G1508-1600WNA – 1600W CRPS Power Supply for Edge Datacenters, Real-Time Processing Systems, and Advanced Network Appliances

The G1508-1600WNA is a 1600W CRPS power module developed for edge datacenters, real-time processing systems, and advanced network appliances that require stable and efficient power in compact environments. Its standardized 1U CRPS form factor (185 × 73.5 × 40 mm) ensures effortless integration into dense, space-restricted hardware architectures. Providing a robust 12V main output rated at 133A along with a 12V standby rail at 2.1A, the unit delivers consistent power to CPUs, network processors, high-speed switching modules, and auxiliary management circuits. The wide input range of 90–264Vac / 180–300Vdc supports global deployment across varying power grids. Equipped with digital control and full PMBus 1.2 capability, the G1508-1600WNA enables detailed telemetry, power tuning, and remote supervision—ideal for distributed systems where precise control improves uptime and service efficiency. Its intelligent cooling system dynamically adjusts airflow to maintain thermal stability while reducing unnecessary acoustic output. A reverse-airflow option is available for platforms that require non-traditional cooling routes, offering enhanced flexibility for design engineers.

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): 1600
Length (mm): 185
Width (mm): 73.5
Height (mm): 40
Mounting Type: Hot pluggable
Minimum Output Current (A): 0
Maximum Output Current (A): 133
Output Voltage (V): 12
Minimum Output Power (W): 0
Maximum Output Power (W): 1600
Minimum Input Voltage (V): 90
Maximum Input Voltage (V): 264

Model Selection Comparison Table

Model

Power Tier Behavior PMBus Form Factor Recommended Use
G1508-1600WNA Mid-high performance Compute/storage balanced Yes CRPS

Virtualization + inference

G1508-2000WNA

Large enterprise compute Heavy AI/HPC Yes CRPS Multi-GPU, HPC fabrics
G1505-2700WNA Entry high-capacity GPU/Compute dense workloads Yes CRPS

HPC / inference clusters

G1505-3200WNA

Maximum performance Heavy accelerated compute Yes CRPS

AI + multi-node processing

Deployment Scenarios

G1508-1600WNA is the higher-capacity performance model in the G1508 platform, targeting edge-scale compute, multi-NIC gateways, distributed storage blocks, virtualized clusters, and medium AI inference pipelines that demand stable rail delivery beyond 1200W-class envelopes. It is positioned for environments where workload concurrency and memory traffic generate continuous mid-to-high utilization, but thermal and cost efficiency still matter as deployment scale increases.

 

This watt tier provides comfortable operational margin for 2–4 accelerator cards, NVMe-rich storage appliances, mid-density inference racks, content delivery processors, and mixed virtualization nodes. Its rail stability under moderate step loads reduces jitter during container burst launches, storage index rebuilds, encryption tasks and micro-batch inference surges, helping preserve latency performance without premature redundant PSU scale-out.

 

Scenario

Load Pattern Why 1600W Applies
Multi-NIC gateway nodes Mixed compute + I/O

Sustains dual-accelerator duty

NVMe storage blocks

High write concurrency Ripple remains controlled
VM/Container clusters On-off burst cycles

Transient suppression capacity

Mid-range inference

Batch + streaming Rail remains stable near 80–90%
CDN/Edge processor Continuous streaming

Long duty thermal balance

Database middleware

Commit-heavy traffic

Low waveform distortion risk

Power Architecture & Reliability Design

The G1508-1600WNA balances conduction headroom with thermal efficiency, enabling long-life deployment in mixed storage–compute roles without prematurely entering high-power stress conditions. Its power path routing reduces conduction loss under steady transactional workloads, while the switching cadence and magnetic layout control temperature rise during mid-density inference streams, regional CDN cache serving, and container platform expansion cycles. Voltage rails remain stable through rapid utilization swings, limiting ripple propagation into latency-sensitive compute and networking fabrics.

 

Thermal design emphasizes even load distribution rather than peak dissipation. Heat is spread uniformly across switching elements and capacitor domains to delay electrolyte aging during continuous 24/7 operation. Ripple suppression remains consistent during NVMe burst writes, metadata rebuild events, and ingestion-heavy workloads, preventing secondary latency effects under parallel IO pressure. EMI distribution and spread-spectrum control further reduce signal interference when deployed in dense backplanes with high-speed NICs and transceivers.

 

PMBus telemetry provides operational transparency into voltage drift behavior, fan duty response, ripple vector evolution, and thermal slope variation, supporting predictable operation through real-world events such as firmware migrations, node scaling, and index rebuild traffic. Positioned between the 1200W and 2000W classes, the G1508-1600WNA is well suited for environments where compute and storage demand is substantial, but full 2000W provisioning is not yet required.

Power Operating Notes

Reference Condition

Suggested Guidance
VM/Container workloads

Maintain airflow for sustained >70% load

Storage/NVMe clusters

Monitor ripple after long write windows
Edge compute/Nodes

Inspect thermal slope quarterly

CDN/Streaming

Track fan curve under peak nights
24/7 operation

Clean intake paths to protect efficiency

Workload scaling

Add redundancy when consistently >90%
Burst-heavy inference

Monitor PMBus transient logs monthly

Node future expansion

Consider shift to 2000W when GPU count grows

FAQ

Q1. When is G1508-1600WNA preferred?
When mixed compute/storage tasks run near-steady load and require overhead beyond 1200W tier.

 

Q2. Difference vs 2000W?
2000W suits heavier AI acceleration; 1600W fits balanced compute where efficiency matters.

 

Q3. PMBus availability?
Full telemetry for predictive lifecycle planning.

 

Q4. Suitable for 24/7 DC workloads?
Yes — thermal design targets always-on edge and datacenter conditions.

 

Q5. Use case precision?
Virtualization pools, NVMe nodes, mid-range inference clusters.

 

Q6. Thermal guidance?
Stable cooling keeps rail behavior linear under 80–90% sustained load.

 

Q7. Reliability positioning?
Optimized for long-term deployment where electrical stability > raw watt ceiling.

 

Q8. Scaling advice?
Upgrade to 2000W when workload expands into heavy multi-GPU territory.

 

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