Hardware Acceleration with Multi-Threading of Java-Based High Level Synthesis Tool.

In this research, we attempt to speed up the computational fluid dynamics (CFD) and the convolutional neural network (CNN) using JavaRock-Thrash thread function of the high-level synthesis tool with an FPGA. In the two-dimensional heat equation, by using the thread function of the high-level synthesis tool, up to a 12.13 times speedup compared to single-threaded processing is obtained with multi-threading, up to a 29.0 times speedup against Vivado HLS is achieved. In the convolution process, the process of passing 11 x 11 filters on 2-dimensional data of 33 x 33 described with 484 threads results in a speedup of 78 times compared to the processing time at Vivado HLS.