When it comes to data infrastructure, AI workflows are not just any old workflows. Storage and memory play a pivotal role in ensuring smooth data flow to GPUs which power AI tasks, and local storage cache solutions accelerate data access and prevent bottlenecks, maintaining efficient AI operations. What’s more, for AI use cases, advanced memory solutions help feed training data into High Bandwidth Memory (HBM) on GPUs, enabling faster and more accurate AI applications such as image classification and voice recognition. Due to these unique demands of AI workflows, choosing the right servers is crucial for AI deployments.
Despite the focus on CPUs and GPUs, the importance of AI storage and memory is often underestimated. Simply put, these components determine how swiftly AI models process data, and are not to be overlooked. For example, AI applications in computer vision, like facial recognition, rely on high-bandwidth, low-latency memory to handle large data volumes in real-time. Similarly, natural language processing requires seamless data flow to avoid delays in AI-driven assistants. When AI storage solutions are optimized there is a lot to be gained, as they can reduce AI model training time, lower costs, and enhance inferencing accuracy across key areas like computer vision and natural language processing.
To optimize configurations and minimize risk, testing in an innovation lab is essential. Labs like the ECS Innovation Center allow rigorous evaluation of experimental use cases like those utilizing AI cloud storage under various workloads before deployment. This is how ECS provides high-performance server solutions designed for AI workloads, ensuring data centers can achieve these efficiencies. Want a peek at just how tests on new technologies like AI accelerators perform against legacy systems? Learn all about it and much more in an exclusive AI storage webinar hosted by ECS in collaboration with Micron.
Entitled The Importance of Storage in AI Infrastructure and featuring industry leaders Andrew Mierau from Micron Technology and Patrick Pedroso from ECS, this is where you can discover how to supercharge your AI deployments. In the webinar, you’ll dive deep into the topic of how to accelerate progress with AI storage and memory, unpacking new server memory hierarchies, AI storage configurations, and the critical role of memory in AI inferencing and training. With use cases spanning deep learning, generative AI, language processing, and computer vision, this session is packed with actionable takeaways.
Explore cutting-edge insights into AI data storage, memory, and hardware innovation to optimize your AI workflows! Take the first step toward building the AI infrastructure of tomorrow by watching the video below:
