Scaling Distributed Machine Learning leveraging vSphere, Bitfusion and NVIDIA GPU (Part 1 of 2) - Virtualize Applications

Organization are quickly embracing Artificial Intelligence (AI), Machine Learning and Deep Learning to open new opportunities and accelerate business growth. AI Workloads, however, require massive compute power and has led to the proliferation of GPU acceleration in addition to traditional CPU power. This has led to a break in the traditional data center architecture and amplification of organizational silos, poor utilization and lack of agility. While virtualization technologies have proven themselves in the enterprise with cost effective, scalable and reliable IT computing, Machine Learning infrastructure however has not evolved and is still bound to dedicating physical resources to optimize and reduce training times. Bitfusion helps enterprises dis-aggregate the GPU compute and dynamically attach GPUs anywhere in the datacenter just like attaching storage.