US-based SiMa.ai, machine learning start-up focussing on solutions for the embedded edge, has clocked the highest result in its debut in MLPerf Benchmark performance in the Closed Edge Power category.
Founded by Krishna Rangasayee (Founder and CEO), the start-up is focussing on embedded edge market with its team focussing on software, semiconductor design, and machine learning. It initially focused on solve challenges in the area of smart vision, robotics and Industry 4.0, drones and autonomous vehicles among others.
The company’s Machine Learning System-on-Chip (MLSoC) platform earned top inference achievements in all aspects of the ResNet-50 benchmark, beating the industry leader on both performance (frames per second) and power. These MLPerf results demonstrate that the MLSoC Platform follows through on its promise of an Any, 10x, Pushbutton solution for effortless ML deployment.
The ResNet-50 benchmark is an inference benchmark (test) for image classification and is often used as a standard for measuring performance of machine learning accelerators.
Rangasayee said “While it is exciting that we won at MLPerf in performance and power over the incumbent leader, what is super rewarding is that we are delighting customers globally with a ‘Any. 10x. Pushbutton’ experience that in real life applications far exceeds any other alternative which remains our focus – doing ML software right for our customers.”
Established by industry leaders in 2018, the foundation for MLCommons aims to accelerate machine learning innovation. The MLPerf inference benchmarks are released bi-annually and define a fully standardised way of measuring performance and power for a variety of ML applications, enabling end-users to easily sort out company claims, and provide industry-standard metrics.
SiMa.ai’s MLSoC hardware combined with its Palette software delivers a purpose-built platform with push button results, enabling effortless ML deployment and scaling at the embedded edge while achieving a claimed 10x better performance at the lowest power.
With this methodology, SiMa.ai says it is able to achieve dramatic results without needing to employ a massive team while delivering results in minutes versus competitor technology that requires months.
For the autonomous driving technology, the start-up claims it can support the automotive industry for ADAS and electrification roadmap with its solutions that can take care of all the computation needs for less than 10W for L2+/L3 applications and less than 100W for complex L4/L5 automotive systems.
