MLPerf

Building fair, useful, industry-standard benchmarks for ML training and inference performance of hardware, software, and services from TinyML to supercomputers

[MLCommons @MLCommons]

We've just released @MLPerf Mobile version 5.0.2 on the Google Play Store and GitHub. This version adds support for devices based on the Samsung Exynos 2500 SoC.

https://t.co/715ENpUz6w

[MLCommons @MLCommons]

@MLCommons & @AVCConsortium announce @MLPerf Automotive v0.5 benchmark results—a major step for transparent, reproducible automotive AI performance data. https://t.co/Bt89S9JgCG

[MLPerf @MLPerf]

@zhentan We prefer Tekken, @TheKanter happens to be quite fond of it from his college days!

[MLPerf @MLPerf]

@sandyasm @JeffDean @matei_zaharia @NaveenGRao @HazyResearch @DrJimFan You should reach out to @TheKanter if you are interested!

[MLPerf @MLPerf]

@SwayStar123 @EMostaque @intel @HabanaLabs The dataset for MLPerf Stable Diffusion is ~6M images, and is likely smaller than what @EMostaque uses in production training.

[HPCwire @HPCwire]

Guess who was named an AI inference leader in the latest @MLPerf results released by MLCommons?

[David Kanter @TheKanter]

On a personal level, I loved seeing .@MLPerf being mentioned so much! I can’t wait to see more submissions from across the industry as we push for the next 1000x in machine learning performance.

[Nutanix Inc. @nutanix]

@MLCommons @MLPerf The Perf Storage Benchmark Suite will be a critical resource in improving machine learning and we’re honored to have participated alongside these industry leaders and academic organizations!

[Sean Kerner @TechJournalist]

Inference keeps getting faster ... and more demanding. @MLCommons
MLPerf Inference 3.1 adds large language model benchmarks for inference https://t.co/YMWwHZKrij via @VentureBeat

"“We’re evolving the benchmark suite to reflect what’s going on,” @TheKanter said.

[MLCommons @MLCommons]

@MLCommons, we just released! New @MLPerf Inference and Storage results. Record participation in MLPerf Inference v3.1 and first-time MLPerf Storage v0.5 results highlight the growing importance of GenAI and storage. See all the results and learn more https://t.co/7eycrrmOdw

[Intel Capital @intelcapital]

AI semiconductor company @Syntiantcorp announced its Syntiant Core 2™ programmable #deeplearning #architecture ranked as utilizing the lowest power #energy across three categories in @MLCommons @MLPerf Tiny v1.1 benchmark suite. Read more about energy performance below:

[MLCommons @MLCommons]

If you are at the @databricks Data+AI Summit this week be sure to check out @MLCommons Exec Director @TheKanter's session - Advancing ML Through Benchmarks & Data, Thursday, June 29 at 2:30pm
https://t.co/k4ge9Bpyic

[MLPerf @MLPerf]

@braindersnn Maybe you should move the party over to .@MLCommons…I hear they are pretty nice!

[MLCommons @MLCommons]

Calling all ISC attendees, stop by the @MLPerf roundtable 5/24 at 9am, Hall E - 2nd floor, to learn more about the MLPerf HPC benchmark suite V3.0 from the experts who created it. #mlcommons #MachineLearning #ISC23

[MLPerf @MLPerf]

Can you train a large language model? We’re adding GPT3 to MLPerf Training v3.0, so show us what you’ve got in Q2! Let the games begin 🥳🎉🎈🎊

[MLPerf @MLPerf]

Driving ML Forward in Automotive - David Kanter - 2023 CASPA Spring Symp... https://t.co/XPirDjeytM via @YouTube

[HPCwire @HPCwire]

MLCommons: MLPerf Inference Delivers Power Efficiency and Performance Gains
https://t.co/wROKZkabnX #HPC @MLCommons @MLPerf

[Red Hat AI @RedHat_AI]

Learn about the business implications and check out the technical details of our @MLPerf submission in our blog.

https://t.co/y9NW99Jvwe

[Sally Ward-Foxton @sallywf]

.@MLPerf inference results are out! Two startups took on @nvidia and won (albeit for perf/Watt, and only in certain specific scenarios): Taiwan's Neuchips and Silicon Valley's SiMa. @Qualcomm also has some perf/Watt wins against H100 this time.
#mlperf #ai
https://t.co/ZqFdOPKjlC

[Mark Kurtz @markurtz_]

New @MLPerf inference results from us at @neuralmagic are now up! We show 1,000x performance improvements and 92% reduction in energy consumption. Dive into the blog to learn more: https://t.co/IzJ3IiwfgG

#mlops #mlperf #ml