In this demo, we will present how users can run up to 40x faster their ML applications using oneAPI. As a use case we will show how Logistic Regression training can run 42x faster on an Arria 10 FPGA card using the oneAPI interface. The logistics Regression ML Model reference code was ported to DPC++ code and the results were compared. The implementation was done on Intel FPGA using oneAPI  FPGA development flow.

Learning objectives: Using oneAPI toolkit with FPGA add-on to speedup widely used ML algorithms
Developer Takeaway : Easy acceleration of ML applications using FPGA Development Flow with oneAPI on Intel FPGAs
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