We are a Startup Company with a Turnkey Machine Learning Solutions for FPGA Edge Acceleration

–	Deep understanding of Machine Learning
–	CNN Architecture explorations, Training & Efficient implementation
–	Efficient Acceleration Hardware design on FPGA
–      Industry veterans & Academia experts to solve real life challenges in AI
–	Top notch team & strong Customer support

Want to find out how savvy professionals are implementing Edge AI networks on FPGA efficiently?  

Deploying AI Models on FPGA is attractive in Edge applications due to lower Cost and Power, and ability to scale up the performance by migrating with higher FPGA densities.  But conversion of AI models from GPU to FPGA hardware is a complex task, each path chosen comes with its own challenges: 

–	FPGA HLS Tools are not efficient in resource utilization
–	Hand craft RTL design requires specialized experts and consumes time
–	Generic Tools oversimplify CNNs and trade off accuracy for performance

ComputEra offers a Comprehensive approach to developing AI models and implementing on FPGA Hardware.  We take a holistic approach to Edge AI design starting with CNN Network architecture re-design, model re-train, to get better accuracy & hardware friendliness.  Our design flow uses our configurable CNN Accelerator that has been design from the ground up for FPGA implementation.   We leverage our CNN Compiler to generate efficient instructions to achieve the highest performance while running on our Accelerator.  That ensures the highest level of hardware speed up and the right power and performance tradeoffs are taken.  We leverage our tools & design flows to complete the design in days versus months.

Interested in learning how ComputEra can help on your next FPGA AI design?

Email us at info@computera.ai

ComputERA

ComputERA's headquarters in Santa Clara, CA, United States

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People (2)

Shihming (Sherman) Liu

Edwin Chu

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