At VMWorld 2018 US, Get Ready for Bitfusion’s The Need for Elastic Artificial Intelligence Infrastructure
Bitfusion Is Joining VMWorld to Present the Session at VMWorld 2018 US, with Focus on Artificial Intelligence, Machine Learning and Analytics Adoption That Drives Increased Demand for Flexible Virtual Infrastructure
Bitfusion, the Elastic Artificial Intelligence (AI) software company, along with VMware, is presenting a session at VMworld 2018 US. The session, titled The Need for Elastic Artificial Intelligence Infrastructure, focuses on elastic AI infrastructure on vSphere. It will highlight how Bitfusion’s elastic AI infrastructure combines with VMWare vSphere to enable network-attached virtual GPU and FPGA deployment from a shared pool, which, in turn, enables real-time response to machine learning workload demand.
The four-day conference, VMworld 2018 US will take place 26 August 2018 to 30 August 2018, at Mandalay Bay in Las Vegas, Nevada. The Bitfusion breakout session will take place on 27 August 2018 from 2.30 pm – 3.30 pm.
“We are delighted to partner with VMware and deliver GPU virtualization and AI Attached Network. VMware is a leader in compute, storage and networking virtualization. Now through the partnership with Bitfusion, Machine Learning, AI, GPUs and FPGAs can also be virtualized and designed as a composable resource,” wrote Michael Zimmerman , CEO of Bitfusion, in a company blog post.
Talking about the collaboration by VMWare vSpehere, Zimmerman adds, “As enterprises look to support more applications and users due to the adoption of artificial intelligence, analytics and machine learning strategies, they require flexible technologies that deliver high performance while maintaining costs savings. The combination of Bitfusion Elastic AI with VMWare vSphere delivers a unique solution that increases productivity, profitability, CapEx, OpEx and agility.”
Bitfusion creates a virtual elastic GPU cluster from all of the scattered deployed GPU servers in an enterprise. With Bitfusion software, each physical GPU can be partitioned into multiple flexible and elastic virtual GPUs. Any user, framework and computer server can attach instantaneously to a remote fractional GPU, single GPU or group of GPUs in the virtual cluster, run the AI code and then detach. Bitfusion virtualizes the capacity and location of GPUs and makes them accessible to any compute machine in the network.