Dataflow Using HLS Stream

This is simple example of vector addition to demonstrate Dataflow functionality of HLS. HLS Dataflow allows user to schedule multiple task together to achieve higher throughput.

KEY CONCEPTS: Task Level Parallelism

KEYWORDS: dataflow, hls::stream

This example explains how #pragma HLS dataflow can be used to implement task level parallelism using HLS Stream datatype.

Usually data stored in the array is consumed or produced in a sequential manner, a more efficient communication mechanism is to use streaming data as specified by the STREAM pragma, where FIFOs are used instead of RAMs. Depth of FIFO can be specified by depth option in the pragma.

#pragma HLS STREAM variable = inStream depth = 32
#pragma HLS STREAM variable = outStream depth = 32

Vector addition in kernel is divided into 3 sub-tasks(read, compute_add and write) which are then performed concurrently using Dataflow.

#pragma HLS dataflow
    read_input(in, inStream, size);
    compute_add(inStream, outStream, inc, size);
    write_result(out, outStream, size);

EXCLUDED PLATFORMS:

• All NoDMA Platforms, i.e u50 nodma etc

DESIGN FILES

Application code is located in the src directory. Accelerator binary files will be compiled to the xclbin directory. The xclbin directory is required by the Makefile and its contents will be filled during compilation. A listing of all the files in this example is shown below

src/adder.cpp
src/host.cpp

Access these files in the github repo by clicking here.

COMMAND LINE ARGUMENTS

Once the environment has been configured, the application can be executed by

./dataflow_stream <adder XCLBIN>