-port QSFP112 (200 Gb/s) | Provides redundancy and full-bandwidth connectivity |
Features | RDMA, GPUDirect | Reduces CPU overhead and improves GPU-to-GPU communication |
Part number | P65333-B21 | NVIDIA ConnectX-7–class adapter validated by HPE |
This configuration is based on NVIDIA ConnectX-7–class adapters, commonly used in modern AI and HPC clusters.
Security: TPM 2.0 module
Component | Details |
TPM | TPM 2.0 module |
Part number | P63379-B21 |
Provides hardware root of trust, secure boot, and firmware validation.
Power and cooling: High-power air-cooled
Component | Details |
Power consumption | ~10–11 kW under sustained load (higher transient peaks possible) |
Power cables | 6× C19–C20 |
Cooling | Air-cooled (supported) / Direct Liquid Cooling (recommended for dense racks) |
GPU power | Up to 700 W per NVIDIA H100 SXM GPU |
Under sustained load, an 8× H100 SXM system typically draws ~10–11 kW, with higher transient peaks possible. While air-cooled configurations are supported, direct liquid cooling (DLC) is commonly required to sustain full 700 W GPU operation reliably in dense rack deployments.
Platform Overview – HPE Cray XD670 AI Server with 8× NVIDIA H100 GPUs
The HPE Cray XD platform represents HPE’s current generation of AI and HPC systems, evolved from earlier Cray architectures.
It is designed for:
High GPU density
Efficient thermal management
Large-scale, multi-rack clusters
For 8× SXM GPU configurations, DLC is often preferred to maintain performance consistency and rack density.
Practical use cases – HPE Cray XD670 AI Server with 8× NVIDIA H100 GPUs
AI model training — sustained, high GPU utilization
Large language models — model parallelism and multi-node scaling
HPC simulations — engineering, physics, climate modeling
Scientific research — genomics, materials science, national labs
Data-intensive workloads — fast local NVMe reduces I/O bottlenecks
Testing, condition, and warranty – HPE Cray XD670 AI Server with 8× NVIDIA H100 GPUs
For new factory-built systems:
Assembled and validated by HPE
Firmware tested
Hardware burn-in performed
Testing typically includes CPU, GPU, thermal, and power validation.
Final note – HPE Cray XD670 AI Server with 8× NVIDIA H100 GPUs
This is not a general-purpose server.
It is designed for organizations that require:
Dense GPU compute
Sustained AI training performance
Enterprise-grade power, cooling, and support
This configuration represents a realistic, deployable baseline for modern AI and HPC environments.
NVIDIA HGX H100 SXM5 8-GPU AI Server
✔️ 5-Year Warranty – No Risk: Pay Only After Testing