Since launching their organization early last year, the MLPerf group has been slowly and steadily building up the scope and the scale of their machine learning benchmarks. Intending to do for ML performance what SPEC has done for CPU and general system performance, the group has brought on board essentially all of the big names in the industry, ranging from Intel and NVIDIA to Google and Baidu. As a result, while the MLPerf benchmarks are still in their early days – technically, they’re not even complete yet – the group’s efforts have attracted a lot of interest, which vendors are quickly turning into momentum.
Back in June the group launched its second – and arguably more interesting – benchmark set, MLPerf Inference v0.5. As laid out in the name, this is the MLPerf group’s machine learning inference benchmark, designed to measure how well and how quickly various accelerators and systems execute trained neural networks. Designed to be as much a competition as it is a common and agreed upon means to test inference performance, MLPerf Inference is intended to eventually become the industry’s gold standard benchmark for measuring inference performance across the spectrum, from low-power NPUs in SoCs to dedicated, high-performance inference accelerators in datacenters. And now, a bit over 4 months after the benchmark was first released, the MLPerf group is releasing the first official results for the inference benchmark.
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