vmware horizon client 5.5.1 download for windows 10

On vGPUs that use the best-effort scheduler, the FRL can be disabled asĮxplained in the release notes for your chosen hypervisor at NVIDIA AI Enterprise Documentation.īefore you begin, ensure that the following For details, see Changing Scheduling Behavior for Time-Sliced vGPUs. Scheduling behavior is changed from the default best-effort scheduler on GPUs that supportĪlternative vGPU schedulers. Rate in frames per second (FPS) for C-series vGPUs to 60 FPS.īy default, the FRL is enabled for all GPUs. When enabled, the frame-rate limiter (FRL) limits the maximum frame VGPUs, but only 2 A16-8C vGPUs, for a total of 8 vGPUs. For example, an NVDIA A16īoard can support up to 4 A16-4C vGPUs on each of its two physical GPUs, for a total of 16 Simultaneously on a physical GPU varies according to the vGPU type. For example, a vGPU of type A16-4C isĪllocated 4096 Mbytes of frame buffer on an NVIDIA A16 board.ĭue to their differing resource requirements, the maximum number of vGPUs that can be created

The number after the board type in the vGPU type name denotes the amount of frameīuffer that is allocated to a vGPU of that type. Learning, or high-performance computing (HPC) 1, 2 This provides communication between GPU memory and storage across a cluster for improved performance.Ĭompute-intensive server workloads, such as artificial intelligence (AI), deep Additionally, technologies like GPUDirect Communications can Run AI workloads at near bare-metal performance with new optimizations for GPU acceleration on vSphere, including supportįor the latest Ampere architecture including the NVIDIA A100. Scaling with bare metal performance in a fully virtualized environment was limited to a single node, limiting the complexityĪnd size of AI workloads that could be supported.

Scale out to multiple nodes, enabling even the largest deep learning training models to run on the VMware vSphere. Leverage the jointly certified NVIDIA and Red Hat solution to deploy and manage AI workloads in containers or VMs with optimized GPU-accelerated instances in the public cloud.

NVIDIA-Certified Systems configured with or without GPUs, and on Run NVIDIA AI frameworks and tools optimized for GPU acceleration, reducing deployment time and ensuring reliable performance.ĭeploy anywhere – including on popular data center platforms from VMware and Red Hat, mainstream Leverage fully integrated, optimized, certified, and supported software from NVIDIA for AI workloads.

Vmware horizon client 5.5.1 download for windows 10