XRT Streaming Platform Support

Starting from the 2019.1 release, XRT supports a new programming model which supports the direct streaming of data from host to kernel and kernel to host without having to go through global memory. This feature is an addition to the existing host to kernel and kernel to host data transfer using global memories. By using streams, you can get some of the advantages such as:

  • The host application does not necessarily need to know the size of the data coming from the kernel. Data resides on the host memory can be transferred to the kernel as soon as it is needed. Similarly, the processed data can be transferred back when it is required.
  • This programming model uses minimal storage compared to the larger and slower global memory bank, and thus improving the performance and power.

APIs required for streaming data tranfer

OpenCL™ extension APIs for streaming operation

APIs Description
clCreateStream Creates a read or write stream
clReleaseStream Frees the created stream and its associated memory
clWriteStream Writes data to stream
clReadStream Gets data from stream
clPollStreams Polls for any stream on the device to finish. Required only for non-blocking stream operation.

The typical API flow is described below:

  • Create the required number of the read/write streams by clCreateStream.

    • Streams should be directly attached to the OpenCL device object because it does not use any command queue. A stream itself is a command queue that only passes the data to a particular direction, either from host to kernel or from kernel to host.
    • An appropriate flag should be used to denote stream write/read operation (from the host perspective).
    • To specify how the stream is connected to the device, a predefined extension pointer (cl_mem_ext_ptr_t) should be used to denote the kernel and its argument the stream is associated with.

In the code block below, a Read Stream (named read_stream) and a Write Stream (named write_stream) are created.

#include <CL/cl_ext_xilinx.h> // Required for Xilinx® Extension

// Device connection specification of the stream through extension pointer
cl_mem_ext_ptr_t  ext;  // Extension pointer
ext.param = kernel;     // The .param should be set to kernel (cl_kernel type)
ext.obj = nullptr;

// The .flag should be used to denote the kernel argument
// Create write stream for argument 3 of kernel
ext.flags = 3;
cl_stream write_stream = clCreateStream(device_id, CL_STREAM_WRITE_ONLY, CL_STREAM, &ext, &ret);

// Create read stream for argument 4 of kernel
ext.flags = 4;
cl_stream read_stream = clCreateStream(device_id, CL_STREAM_READ_ONLY, CL_STREAM, &ext,&ret);
  • Set the remaining non-stream kernel arguments and enqueue the kernel. The following code block shows typical kernel argument (non-stream arguments such as buffer and/or scalar) setting and kernel enqueuing.
// Set kernel non-stream argument (if any)
clSetKernelArg(kernel, 0,...,...);
clSetKernelArg(kernel, 1,...,...);
clSetKernelArg(kernel, 2,...,...);
// 3rd and 4th arguments are not set as those are already specified when creating the streams

// Schedule kernel enqueue
clEnqueueTask(commands, kernel, . .. . );
  • Initiate Read and Write transfer by clReadStream and clWriteStream.

    • Note the usage of attribute cl_stream_xfer_req associated with read and write request.

    • The .flag is used to denote transfer mechanism.

      • CL_STREAM_EOT: Currently, successful stream transfer mechanism depends on identifying the end of the transfer by an End of Transfer signal. This flag is mandatory in the current release.
      • CL_STREAM_NONBLOCKING: By default the Read and Write transfers are blocking. For non-blocking transfer, CL_STREAM_NONBLOCKING has to be set.
    • The .priv_data is used to specify a string (as a name for tagging purpose) associated with the transfer. This will help identify specific transfer completion when polling the stream completion. It is required when using the non-blocking version of the API.

In the following code block, the stream read and write transfers are executed with the non-blocking approach.

// Initiate the READ transfer
cl_stream_xfer_req rd_req {0};

rd_req.priv_data = (void*)"read"; // You can think this as tagging the
                                                                      transfer with a name
clReadStream(read_stream, host_read_ptr, max_read_size, &rd_req, &ret);

// Initiating the WRITE transfer
cl_stream_xfer_req wr_req {0};

wr_req.priv_data = (void*)"write";

clWriteStream(write_stream, host_write_ptr, write_size, &wr_req , &ret);
  • Poll all the streams for completion. For the non-blocking transfer, a polling API is provided to ensure the read/write transfers are completed. For the blocking version of the API, polling is not required.

    • The number of poll requests should be used through cl_streams_poll_req_completions.
    • The clPollStreams is a blocking API. It returns the execution to the host code as soon as it receives the notification that all stream requests have been completed, or until you specify the timeout.
// Checking the request completion
cl_streams_poll_req_completions poll_req[2] {0, 0}; // 2 Requests

auto num_compl = 2;
clPollStreams(device_id, poll_req, 2, 2, &num_compl, 5000, &ret);
// Blocking API, waits for 2 poll request completion or 5000ms, whichever occurs first
  • Read and use the stream data in host.

    • After the successful poll request is completed, the host can read the data from the host pointer.
    • Also, the host can check the size of the data transferred to the host. For this purpose, the host needs to find the correct poll request by matching priv_data and then fetching nbytes (the number of bytes transferred) from the cl_streams_poll_req_completions structure.
for (auto i=0; i<2; ++i) {
    if(rd_req.priv_data == poll_req[i].priv_data) { // Identifying the read transfer

     // Getting read size, data size from kernel is unknown
     ssize_t result_size=poll_req[i].nbytes;

The header file containing function prototype and argument description is available in the XRT GitHub repository.

IMPORTANT: If the streaming kernel has multiple CUs, the host code needs to use a unique cl_kernel object for each CU. The host code must use clCreateKernel with <kernel_name>:{compute_unit_name} to get each CU, creating streams for them, and enqueuing them individually.