vSphere Bitfusion supports AI- and ML-based workloads by virtualizing hardware accelerators such as GPUs. Multi-vendor hardware accelerators and the ecosystem around them are key components for delivering modern applications. These accelerators can be used regardless of location in the environment.
vSphere Bitfusion decouples physical resources from servers within an environment. The platform can share GPUs in a virtualized infrastructure, as a pool of network-accessible resources, rather than isolated resources per server. Bitfusion works across AI frameworks, clouds, networks, and in environments such as virtual machines, containers, and notebooks. And Bitfusion stands ready to carry virtualization forward as new hardware accelerators are introduced.
Bitfusion disaggregates your GPU compute and dynamically attaches GPUs anywhere in the datacenter, just like attaching storage.
Bitfusion enables use of any arbitrary fractions of GPUs. Support more users in the test and development phase.
Leverage GPUs across an infrastructure plus integrate evolving technologies as standards emerge.
Bitfusion attaches GPUs based on CUDA calls at run-time, maximizing utilization of GPU servers anywhere in the network.
Bitfusion is a transparent layer and runs with any workload, framework, container or notebook.
The most advanced GPU virtualization technology to accelerate AI, ML and HPC.
vSphere Bitfusion connects any compute servers remotely, over the network to GPU servers pools while attaching and detaching GPUs. This virtualizes the GPUs, allowing multiple workloads to run in parallel. Bitfusion does for GPUs what vSphere did for CPUs.
vSphere Bitfusion Manager is the management tool which allows the administrator to Monitor health, utilization and efficiency and availability of all GPU servers in the network. The tool also provides viewing and monitoring of client consumption of GPUs, plus assigning quotas and time limits.