Certification program expands to workstations, offers best performance for Cloudera Data Platform.
Enterprises challenged with running accelerated workloads have an answer: NVIDIA-Certified Systems. Available from nearly 20 global computer makers, these servers have been validated for running a diverse range of accelerated workloads with optimum performance, reliability and scale.
Now NVIDIA-Certified Systems are expanding to the desktop with workstations that undergo the same testing to validate their ability to run GPU-accelerated applications well.
Certification ensures that these systems, available as desktop or laptop models, have a well-balanced design and the correct configurations to maximize performance. GPUs eligible for certification in the workstations include the newest NVIDIA RTX A6000, A5000 and A4000, as well as the RTX 8000 and 6000.
NVIDIA-Certified workstations will join a lineup of over 90 already available systems that range from the highest performance AI servers with the NVIDIA HGX A100 8-GPU, to enterprise-class servers with the NVIDIA A30 Tensor Core GPU for mainstream accelerated data centers, to low-profile, low-power systems designed for the edge with NVIDIA T4 GPUs.
Certified Systems to Accelerate Data Science on CDP
Cloudera Data Platform (CDP) v7.1.7, which went into general availability last week, now takes advantage of NVIDIA-Certified Systems. This latest version adds RAPIDS to accelerate data analytics, ETL and popular data science tools like Apache Spark with NVIDIA GPUs to churn through massive data operations.
Testing has shown that this version of CDP runs up to 10x faster on servers with NVIDIA GPUs vs. non-accelerated servers. To make it easy to get started, NVIDIA and Cloudera recommend two NVIDIA-Certified server configurations that customers can purchase from several vendors:
- CDP-Ready: For running Apache Spark, a CDP-Ready configuration of NVIDIA-Certified servers with two NVIDIA A30 GPUs per server offers over 5x the performance at less than 50 percent incremental cost relative to modern CPU-only alternatives.
- AI ready: For customers additionally running machine learning or other AI-related applications, the NVIDIA A100 GPU provides even more performance — as well as acceleration on machine learning and AI training.
Data scientists often develop and refine machine learning and deep learning models on workstations to augment data center resources or help minimize cloud-based compute costs. By using an NVIDIA-Certified workstation, they can transition their work to NVIDIA-Certified servers when it’s time for larger scale prototyping and eventually production, without having to port to a different tool or framework.
New White Paper Describes Value of Certification
When it comes to installing GPUs and SmartNICs in a system, choosing the right server or workstation model and correctly configuring the components and firmware are critical to getting the most out of the investment.
With NVIDIA-Certified Systems, NVIDIA and its partners have already done the work of validating that a particular system is capable of running accelerated workloads well, and they’ve figured out the most optimal hardware configuration.
Misconfiguration can lead to poor performance and even inability to function properly or complete tasks. The certification process ensures that issues such as these are surfaced and resolved for each tested system. We’ve described this and more in a new white paper, Accelerate Compute-Intensive Workloads with NVIDIA-Certified Systems.
Our system partners run a suite of more than 35 tests designed by NVIDIA based on our vast experience with compute, graphics and network acceleration. Each of the tests is chosen to exercise the hardware of the system in a unique and thorough manner, so as many potential configuration issues as possible can be exposed. Some of the tests focus on a single aspect of the hardware, while others stress multiple components, both simultaneously as well as in a multi-step workflow.
With NVIDIA-Certified Systems, enterprises can confidently choose performance-optimized hardware to power their accelerated computing workloads — from the desktop to the data center to the edge.
Learn more about NVIDIA-Certified Systems:
