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footnotes: trim fn-mlperf (benchmarking) — remove three-suite recap that duplicated body prose

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Vijay Janapa Reddi
2026-02-24 08:52:03 -05:00
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book/quarto/contents/vol1/benchmarking/benchmarking.qmd
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@@ -342,7 +342,7 @@ DAWNBench [@coleman2017dawnbench] emerged as an early ML benchmark that pioneere
\index{Patterson, David!MLPerf leadership}
\index{MLCommons!benchmark organization}
[^fn-mlperf]: **MLPerf**: Founded in 2018 by researchers from Google, NVIDIA, Intel, Harvard, Stanford, and UC Berkeley, the name combines "ML" with "Perf" (performance), echoing SPEC's benchmarking tradition. MLPerf's design principles -- representative workloads, full-system measurement, and open submission -- directly address the gaming that plagued Whetstone and LINPACK. Its three suites (Training, Inference, Power) force vendors to report end-to-end numbers rather than cherry-picked kernel throughput. \index{MLPerf!founding}
[^fn-mlperf]: **MLPerf**: Founded in 2018 by researchers from Google, NVIDIA, Intel, Harvard, Stanford, and UC Berkeley, the name combines "ML" with "Perf" (performance), echoing SPEC's benchmarking tradition. MLPerf's design principles — representative workloads, full-system measurement, and open submission — directly address the gaming that plagued Whetstone and LINPACK: vendors who could previously report peak kernel throughput on cherry-picked problem sizes must now report end-to-end system performance on standardized tasks. \index{MLPerf!founding}
### Energy Benchmarks {#sec-benchmarking-energy-benchmarks-709a}