G1429-1300WNA – 1300W CRPS Power Supply Optimized for High-Density Server and Network Environments
Features
CRPS-185: 185×73.5x40mm(LxWxH)
CRPS-265: 265×73.5x40mm(LxWxH)
Input: 90 to 264Vac,180-300VdC
Hot-plug
Full Digital control
Active Power Factor Correction
Intelligent-thermal Fan Control
N+N N+1 Redundant
Reverse Airflow Option
Applications
Server
Storage
Networking
HPC
Edge Computing
Telecom
AI Training
Industrial Automation
Approvals
UL/cUL
CB
TuV-Mark
CCC/CQC
FCC
CE
NOM
BIS
Specifications
| Output Power (W): | 1300 |
| Length (mm): | 185 |
| Width (mm): | 73.5 |
| Height (mm): | 40 |
| Mounting Type: | Hot pluggable |
| Minimum Output Current (A): | 0 |
| Maximum Output Current (A): | 108.33 |
| Output Voltage (V): | 12 |
| 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 Tier | Behavior | PMBus | Form Factor | Recommended Use |
| G1429-0800WNA | Titanium efficiency mid-range | Light-to-mid cluster workloads | Yes | CRPS |
Edge compute / analytics |
| Titanium high tier | Heavier virtualization/inference | Yes | CRPS |
Multi-VM / GPU-assisted nodes |
Deployment Scenarios
As the higher-capacity Titanium model in the G1429 platform, G1429-1300WNA is designed for dense multi-service compute clusters, GPU-assisted virtualization, data analytics nodes, edge inference workloads, and medium-weight AI processing. Its 1300W continuous output capacity provides operational margin for environments that experience sustained parallel processing, high memory bandwidth consumption, heavy I/O synchronization, or moderate GPU burst cycles.
The model is commonly adopted by enterprise virtualization stacks, distributed AI inference, mini HPC nodes, storage gateways, CDN acceleration, database caching platforms, and backbone coordination servers. Titanium conversion efficiency helps reduce electricity cost and thermal overhead per rack unit, allowing tighter node placement without compromising lifetime.
|
Scenario |
Workload Behavior | Why 1300W Fits |
| Medium GPU inference | Burst + sustained cycles |
Higher load ceiling |
|
Virtualization clusters |
Multi-VM parallel tasks | Stable under mid-heavy duty |
| Mini HPC | Balanced compute streams |
Smooth voltage behavior |
|
Storage gateway |
Sync+cache spikes | Headroom avoids droop |
| CDN acceleration | High traffic windows |
Thermal predictability |
|
Data analytics nodes |
CPU/GPU hybrid | Margin for expansion |
Power Architecture & Reliability Design
G1429-1300WNA applies Titanium-grade switching topology and refined magnetic balance to maintain low conduction loss even under higher sustained loads, enabling data-center operators to scale service density without escalating thermal or cooling budgets. This power class provides stronger voltage stability during GPU-assisted tasks and rapid burst transitions, reducing performance jitter in virtual cluster operations.
Extended capacitance layout enhances endurance during high-temperature duty cycles, while optimized airflow geometry spreads heat extraction evenly, extending internal component lifespan. PMBus telemetry enables tracking of supply health indicators such as ripple drift trend, cooling curve behavior, cumulative runtime, and protection events, assisting predictive maintenance planning. G1429-1300WNA is engineered for heavy concurrency where uptime targets exceed routine maintenance cycles.
The core architecture leverages Titanium-grade conversion efficiency to reduce operating costs in dense rack environments while maintaining sufficient headroom to absorb GPU bursts and high memory load events. Ripple stabilization ensures voltage consistency during heavy virtualization, and the capacitor layout is designed to withstand prolonged thermal exposure under sustained duty cycles. PMBus monitoring enables predictive replacement by revealing early signs of component wear, while reliable current delivery supports multi-tenant cluster orchestration without performance degradation. Lower heat output improves overall cooling efficiency, making the platform well suited for scale-out AI and compute edge growth.
Power Operating Notes
|
Reference Condition |
Suggested Guidance |
| GPU-assisted inference |
Maintain stable intake airflow for thermal margin |
|
Virtualization & clustering |
Review PMBus fault logs monthly |
| Data node caching |
Monitor ripple drift during sync bursts |
|
Mini-HPC |
Keep inlet <35°C for component stability |
| Scaling workloads |
Balance rail share in N+1 topology |
|
Distributed POP edge |
Clean dust intake quarterly |
| Storage gateway |
Fan ramps may indicate capacitor aging |
|
Future expansion |
Upgrade PSU only if sustained load >80% |
FAQ
Q1. When to choose G1429-1300WNA instead of 800W?
When workloads include GPU-assisted compute, multi-tenant virtualization, or higher sustained traffic.
Q2. Does Titanium efficiency matter under high load?
Yes — energy loss remains low even near operational ceiling, reducing cooling cost.
Q3. Is PMBus supported for remote telemetry?
Fully supported for health, temperature, fan, and protection reporting.
Q4. Uptime suitability?
Built for 24/7 data-center operation with predictive maintenance scheduling.
Q5. GPU inference capability?
Suitable for medium AI acceleration, depending on GPU configuration.
Q6. Deployment cluster size?
Performs well in scale-out architectures with consistent compute demand.
Q7. Hot-swap and N+1 integration?
Compatible within CRPS-based redundancy structures.
Q8. If future load increases?
Remain below 80% sustained load for efficiency; otherwise scale PSU capacity.