NVIDIA Hopper H100 & L4 Ada GPUs Achieve Record-Breaking Performance In MLPerf AI Benchmarks
NVIDIA has just unveiled some record-breaking performances of its Hopper H100 & L4 Ada GPUs within MLPerf AI benchmarks.
Today, NVIDIA is presenting its latest figures achieved within MLPerf Interface 3.0. The three main highlights are the latest Hopper H100 records which show the progress of the flagship AI GPU over the past 6 months with several software optimizations, we also get to see the first results of the L4 GPU based on the Ada graphics architecture which was announced at GTC 2023 and lastly, we have updated results of the Jetson AGX Orin which gets much more faster thanks to similar software and platform power-level optimizations. To sum up, the following are the highlights that we are going to look at today:
For today's benchmark suite, NVIDIA will be taking a look at MLPerf Inference v3.0 which retains the same workloads which were used 6 months ago in prior submissions but the network environment has been added which accurately measures how data is sent into an inferencing platform to get the work done. NVIDIA also reveals that over a product's lifespan, the company can squeeze out almost 2x the performance through software optimizations, and that has already been seen on past GPUs such as the Ampere A100.
Starting with the Hopper H100 performance tests, we see the MLPerf inference tests in offline and server categories. The Offline benchmarks show up to a 4.5x performance increase over Ampere A100 (BERT 99.9%) while in the Server scenario, the H100 yields an impressive 4.0x performance jump over its predecessor.
To achieve this level of performance, NVIDIA is using FP8 performance through its transformer engine that is embedded within the Hopper architecture. It works on a per-layer basis by analyzing all of
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