AI0-001 AI Infrastructure and Technologies Practice Question
A data scientist needs to train a deep learning model on a large image dataset. Which hardware is most suitable for parallel matrix operations and faster training compared to a CPU?
⚠ Common exam trap
CompTIA often tests the misconception that a TPU is always the best choice for deep learning, but the trap here is that the question specifies 'parallel matrix operations' and 'faster training compared to a CPU' without limiting the framework to TensorFlow, making the GPU the most universally suitable and correct answer.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
GPU with thousands of CUDA cores
A GPU with thousands of CUDA cores is the most suitable hardware for parallel matrix operations because deep learning training involves massive matrix multiplications and tensor operations that can be decomposed into thousands of independent threads. CUDA cores execute these threads in a massively parallel SIMT (Single Instruction, Multiple Thread) fashion, achieving significantly higher throughput than a CPU for such workloads, which leads to faster training times.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
GPU with thousands of CUDA cores
Why this is correct
GPUs excel at parallel matrix multiplications, drastically reducing training time for deep learning models.
- ✗
TPU designed for TensorFlow
Why it's wrong here
TPUs are also highly efficient for training, but GPUs are more universally adopted and the question does not specify TensorFlow usage.
- ✗
CPU with high clock speed
Why it's wrong here
CPUs are optimized for sequential tasks and cannot match the parallel throughput needed for large-scale neural network training.
- ✗
FPGA for reconfigurable logic
Why it's wrong here
FPGAs are used for low-latency inference, not typically for training large models.
About these practice questions
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JA
Written by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
This AI0-001 practice question is part of Courseiva's free CompTIA certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the AI0-001 exam.