Maximize Your Returns on AI/ML Investment

Adoption of Artificial intelligence and Machine learning (AI/ML) and its application to solve business problems is growing in leaps and bounds. According to a recent Gartner report, 48% of global CIOs will deploy AI by 2020. Manufacturing, Financial Services, Utilities, and many other industries are already applying AI/ML to drive value across their businesses, especially in process automation, improving customer experience, cost reduction, and revenue growth.

Companies aspiring to drive continual value through their AI/ML investments need to establish accuracy checkpoints on ML outcomes. Recent research suggests that model accuracy increases logarithmically based on the volume of the training data. Hence, data scientists require multiple terabytes of data to drive incremental improvements in model accuracy. This demands for a truly scalable AI infrastructure that can autonomously adapt to the new data. Data scientists also need to frequently retrain their ML models with this new and different datasets to improve their model’s predictive performance. These growing business expectations to frequently scale and retrain models results in expensive AI/ML infrastructure investments along with heavy compute resources. Choosing the right scalable AI/ML platform that is composed of CPUs and GPUs will help future-proof investments and maximize returns.


Diamanti ML Platform

Diamanti ML platform is the first bare metal enterprise platform with both GPU and CPU based support for running containerized AI/ML workloads on Kubernetes. This provides the flexibility for data scientists to accelerate model training with GPUs, and deploy analytics and any other CPU-optimized workloads to the same cluster. The Diamanti ML platform is a powerful combination of Diamanti Spektra, a prevalidated, pre-packaged and fully-featured software stack, Diamanti Ultima I/O acceleration cards, and Diamanti D20 series of modern hyperconverged platforms offering multiple configurations consisting of Intel CPUs, NVIDIA GPUs, memory, and NVMe storage.


Figure 1: AI/ML on Diamanti Platform


Diamanti G20 series

The Diamanti G20 series (G20T and G20P) is available in multiple configurations considering the demands of both training and inference as independent and unique workloads with different resource requirements. The G20 series combines the power of Diamanti Ultima, NVIDIA GPUs, and lightning-fast NVMe shared storage to provide a bare metal Kubernetes platform for data scientists to run ML workloads while maximizing resource utilization and return on investment.

Learn more about how Diamanti customers from the energy and services sector are benefiting significantly because of the Diamanti ML platform.


Figure 2: Diamanti G20 series


This brief demo provides an overview of how to deploy applications on Diamanti and easily manage a mix of G20 and D20X resources in a single cluster using the Diamanti Spektra Management Console.


Maximize Utilization and ROI with the Scalable Diamanti ML Platform

Diamanti ML platform provides the scalability and efficiency needed for running AI/ML workloads. With its flexible architecture, data scientists can adapt to the new data to improve model accuracy and insights. By using the processing power of NVIDIA GPUs alongside CPUs combined with Diamanti Ultima I/O acceleration cards and low-latency NVMe storage, the Diamanti ML platform provides a great way to optimize costs and maximize returns on your AI/ML investments.

To learn more about how Diamanti can help you supercharge your applications, register for the upcoming Supercharge Stateful Applications on Kubernetes webinar.