xcl_dataflow

Description

The xcl_dataflow attribute enables task-level pipelining, allowing functions and loops to overlap in their operation, increasing the concurrency of the RTL implementation, and increasing the overall throughput of the design.

All operations are performed sequentially in a C description. In the absence of any directives that limit resources (such as pragma HLS allocation), Vivado HLS seeks to minimize latency and improve concurrency. However, data dependencies can limit this. For example, functions or loops that access arrays must finish all read/write accesses to the arrays before they complete. This prevents the next function or loop that consumes the data from starting operation. The dataflow optimization enables the operations in a function or loop to start operation before the previous function or loop completes all its operations.

When dataflow optimization is specified, Vivado HLS analyzes the dataflow between sequential functions or loops and create channels (based on pingpong RAMs or FIFOs) that allow consumer functions or loops to start operation before the producer functions or loops have completed. This allows functions or loops to operate in parallel, which decreases latency and improves the throughput of the RTL.

If no initiation interval (number of cycles between the start of one function or loop and the next) is specified, Vivado HLS attempts to minimize the initiation interval and start operation as soon as data is available.

TIP: Vivado HLS provides dataflow configuration settings. The config_dataflow command specifies the default memory channel and FIFO depth used in dataflow optimization. Refer to the Vivado Design Suite User Guide: High-Level Synthesis (UG902) for more information.
For the DATAFLOW optimization to work, the data must flow through the design from one task to the next. The following coding styles prevent Vivado HLS from performing the DATAFLOW optimization, refer to Vivado Design Suite User Guide: High-Level Synthesis (UG902) for more information:
  • Single-producer-consumer violations
  • Bypassing tasks
  • Feedback between tasks
  • Conditional execution of tasks
  • Loops with multiple exit conditions
IMPORTANT!: If any of these coding styles are present, Vivado HLS issues a message and does not perform DATAFLOW optimization.

Finally, the DATAFLOW optimization has no hierarchical implementation. If a sub-function or loop contains additional tasks that might benefit from the DATAFLOW optimization, you must apply the optimization to the loop, the sub-function, or inline the sub-function.

Syntax

Assign the dataflow attribute before the function definition or the loop definition:

__attribute__((xcl_dataflow))

Examples

Specifies dataflow optimization within function foo. 

#pragma HLS dataflow

See Also