Many IT leaders are responding to executive pressure for artificial intelligence (AI) capabilities by increasing their organizations' AI investments into 2024. They recognize that successful AI is a complex challenge and will require all the help they can get.
Choosing the right AI system vendor (one with the right capabilities) won't solve all these problems. However, it has the potential to simplify achieving your AI goals.
IT leaders attending NVIDIA's GTC 2024 AI Developer Conference, March 18-21, 2024 in San Jose, California, will be joined by one of the world's leaders in high-performance AI servers based on NVIDIA's MGX Server Reference Architecture. You can explore these features with ASUS. ASUS servers leverage the latest NVIDIA advances in GPUs, CPUs, NVME storage, and PCIe Gen5 interfaces.
To succeed with AI, IT leaders need system vendors to do more than just plug the latest GPU processors into standard rack-mount servers. Here are his six key features that IT leaders should look for when choosing an AI system vendor for data center deployments.
1. Maximize performance
Look for servers with cutting-edge CPUs or GPUs optimized for AI workloads. Evaluate your processor to ensure it can meet the computing demands of your AI algorithms.
- ASUS midrange and high-range NVIDIA MGX servers incorporate the latest NVIDIA chip products, including the Grace Hopper superchip, GH200 Grace CPU superchip, and the complete NVIDIA GPU portfolio.
2. Maximize data storage
AI workloads require vast amounts of data. Evaluate vendor storage options such as SSD, HDD, and especially his NVMe drives. Consider capacity, speed, and scalability.
- ASUS AI Server leverages a range of high-performance storage options, including: Graid Technology's SupremeRAID is RAID software that is loaded onto GPU cards to maximize storage performance without consuming CPU cycles. Support for NVIDIA PCI Express Gen 3, 4, and 5 interfaces.
3. Consider scalability and flexibility
Look for an AI server solution that clearly scales both horizontally and vertically to accommodate growing AI workloads. Evaluate modular design, expansion options, and support for cloud-based or hybrid deployments.
- ASUS can tailor NVIDIA MGX-based servers to target an organization's initial AI pilots and quickly add compute and storage capacity as needed.
4. Understand your cooling options
AI computing servers generate a tremendous amount of heat compared to traditional servers. Assess the vendor's ability to cost-effectively and reliably minimize server heat output.
- ASUS has a variety of cooling options, from efficient air systems to direct liquid cooling to the chip to full immersion cooling.
5. Ask about AI framework support
Document vendor support for popular AI frameworks such as TensorFlow, PyTorch, and MXNet. Compatibility with these frameworks allows you to streamline your development and deployment workflows.
- In addition to supporting the NVIDA AI framework, ASUS has created its own no-code AI platform to accelerate AI development for organizations with large-scale language models (LLM) pre-training, fine-tuning, and inference.
6. Check reliability and support
Evaluate the vendor's reliability, quality, and customer support record. Look for a vendor with a reputation for providing robust, enterprise-grade server solutions and responsive technical support services.
- ASUS servers power some of the most demanding high-performance computing environments, including ASUS subsidiary Taiwan Web Service (TWSC). The company has 2,000 support centers in 200 countries.
For more information, please visit https://servers.asus.com/.