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An enterprise is designing a solution for training a large, custom Convolutional Neural Network (CNN) for a new computer vision application. Their data science team has determined that the training process will need to be distributed across multiple GPUs to be completed in a reasonable timeframe. The training process involves intensive matrix multiplication operations. The architect is specifying components from the HPE Private Cloud Al solution. Which infrastructure components are critical for accelerating this specific distributed training workload? (Select all that apply.)
A. The HPE Data Fabric software component.
B. NVIDIA GPUs featuring multiple Tensor Cores.
C. An NVIDIA NVLink Bridge to connect the GPUs.
D. HPE ProLiant DL325 servers for the worker nodes.
E. HPE GreenLake for File Storage with standard NFS over TCP/IP.

há 5 meses

há 5 meses

HPE2-B08 HPE Private Cloud AI Solutions Dumps

HPE2-B08 HPE Private Cloud AI Solutions Dumps

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Ed

há 5 meses

Para responder a essa pergunta, precisamos analisar quais componentes são críticos para acelerar o treinamento distribuído de uma rede neural convolucional (CNN) em um ambiente de computação em nuvem privada, especialmente considerando que o processo envolve operações intensivas de multiplicação de matrizes. Vamos analisar as opções: A. The HPE Data Fabric software component. - Embora o HPE Data Fabric possa ajudar na gestão de dados, não é especificamente crítico para acelerar o treinamento em si. B. NVIDIA GPUs featuring multiple Tensor Cores. - As GPUs da NVIDIA com Tensor Cores são projetadas para acelerar operações de aprendizado de máquina, especialmente multiplicações de matrizes, tornando-as essenciais para essa tarefa. C. An NVIDIA NVLink Bridge to connect the GPUs. - O NVLink permite uma comunicação mais rápida entre as GPUs, o que é crucial para o treinamento distribuído, pois melhora a eficiência da troca de dados. D. HPE ProLiant DL325 servers for the worker nodes. - Esses servidores são adequados para cargas de trabalho de aprendizado de máquina, mas a especificidade do modelo pode não ser tão crítica quanto as GPUs e a interconexão. E. HPE GreenLake for File Storage with standard NFS over TCP/IP. - Embora o armazenamento seja importante, a velocidade de treinamento é mais impactada pela capacidade de processamento e pela interconexão das GPUs. Com base nessa análise, as opções críticas para acelerar o treinamento distribuído de uma CNN são: B. NVIDIA GPUs featuring multiple Tensor Cores. C. An NVIDIA NVLink Bridge to connect the GPUs. Portanto, as respostas corretas são B e C.

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HPE2-B08 HPE Private Cloud AI Solutions Dumps

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