Which NVIDIA parallel computing platform and programming model allows developers to program in popular languages and express parallelism through extensions?

The correct answer is A. CUDA. CUDA (Compute Unified Device Architecture) is NVIDIA's foundational parallel computing platform and programming model. It enables developers to harness GPU parallelism by extending popular languages such as C, C++, and Fortran with parallelism-specific constructs (e.g., kernel…

NVIDIA AI Platform and Ecosystem

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Options

ACUDA
BCUML
CCUGRAPH

How the community answered

(28 responses)

A
89% (25)
B
4% (1)
C
7% (2)

Explanation

CUDA (Compute Unified Device Architecture) is NVIDIA's foundational parallel computing platform and programming model. It enables developers to harness GPU parallelism by extending popular languages such as C, C++, and Fortran with parallelism-specific constructs (e.g., kernel launches, thread management). CUDA also provides bindings for languages like Python (via libraries like PyCUDA), making it versatile for a wide range of developers. In contrast, CUML and CUGRAPH are higher-level libraries built on CUDA for specific machine learning and graph analytics tasks, not general-purpose programming models.

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#CUDA#Parallel Computing#Programming Model#NVIDIA Platform

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