MLPerf

Apr 05, 2023

Setting New Records in MLPerf Inference v3.0 with Full-Stack Optimizations for AI

The most exciting computing applications currently rely on training and running inference on complex AI models, often in demanding, real-time deployment...
15 MIN READ
Nov 09, 2022

Tuning AI Infrastructure Performance with MLPerf HPC v2.0 Benchmarks

As the fusion of AI and simulation accelerates scientific discovery, the need has arisen for a means to measure and rank the speed and throughput for building...
14 MIN READ
Nov 09, 2022

Leading MLPerf Training 2.1 with Full Stack Optimizations for AI

MLPerf benchmarks, developed by MLCommons, are critical evaluation tools for organizations to measure the performance of their machine learning models' training...
14 MIN READ
Sep 08, 2022

Full-Stack Innovation Fuels Highest MLPerf Inference 2.1 Results for NVIDIA

Today’s AI-powered applications are enabling richer experiences, fueled by both larger and more complex AI models as well as the application of many models in...
14 MIN READ
Jun 30, 2022

The Full Stack Optimization Powering NVIDIA MLPerf Training v2.0 Performance

MLPerf benchmarks are developed by a consortium of AI leaders across industry, academia, and research labs, with the aim of providing standardized, fair, and...
14 MIN READ
May 11, 2022

Accelerating AI Inference Workloads with NVIDIA A30 GPU

NVIDIA A30 GPU is built on the latest NVIDIA Ampere Architecture to accelerate diverse workloads like AI inference at scale, enterprise training, and HPC...
6 MIN READ
Apr 06, 2022

Getting the Best Performance on MLPerf Inference 2.0

Models like Megatron 530B are expanding the range of problems AI can address. However, as models continue to grow complexity, they pose a twofold challenge for...
11 MIN READ
Mar 01, 2022

Saving Time and Money in the Cloud with the Latest NVIDIA-Powered Instances

AI is transforming every industry, enabling powerful new applications and use cases that simply weren’t possible with traditional software. As AI continues to...
9 MIN READ
Dec 01, 2021

Boosting NVIDIA MLPerf Training v1.1 Performance with Full Stack Optimization

Five months have passed since v1.0, so it is time for another round of the MLPerf training benchmark. In this v1.1 edition, optimization over the entire...
22 MIN READ
Data server room. Courtesy of Forschungszentrum Jülich/Sascha Kreklau.
Nov 17, 2021

MLPerf HPC v1.0: Deep Dive into Optimizations Leading to Record-Setting NVIDIA Performance

In MLPerf HPC v1.0, NVIDIA-powered systems won four of five new industry metrics focused on AI performance in HPC. As an industry-wide AI...
7 MIN READ
Sep 22, 2021

Furthering NVIDIA Performance Leadership with MLPerf Inference 1.1 Results

AI continues to drive breakthrough innovation across industries, including consumer Internet, healthcare and life sciences, financial services, retail,...
6 MIN READ
Jun 30, 2021

MLPerf v1.0 Training Benchmarks: Insights into a Record-Setting NVIDIA Performance

MLPerf is an industry-wide AI consortium tasked with developing a suite of performance benchmarks that cover a range of leading AI workloads widely in use. The...
31 MIN READ
Apr 22, 2021

Extending NVIDIA Performance Leadership with MLPerf Inference 1.0 Results

Inference is where we interact with AI. Chat bots, digital assistants, recommendation engines, fraud protection services, and other applications that you use...
7 MIN READ
Nov 23, 2020

Updating AI Product Performance from Throughput to Time-To-Solution

Data scientists and researchers work toward solving the grand challenges of humanity with AI projects such as developing autonomous cars or nuclear fusion...
9 MIN READ
Oct 21, 2020

Winning MLPerf Inference 0.7 with a Full-Stack Approach

Three trends continue to drive the AI inference market for both training and inference: growing data sets, increasingly complex and diverse networks, and...
8 MIN READ
Jul 29, 2020

Accelerating AI Training with MLPerf Containers and Models from NVIDIA NGC

The MLPerf consortium mission is to “build fair and useful benchmarks” to provide an unbiased training and inference performance reference for ML hardware,...
13 MIN READ