IBM Extends GPU Cloud Capabilities, Targets Machine Learning

As we have noted over the last year in particular, GPUs are set for another tsunami of use cases for server workloads in high performance computing and most recently, machine learning. As GPU maker Nvidia's CEO stressed at this year's GPU Technology Conference, deep learning is a target market, fed in part by a new range of their GPUs for training and executing deep neural networks, including the Tesla M40, M4, the existing supercomputing-focused K80, and now, the P100 (Nvidia's latest Pascal processor, which is at the heart of a new appliance specifically designed for deep learning workloads). While we have heard a great deal over the last year from companies like Baidu, Flickr, and others, on-premises GPU-laden systems are the key to training deep neural nets, but according to IBM, there will be a new wave of users who want to circumvent the on-site boxes and take advantage of GPUs on IBM's cloud. While cloud rival Amazon Web Services, among others, are sporting GPU cards for high performance computing (HPC) and deep learning users, the partnership between Nvidia and IBM is giving Big Blue a leg up in terms of making a wider array of GPUs available to suit different workloads. Currently, IBM's cloud boasts the K80, as well as the lower power and less beefy K10.