We work with a range of technology partners, providing machine learning and acceleration expertise.
We’re an Intel Gold Partner. We work within their Design Solutions Network (DSN) program delivering solutions for the entire Intel range of data center acceleration cards, based on Arria 10 and Stratix 10 FPGAs.
We’re a Xilinx Alliance Partner and target a range of Xilinx boards. We are in the process of releasing our tileable MAU™ Core based inference accelerator on the new Xilinx Alveo. Currently available under Nimbix, Alveo is Xilinx’s latest adaptable accelerator card for Data Center Workloads. We also deploy on the Xilinx UltraScale+ in the Amazon AWS F1 cloud.
Jaguar Land Rover is a leader in autonomous driving and their Cortex project is all about improving current systems and working with the tech that can take autonomy further afield. We’re very proud to have been chosen by them to be a core part of Cortex. In collaboration with Birmingham University the collaboration combines machine learning, with advanced radar and camera data to realize Level 4 autonomous driving in poor weather and off-road conditions. The project recently featured in a Wired magazine article.
We are proud to be an Amazon Web Services Partner. We deploy object detection, image segmentation and image recognition solutions on Amazon F1 instances. Originally developed for edge devices these run on data center Xilinx UltraScale+ boards and can be viewed on the AWS marketplace. These demonstrations show how inference can be run securely on re-programmable silicon between decryption/ encryption stages.
MLPerf.org is an industry led machine learning benchmarking effort. It covers the seven principal real-world uses of machine learning. One of only 10 global benchmark owners, we are a benchmark owner for the speech transcription workload. The code we have open sourced as part of our commitment is being used to benchmark new edge and data center hardware.
Myrtle is also part of the MLCommons whose mission is to accelerate ML innovation and increase its positive impact on society. MLCommons aims to do this by creating public resources, industry-scale public datasets and supporting outreach activities.