Q: 14
You are tasked with optimizing an AI-driven financial modeling application that performs both
complex mathematical calculations and real-time data analytics. The calculations are CPU-intensive,
requiring precise sequential processing, while the data analytics involves processing large datasets in
parallel. How should you allocate the workloads across GPU and CPU architectures?
Options
Discussion
Option C, CPUs have better sequential processing for the math, GPUs are way faster with parallel data analytics.
Makes sense to go with C here. CPUs handle the complex math part better, GPUs are just built for those huge parallel data analytics loads.
I don’t think D is right, I’d stick with B.
C tbh, D is tempting but CPUs are made for sequential workloads and that's the trap here.
C , lot of folks get trapped picking D but CPUs are still king for sequential math.
Its C
Looks like C. CPUs are better for complex, sequential math (trap is thinking GPUs always win). GPUs handle parallel data analytics best.
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