The design in distribute_L2.py uses an Object FIFO of_in to bring data from external memory to L2 as 24xi32 tensors. From there, the data is distributed to three Object FIFOs in smaller 8xi32 parts. Each Worker receives a different part of the larger data based on which of the three Object FIFO it accesses.
# Dataflow with ObjectFifos
# Input
of_offsets = [8 * worker for worker in range(n_workers)]
of_in = ObjectFifo(tile24_ty, name="in")
of_ins = (
of_in
.cons()
.split(
of_offsets,
obj_types=[tile8_ty] * n_workers,
names=[f"in{worker}" for worker in range(n_workers)],
)
)All Workers are running the same process of acquiring one object from their respective input Object FIFOs to consume, adding 1 to all of its entries, and releasing the object. The join design shows how the data is sent back out to external memory and tested.
It is possible to compile this design with the following commands:
makeThe explicitly placed level of IRON programming for this design is available in distribute_L2_placed.py. It can be compiled with the following commands:
env use_placed=1 makeOther examples containing this data movement pattern are available in the programming_examples/matrix_multiplication/.