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MLCommons Releases MLPerf Tiny Inference Benchmark


MLCommons Releases MLPerf Tiny Inference Benchmark
June 16, 2021
SAN FRANCISCO, June 16, 2021 Today, MLCommons, an open engineering consortium, launched a new benchmark, MLPerf Tiny Inference, to measure how quickly a trained neural network can process new data for extremely low-power devices in the smallest form factors and included an optional power measurement. MLPerf Tiny v0.5 is the organization’s first inference benchmark suite that targets machine learning use cases on embedded devices.
Embedded machine learning is a burgeoning field where AI-driven sensor data analytics is performed in real-time, close to where the data resides. The new MLPerf Tiny Inference benchmark suite captures a variety of use cases that involve “tiny” neural networks, typically 100 kB and below, that process sensor data such as audio and vision to provide endpoint intelligence. ....

Colby Banbury , Peter Torelli , Vijay Janapa Reddi , Microprocessor Benchmark Consortium , Harvard University , Tiny Inference , Pengcheng Labs , New Measurement , Advance Intelligence , Embedded Microprocessor Benchmark Consortium , Wake Words , Image Classification , Professor Vijay Janapa Reddi , Digital Catapult , Peng Cheng Laboratories , Sambanova Systems , Silicon Labs , ஹார்வர்ட் பல்கலைக்கழகம் , புதியது அளவீட்டு , எழுந்திரு சொற்கள் , படம் வகைப்பாடு , டிஜிட்டல் கவண் , சிலிக்கான் ஆய்வகங்கள் ,