Circuit IR Compilers and Tools

DC Dialect Rationale


DC (Dynamic Control) IR describes independent, unsynchronized processes communicating data through First-in First-out (FIFO) communication channels. This can be implemented in many ways, such as using synchronous logic, or with processors.

The intention of DC is to model all operations required to represent such a control flow language. DC aims to be strictly a control flow dialect - as opposed to the Handshake dialect, which assigns control semantics to all SSA values. As such, data values are only present in DC where they are required to model control flow.

By having such a control language, the dialect aims to facilitate the construction of dataflow programs where control and data is explicitly separate. This enables optimization of the control and data side of the program independently, as well as mapping of the data side into functional units, pipelines, etc.. Furthermore, separating data and control will make it easier to reason about possible critical paths of either circuit, which may inform buffer placement.

The DC dialect has been heavily influenced by the Handshake dialect, and can either be seen as a successor to it, or a lower level abstraction. As of writing, DC is fully deterministic. This means that non-deterministic operators such as the ones found in Handshake - handshake.merge, handshake.control_merge - do not have a lowering to DC. Handshake programs must therefore be converted or by construction not contain any of these non-deterministic operators. Apart from that, all handshake operations can be lowered to a combination of DC and e.g. arith operations (to represent the data side semantics of any given operation).

In DC IR, all values have implicit fork and sink semantics. That is, a DC-typed value may be referenced multiple times, as well as it being legal that said value is not referenced at all. This has been chosen to facilitate canonicalization, thus removing the need for all canonicalization patterns to view forks as opaque/a special case. If a given DC lowering requires explcit fork/sink semantics, forks and sinks can be materialized throuh use of the --dc-materialize-forks-sinks pass. Conversely, if one wishes to optimize DC IR which already contains fork and sink operations, one may use the --dc-dematerialize-forks-sinks pass, run canonicalization, and then re-apply the --dc-materialize-forks-sinks pass.


By explicitly separating data and control parts of a program, we allow for control-only canonicalization to take place. Here are some examples of non-trivial canonicalization patterns:

  • Transitive join closure:
    • Taking e.g. the Handshake dialect as the source abstraction, all operations
    • unless some specific Handshake operations - will be considered as unit rate actors and have join semantics. When lowering Handshake to DC, and by separating the data and control paths, we can easily identify join operations which are staggered, and can be merged through a transitive closure of the control graph.
  • Branch to select: Canonicalizes away a select where its inputs originate from a branch, and both have the same select signal.
  • Identical join: Canonicalizes away joins where all inputs are the same (i.e. a single join can be used).