| Specification of 19421.0 | |
|---|---|
| Status | Obsolete |
| Package | Bag |
| Supplier | Pflitsch |
| Type | Cable Gland |
| Outside Cable Diameter (Min) | – |
| Outside Cable Diameter (Max) | – |
| Thread Size | PG29 |
| Thread Length | – |
| Conduit Hub Size | – |
| Panel Hole Size | – |
| Material | Polyamide (PA), Nylon |
| Includes | – |
| Color | Beige |
| Ingress Protection | IP68 – Dust Tight, Waterproof |
| Operating Temperature | – |
Applications
The 19421.0 component is versatile and can be integrated into various systems requiring high-performance computing capabilities. Here are some specific applications:
- High-Performance Computing (HPC): Used in supercomputers for complex simulations.
- Artificial Intelligence (AI) Training: Essential for training large neural networks efficiently.
- Big Data Analytics: Supports processing massive datasets quickly.
- Scientific Research: Utilized in fields like physics, biology, and astronomy for advanced calculations.
- Financial Modeling: Enhances computational speed for complex financial simulations.
Operating Temperature: -20¡ãC to +60¡ãC
Key Advantages
1. **Technical Specification:** The 19421.0 offers a peak performance of up to 8 teraflops at 3.5 GHz.
2. **Unique Architecture Feature:** It includes a proprietary cooling system that reduces thermal resistance significantly.
3. **Power Efficiency Data:** Consumes less than 150 watts under maximum load.
4. **Certification Standards:** Meets international safety and environmental standards, including CE, FCC, and RoHS.
Frequently Asked Questions
Q1: What is the typical lifespan of the 19421.0?
A1: The expected lifespan is over 10 years under normal operating conditions.
Q2: Is the 19421.0 compatible with existing hardware?
A2: Yes, it is backward-compatible with most current hardware interfaces and can be easily integrated into existing systems without major modifications.
Q3: In which specific scenarios would you recommend using the 19421.0?
A3: The 19421.0 is recommended for scenarios requiring high-speed data processing, such as real-time analysis in financial markets, deep learning model training, and high-resolution image processing in medical imaging.
Other people’s search terms
– High-performance computing components
– AI training accelerators
– Scientific research computing solutions
– Financial modeling hardware
– Big data analytics processors
