You plan to use .a Deep learning Virtual Machine (DLVM) to train deep learning models using Compute Unified Device Architecture (CUDA) computations. You need to configure the IXVM to support CUOA…

The correct answer is C. Graphic Processing Unit (GPU). CUDA (Compute Unified Device Architecture) is NVIDIA's parallel computing platform and API that runs exclusively on GPU (Graphics Processing Unit) hardware. A Deep Learning Virtual Machine requires GPU instances to execute CUDA kernels for accelerated model training. Intel SGX…

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Question

You plan to use .a Deep learning Virtual Machine (DLVM) to train deep learning models using Compute Unified Device Architecture (CUDA) computations. You need to configure the IXVM to support CUOA. What should you implement?

Options

AIntel Software Guard Extensions (Intel SGX) technology
BSolid State Drives (SSD)
CGraphic Processing Unit (GPU)
DComputer Processing Unit (CPU) speed increase by using overcloking
EHigh Random Access Memory (RAM) configuration

How the community answered

(33 responses)

A
3% (1)
B
3% (1)
C
94% (31)

Explanation

CUDA (Compute Unified Device Architecture) is NVIDIA's parallel computing platform and API that runs exclusively on GPU (Graphics Processing Unit) hardware. A Deep Learning Virtual Machine requires GPU instances to execute CUDA kernels for accelerated model training. Intel SGX is a security technology for protecting code execution in enclaves. SSDs improve storage I/O speed. CPU overclocking increases general compute throughput but cannot run CUDA workloads. High RAM improves memory capacity but does not enable CUDA. Only a GPU provides the CUDA-capable cores required.

Topics

#Deep Learning#GPU#CUDA#Virtual Machine

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