Exam NCA-GENM Topic 1 Question 90 Discussion

Actual exam question for NVIDIA's NCA-GENM exam
Question #: 90
Topic #: 1

You are tasked with deploying a generative A1 model for image inpainting using Triton Inference Server. The model requires significant GPU memory and you want to maximize throughput. Which Triton configuration parameters would be MOST important to tune, and why?

A. 'instance_group' (setting count to the number of available GPUs) and (setting a high value to accumulate requests). B. 'instance_group' (setting count to the number of available GPUs and kind to KIND_GPU) and (increasing it to the largest value that fits in GPU memory). C. 'dynamic_batching' (enabling it and setting and 'model_warmup' (specifying dummy inputs to pre-load the model). D. 'optimization' (setting strategy to TRT to enable TensorRT optimization) and 'input_shape' (specifying the exact input shape). E. Both B and C.

Suggested Answer: E Vote an answer

'instance_group' with 'KIND_GPIY assigns the model to specific GPUs. Increasing (B) leverages GPU parallelism. Enabling 'dynamic_batching' and setting (C) allows Triton to dynamically batch requests to maximize throughput. Model warmup reduces first request latency. (A) is incomplete (missing KIND_GPU). (D) is relevant for latency optimization but not as crucial for throughput in a memory-constrained scenario. Therefore both B and C are most crucial in optimizing throughput while dealing with memory constraint.

by Dominic at Jun 30, 2025, 10:10 AM

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