Machine Learning-FPGA

LogicTronix have did multiple implementation of Machine Learning and Neural Networks on FPGA [including VCU1525, Alveo, ZCU102, ZCU104 and Ultra96]:

1. Machine Learning with Xilinx VCU1525 with Nimbix Cloud Accelerator Platform:

This implementation uses the YoloV2 algorithm for object recognition, it is implemented on VCU1525 FPGA device on the Nimbix Cloud Platform.

2.Machine Learning with Alveo U200/U250 FPGA

We also have developed different applications based on ML Suite for Alveo FPGA [U200] card. For exploring with ML Suite for Alveo, ML Suite, there is also an example of image classification using the Googlenet with kernel precision INT8, INT16 for test classify and batch classify. This acceleration run on Alveo U200 as well as U250 [with some revision].

Here is the Video Tutorial Link: Machine Learning Suite Acceleration on Alveo FPGA-Video Tutorial.  If you need any reference document or support on it then you may contact us!

3. DPU TRD for ZCU104 [DNNDK Implementation]:

This application is developed for implementing the DNNDK on the ZCU104 using the PG338 of Xilinx[Deephi].  This implementation is used for Image Classification and Face Detection application with some other application.

4. DPU TRD for Ultra96 [DPU Integration for the Ultra96 FPGA]:

It is DNNDK implementation on the Ultra96 FPGA for Image Classification and Face Detection.

5. Machine Learning with PYNQ FPGA:

We have used the BNN for digit recognition and vehicle number plate recognition, QNN/CNN for image classification and few other NN/ML algorithm are used for other applications as traffic sign detection, object recognition etc.

If you are interested on implementing Machine Learning algorithms or Neural Networks on you application or custom application then you can contact us at: info@logictronix.com or sales@logictronix.com.