Updated MLPerf AI Inference Benchmark Results Released

Today, MLCommons announced new results from its MLPerf Inference v4.0 benchmark suite with machine learning (ML) system performance benchmarking. To view the results for MLPerf Inference v4.0 visit the Datacenter and Edge results pages. The MLPerf Inference….

MLPerf Training and HPC Benchmark Show 49X Performance Gains in 5 Years

MLCommons said the results highlight performance gains of up to 2.8X compared to 5 months ago and 49X over the first results five years ago, “reflecting the tremendous rate of innovation in systems for machine learning,” the organizations said. 

MLCommons: MLPerf Results Show AI Performance Gains

Today ML Commons announced new results from two industry-standard MLPerf benchmark suites: Training v3.0, which measures the performance of training machine learning models, and Tiny v1.1, which measures how quickly a trained neural network can process new data for extremely low-power devices in the smallest form factors. To view the results and to find additional […]

An AI-Flavored Set of HPC Predictions for 2023

We recently read an interesting article in Wired magazine on neuromorphic computing stating that neuroscientists increasingly regard the human brain is a “prediction machine,” that people, as a rule, are in a constant state of anticipation, extrapolation and inference. In HPC, situated as it is at the forward edge of compute power, data analysis and […]

MLCommons: Latest MLPerf AI Benchmark Results Show Machine Learning Inference Advances

SAN FRANCISCO – September 8, 2022 – Today, the open engineering consortium MLCommons announced results from MLPerf Inference v2.1, which analyzes the performance of inference — the application of a trained machine learning model to new data. Inference allows for the intelligent enhancement of a vast array of applications and systems. Here are the results and […]

MLPerf: Latest Results Highlight ‘More Capable ML Training’

Open engineering consortium MLCommons has released new results from MLPerf Training v2.0, which measures how fast various platforms train machine learning models. The organizations said the latest MLPerf Training results “demonstrate broad industry participation and up to 1.8X greater performance ultimately paving the way for more capable intelligent systems….” As it has done with previous […]

MLPerf Results Highlight Advances in Machine Learning Inference Performance and Efficiency

SAN FRANCISCO – April 6, 2022 – Today MLCommons, an open engineering consortium, released new results for three MLPerf benchmark suites – Inference v2.0, Mobile v2.0, and Tiny v0.7. MLCommons said the three benchmark suites measure the performance of inference – applying a trained machine learning model to new data. Inference enables adding intelligence to a wide range […]

MLPerf Releases Results for HPC v1.0 ML Training Benchmark

Today, MLCommons released new results for MLPerf HPC v1.0, the organization’s machine learning training performance benchmark suite for high-performance computing (HPC). To view the results, visit https://mlcommons.org/en/training-hpc-10/. NVIDIA announced that NVIDIA-powered systems won four of five MLPerf HPC 1.0 tests, which measures training of AI models in three typical workloads for HPC centers: CosmoFlow estimates details […]

MLCommons Releases MLPerf Inference v1.1 Results 

San Francisco – September 22, 2021 – Today, MLCommons, an open engineering consortium, released new results for MLPerf Inference v1.1, the organization’s machine learning inference performance benchmark suite. MLPerf Inference measures the performance of applying a trained machine learning model to new data for a wide variety of applications and form factors, and optionally includes […]

MLCommons Launches MLPerf Tiny AI Inference Benchmark

Today, open engineering consortium MLCommons released a new benchmark, MLPerf Tiny Inference to measure trained neural network AI inference performance for low-power devices in small form factors. MLPerf Tiny v0.5 is MLCommons’s first inference benchmark suite for embedded device machine learning, a growing field in which AI-driven sensor data analytics is performed in real-time, close […]