Dr Barry Flower
CruxML’s mission is to work with our clients to adopt real-time machine learning in their applications.
We provide full-stack expertise including data collection, Machine Learning (ML) model development, off-the-shelf and bespoke Field Programmable Gate Array (FPGA) acceleration, hardware/software integration and training. We supplement our customers’ existing domain expertise with deep ML and FPGA hardware knowledge to realise novel products and solutions.
The development of ML systems begins with the data, and preliminary analysis and preparation is crucial.
Model selection can be extremely challenging since the ML field is changing rapidly. CruxML’s heritage in academia is beneficial in this regard. Framework selection is influenced by legacy concerns, translation paths to FPGA hardware and other factors and can save person-years of effort to speed up development and facilitate future upgradability. Sovereignty, performance and design productivity also influence solution choices and integration with existing system needs to be carefully managed.
Dr Barry FlowerCEO
Entrepreneur with strong credentials in large global corporates, academia and engineering.
Prof. Philip LeongCTO
Professor of Computer Systems at the University of Sydney. Expertise in FPGA applications and architectures, low-precision neural networks.
Dr Stephen TridgellPrincipal Engineer
PhD in Low Latency Machine Learning on FPGAs and former member of the Waymo Lidar team