Nvidia Hopper H100 GPU and DGX systems

Nvidia H100 ‘Hopper’ Benchmark Outcomes Revealed

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MLCommons, an {industry} group specializing in synthetic intelligence efficiency analysis and machine studying {hardware}, has added outcomes of the most recent synthetic AI and ML accelerators to its database and basically printed the primary efficiency numbers for Nvidia’s H100 and Biren’s BR104 compute GPUs obtained by way of an industry-standard set of checks. The outcomes have been in contrast towards these obtained on Intel’s Sapphire Rapids, Qualcomm’s AI 100, and Sapeon’s X220. 

MLCommons’ MLPerf is a set of coaching and inference benchmarks which are acknowledged by tens of corporations that again the organizations and submit take a look at outcomes of their {hardware} to the MLPerf database. The MLPerf Inference model 2.1 set of benchmarks contains datacenter and edge utilization situations in addition to such workloads as picture classification (ResNet 50 v1.5), pure language processor (BERT Massive), speech recognition (RNN-T), medical imaging (3D U-Internet), object detection (RetinaNet), and suggestion (DLRM). 

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