Today, MLCommons announced new results for its industry-standard MLPerf Inference v4.1 benchmark suite, which delivers machine learning (ML) system performance benchmarking in an architecture-neutral, representative, and ….
Nvidia, AMD, Intel and Google Debut Chips in MLPerf Inference Benchmark for GenAI
August 28, 2024 by
Updated MLPerf AI Inference Benchmark Results Released
March 27, 2024 by
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….
Intel Gaudi 2 Remains Only Benchmarked Alternative to NV H100 for GenAI Performance
March 27, 2024 by
Newest MLPerf results for Intel Gaudi 2 accelerator and 5th Gen Intel Xeon demonstrate how Intel is raising the bar for generative AI performance across its portfolio and with its ecosystem partners.
MLPerf Training and HPC Benchmark Show 49X Performance Gains in 5 Years
November 8, 2023 by
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.
DDN Storage Solutions Deliver 700% Gains in AI and Machine Learning for Image Segmentation and Natural Language Processing
September 14, 2023 by
DDN®, a leader in artificial intelligence (AI) and multi-cloud data management solutions, announced impressive performance results of its AI storage platform for the inaugural AI storage benchmarks released this week by MLCommons Association. The MLPerfTM Storage v0.5 benchmark results confirm DDN storage solutions as the gold standard for AI and machine learning applications.
MLCommons: MLPerf Results Show AI Performance Gains
June 27, 2023 by
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 […]
Deci’s Natural Language Processing (NLP) Model Achieves Breakthrough Performance at MLPerf
September 12, 2022 by
Deci, the deep learning company harnessing Artificial Intelligence (AI) to build better AI, announced results for its Natural Language Processing (NLP) inference model submitted to the MLPerf Inference v2.1 benchmark suite under the open submission track.
MLCommons: Latest MLPerf AI Benchmark Results Show Machine Learning Inference Advances
September 8, 2022 by
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’
June 29, 2022 by
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 More Capable ML Training
June 29, 2022 by
Today, MLCommons®, an open engineering consortium, released new results from MLPerf™ Training v2.0, which measures the performance of training machine learning models. Training models empowers researchers to unlock new capabilities faster such as diagnosing tumors, automatic speech recognition or improving movie recommendations. 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 to benefit society at large.
