G1179-1300WNA – 1300W 2U Power Distribution Board for AI Servers, Data Centers, and High-Bandwidth Networking Equipment
Features
2U Dimension: 265x77x84mm(LxWxH)
Input: 90 to 264Vac,180-300Vdc
Hot-plug
Full Digital control
Efficiency: Platinum/Titanium
Active Power Factor Correction
Reverse Airflow Option
Intelligent-thermal Fan Control
1+1 2U Redundant
Applications
Server
Storage
Networking
HPC
AI Centers
Cloud Platforms
Edge Computing
GPU Workstations
Approvals
UL/cUL
CB
TuV-Mark
CCC/CQC
FCC
CE
NOM
BIS
Specifications
| Output Power (W): | 1300 |
| Length (mm): | 265 |
| Width (mm): | 77 |
| Height (mm): | 84 |
| Mounting Type: | Hot pluggable |
| Output Current (V): | +12V/108A,+5V/25A,+3.3V/25A, -12V/0.5A,+5Vsb/3A |
| Minimum Output Power (W): | 0 |
| Maximum Output Power (W): | 1300 |
| Minimum Input Voltage (V): | 90 |
| Maximum Input Voltage (V): | 264 |
Model Selection Comparison Table
|
Model |
Power Class | Use Role | Input | Form Factor | Recommended Use |
| G1179-0150WNA | Entry | Micro control compute | AC/DC | 1+1 2U PDB |
Monitoring & light routing |
| Mid | Edge + light VM | AC/DC | 1+1 2U PDB | Burst-capable deployment | |
| G1179-0350WNA | Upper-Mid | VM/storage light | AC/DC | 1+1 2U PDB |
Multiple services small scale |
| Mid-High | Multi-role compute | AC/DC | 1+1 2U PDB | Routing/IO concurrency | |
| G1179-0550WNA | High | Dense small servers | AC/DC | 1+1 2U PDB |
Heavier IO & VM |
| Strong | Storage + compute | AC/DC | 1+1 2U PDB |
POP/CDN micro edge |
|
| Extreme | Compute heavy nodes | AC/DC | 1+1 2U PDB | GPU-lite workloads | |
| G1179-1600WNA | Peak | AI/DB + compute | AC/DC | 1+1 2U PDB |
Scale-out fabrics |
Deployment Scenarios
The G1179-1300WNA enters the extreme performance tier within the G1179 platform — designed for compute-intensive edge clusters, high-density multi-VM deployments, SDS/object storage nodes, distributed cloud fabrics, security+routing fusion workloads, and light GPU inference acceleration. It offers significantly more overhead compared to 800W, enabling parallel service execution, burst-tolerant VM scheduling, large data movement, SDS caching and small model inference tasks. This model fits deployments where compute growth, IO frequency, and network throughput scaling require a power capacity that remains stable under constant high activity.
|
Scenario |
Workload Style | Why 1300W Tier Fits |
| Large edge compute | High concurrency |
Stable under VM density |
|
SDS/object storage |
Heavy IO cycles | Ripple headroom holds |
| POP routing + caching | Layered micro-services |
Manages sustained peaks |
|
Private cloud node |
Multi-app workloads | Predictable under load |
| GPU-lite inference | Model routing tasks |
Adequate burst reserve |
|
Data gateway cluster |
Busy interconnect |
Consistent voltage rails |
Power Architecture & Reliability Design
The G1179-1300WNA is engineered for environments that demand high concurrency and sustained compute throughput, supporting nodes where multiple services run continuously under persistent I/O pressure. Its power architecture is designed to deliver stable output as storage, networking, and compute workloads overlap, enabling predictable behavior in clusters that operate near steady-state utilization rather than short burst cycles.
Voltage regulation remains firm during storage indexing operations, high-traffic routing activity, virtual machine scheduling spikes, and moderate inference surges, preventing droop that could destabilize active services. Ripple control is optimized to reduce latency impact on SSD and NVMe subsystems, helping preserve I/O consistency and responsiveness even when read/write activity intensifies alongside compute execution.
PMBus telemetry provides detailed insight into power traces, thermal profiles, and long-term operating patterns, supporting lifecycle visibility and capacity planning across large distributed deployments. Thermal resilience allows reliable operation in edge racks and compact POP environments where airflow margins are limited but uptime requirements are strict. Positioned as the upper performance tier before the 1600W class, the G1179-1300WNA offers strong scalability for compute-dense clusters without immediately moving into maximum power envelopes.
Power Operating Notes
|
Reference Condition |
Suggested Guidance |
| Compute-heavy workloads |
Maintain cooling efficiency |
|
SDS/object storage |
Track SSD temperature profiles |
| POP/CDN + VM fusion |
Leave capacity safety margin |
|
GPU-lite inference |
Validate thermal envelope |
| Distributed cloud fabrics |
Enable periodic PMBus readouts |
|
24/7 active duty |
Ensure dust cleaning intervals |
| Load bursts common |
Maintain grounding integrity |
|
Future scale |
Upgrade to 1600W for AI/DB-heavy growth |
FAQ
Q1. What environment is G1179-1300WNA built for?
Ideal for compute-dense edge clusters, storage-heavy workloads, POP caching, and mixed VM routing environments, where concurrency and IO intensity stay high for long durations.
Q2. Can it be used for continuous 24/7 deployment?
Yes. Its thermal design and regulated voltage behavior support continuous high activity, assuming airflow remains sufficient and PMBus monitoring is part of maintenance.
Q3. How is it superior to the 800W model?
It provides substantially more burst room, better IO tolerance, and improved VM scalability, handling multi-service workloads without power margin constraints.
Q4. Redundancy support?
Fully compatible with 1+1 PDB high-availability configurations, making it fit for POP nodes or cloud infrastructure requiring maintenance-free uptime.
Q5. Is it suitable for GPU-assisted workloads?
Yes — appropriate for light inference accelerators or model serving, but heavy parallel GPU processing should move to 1600W.
Q6. Best roles in POP/CDN?
Delivers stable behavior under cache rotation, routing, and multi-tenant VM workloads, making it strong for distributed content layers.
Q7. VM scalability expectations?
Supports higher VM density than 0550W/0800W, especially in compute-centric clusters with active IO exchange.
Q8. When should deployment move to 1600W?
When workloads shift toward AI compute, sustained NVMe flush cycles, or heavy SDS + routing mix, 1600W delivers better long-term overhead.