Principled Technologies Studies the Potential of Dell PowerEdge R750 Servers with NVIDIA GPUs and VMware vSphere with Tanzu for Deep Learning Workloads
Combining containerization and GPU acceleration, this solution delivered strong image-classification performance at two different container counts.
Durham, NC, March 15, 2023 --(PR.com)-- Organizations increasingly rely on machine learning (ML) and other types of artificial intelligence to solve business problems. By using VMware vSphere with Tanzu containerized environments, they can rapidly scale and robustly deploy their ML applications. For the most computationally demanding workloads—such as AI applications—combining containers with GPUs, which can process multiple computations simultaneously, is an excellent choice. With virtualized GPU hardware, multiple containers can share GPU resources when appropriate for the workload. Using many smaller vGPU slices offers flexibility advantages for smaller jobs, while larger jobs can make good use of the dedicated memory and compute of a whole GPU.
Principled Technologies used ResNet-50—a deep learning image classification workload—on a Dell PowerEdge R750 server with an NVIDIA A100 Tensor Core GPU running VMware vSphere with Tanzu. According to its test report, “Using GPU virtualization to allow 10 containers to share the single GPU, our test solution achieved a maximum of 29,896 samples per second. With a single container using all of the GPU resources and a larger batch size, the solution achieved a maximum of 34,352 samples per second. These results show that the PowerEdge R750 with an NVIDIA A100 Tensor Core GPU in a VMware Kubernetes environment with GPU virtualization can support flexibly apportioning GPU compute capability across multiple machine learning workloads in Kubernetes clusters.”
To learn more, read the report at https://facts.pt/Hi5jvB2 or view the infographic at https://facts.pt/4Sg78CZ.
About Principled Technologies, Inc.
Principled Technologies, Inc. is the leading provider of technology marketing and learning & development services.
Principled Technologies, Inc. is located in Durham, North Carolina, USA. For more information, please visit www.principledtechnologies.com.
Principled Technologies used ResNet-50—a deep learning image classification workload—on a Dell PowerEdge R750 server with an NVIDIA A100 Tensor Core GPU running VMware vSphere with Tanzu. According to its test report, “Using GPU virtualization to allow 10 containers to share the single GPU, our test solution achieved a maximum of 29,896 samples per second. With a single container using all of the GPU resources and a larger batch size, the solution achieved a maximum of 34,352 samples per second. These results show that the PowerEdge R750 with an NVIDIA A100 Tensor Core GPU in a VMware Kubernetes environment with GPU virtualization can support flexibly apportioning GPU compute capability across multiple machine learning workloads in Kubernetes clusters.”
To learn more, read the report at https://facts.pt/Hi5jvB2 or view the infographic at https://facts.pt/4Sg78CZ.
About Principled Technologies, Inc.
Principled Technologies, Inc. is the leading provider of technology marketing and learning & development services.
Principled Technologies, Inc. is located in Durham, North Carolina, USA. For more information, please visit www.principledtechnologies.com.
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Principled Technologies, Inc.
Sharon Horton
828-455-0312
https://www.principledtechnologies.com
Sharon Horton
828-455-0312
https://www.principledtechnologies.com
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