Question

A data science team runs a recommendation model that must score millions of user records nightly. They currently process records one at a time on a CPU, and the batch job takes far too long. An infrastructure engineer suggests moving the workload to a GPU and processing records in large batches. Fundamentally, why does the GPU deliver a large speedup for this type of workload?

Accepted Answer

GPUs execute the same operation across thousands of data elements simultaneously using many parallel cores, making them ideal for high-throughput batched numerical work

Answer

GPUs run each individual record faster than a CPU because each GPU core has a higher clock speed than a CPU core

Answer

GPUs automatically compress the dataset so less data needs to be processed overall

Answer

GPUs eliminate the need for batching by processing records strictly one at a time with lower latency than a CPU