VMware Innovations to Accelerate the Adoption of AI and Machine Learning
VMware today announced innovations to accelerate the adoption of artificial intelligence (AI) and machine learning (ML) technologies for businesses as they pivot towards Malaysia’s growing innovation economy. With Bitfusion Technology integrated into VMware vSphere 7, organizations will have access to elastic infrastructure on-demand to support the increasing adoption of emerging technologies for growth in Malaysia’s digital future. This new feature – VMware vSphere Bitfusion – is developed out of VMware’s 2019 acquisition of Bitfusion, a pioneer in the virtualization of hardware accelerator resources including graphics processor unit (GPU) technology.
“We aim to deliver the same value to GPUs that we delivered for CPUs,” said Krish Prasad, senior vice president and general manager, Cloud Platform Business Unit, VMware. “By breaking down existing silos of GPU resources, organizations will be able to achieve better utilization and efficient use of them through sharing – resulting in immediate cost savings. More importantly, organizations will be able to jumpstart new or stalled AI/ML initiatives to drive their business forward by sharing those GPU resources with their teams on-demand with VMware vSphere 7.”
“Organizations in Malaysia are excited about the growth prospects its flourishing digital economy brings. Many of them are now turning to AI and ML to automate, streamline and catalyze business innovations to unlock growth,” said Devan Parinpanayagam, Country Manager, VMware Malaysia. “With the enhancements to VMware vSphere 7, businesses will have a powerful tool that enables them to harness emerging technologies to drive their growth towards a future that is digital.”
VMware vSphere 7 with Bitfusion Enables Efficient GPU Pooling and Sharing
AI and ML-based applications – deep learning training in particular – rely on hardware accelerators to tackle large and complex computation. With the newly integrated Bitfusion capabilities, VMware vSphere 7 will enable enterprises to pool their powerful GPU resources on their servers and share them within their data centers. That will enable organizations to efficiently and rapidly share GPUs across the network with teams of AI researchers, data scientists and ML developers relying on and/or building AI/ML applications.
Released in April 2020, VMware vSphere 7 was rearchitected into an open platform using Kubernetes to provide a cloud-like experience for developers and operators. The Bitfusion feature of VMware vSphere 7 will leverage GPUs for applications running in virtual machines or containers. Bitfusion can operate in a Kubernetes environment such as VMware Tanzu Kubernetes Grid, and is expected to run side-by-side as customers deploy AI/ML applications as part of an overall modern applications strategy. The Bitfusion feature of VMware vSphere will be available through a single download with no disruption to current infrastructure and will seamlessly integrate with existing workflows and lifecycles.
VMware completed the acquisition of Bitfusion last year with an intention to integrate the technology into VMware vSphere. Bitfusion offered a software platform that decoupled specific physical resources from the servers they are attached to in the environment. This included sharing GPUs in a virtualized infrastructure, as a pool of network-accessible resources, rather than isolated resources per server. Additionally, the platform supported other accelerators like FPGAs and ASICs. With this launch, Bitfusion will add these differentiated capabilities to the already existing support for GPUs in VMware vSphere.