Microsoft’s newest project, code named Project Olympus, is making a big buzz in the Silicon Valley community as it hopes to address these computing stumbling blocks in the way of many companies’ growing successes.
In a blog post by Microsoft, said that the project was made to improve “cloud services and computing power needed for advanced and emerging cloud workloads such as big data analytics, machine learning, and Artificial Intelligence (AI).”
In concurrence with Project Olympus, NVIDIA has unveiled blueprints for a new hyperscale GPU accelerator to drive AI cloud computing. The GPU accelerator chassis for AI, HGX-1, is designed to support eight of the latest “Pascal” generation NVIDIA GPUs and NVIDIA’s NVLink high speed multi-GPU interconnect technology.
The highly modular design of the HGX-1 allows for optimal performance no matter the workload. It provides up to 100x faster deep learning performance compared with legacy CPU-based servers, and is estimated at one-fifth the cost for conducting AI training and one-tenth the cost for AI inferencing.
It is important to note that this is the first (Open Compute Project)OCP server design to offer a broad choice of microprocessor options.
