Neural network weight distribution using a tree direct-memory access (dma) bus

One or more computer-readable non-transitory storage media embodying software that is operable when executed to:

• receive, by a tree direct-memory access (DMA) controller of a machine learning (ML) accelerator, a memory address indicating a location in a memory storing a set of weights associated with a machine-learning model;
• receive, by the tree DMA controller, a distribution instruction indicating one or more tensor processor clusters of a plurality of tensor processor clusters of the ML accelerator selected to receive the set of weights for processing, in parallel, different partitioned portions of an input feature;
• retrieve the set of weights from the location in the memory indicated by the memory address;
• and
• send, via a tree DMA bus, the set of weights in at least one DMA packet addressed to the one or more tensor processor clusters according to the distribution instruction.

A system comprising:

• a compiler;
• a tree DMA bus;
• a plurality of tensor processor clusters;
• and
• a tree direct-memory access (DMA) controller communicably coupled to each of the plurality of tensor processor clusters via the tree DMA bus, the tree DMA controller configured to:
• receive a memory address from the compiler, the memory address indicating a location in a memory storing a set of weights associated with a machine-learning model;
• receive a distribution instruction indicating one or more tensor processor clusters of the plurality of tensor processor clusters selected to receive the set of weights for processing, in parallel, different partitioned portions of an input feature;
• retrieve the set of weights from the location in the memory indicated by the memory address;
• and
• send, via the tree DMA bus, the set of weights in at least one DMA packet addressed to the one or more tensor processor clusters according to the distribution instruction.