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 DLVM to support CUDA. What should you implement?
A.
Solid State Drives (SSD)
B.
Computer Processing Unit (CPU) speed increase by using overclocking
C.
Graphic Processing Unit (GPU)
D.
High Random Access Memory (RAM) configuration
E.
Intel Software Guard Extensions (Intel SGX) technology
CUDA is a parallel computing platform and application programming interface (API) developed by NVIDIA for general-purpose computing on graphics processing units (GPUs). CUDA allows developers to use the power of GPUs to accelerate the processing of data-intensive applications.
In order to use CUDA, a DLVM must have a GPU that is compatible with CUDA. The DLVM must also have the CUDA software installed.
The other options are not relevant to configuring a DLVM to support CUDA. SSDs can improve the performance of a DLVM, but they are not required for CUDA. Overclocking a CPU can improve its performance, but it is not necessary for CUDA. RAM is required for CUDA, but a high RAM configuration is not necessary. Intel SGX is a security technology that is not related to CUDA.
Therefore, the best option is to implement a GPU in the DLVM.
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