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47bce4157d
Added a new data-flow graph (DFG) based combinational logic optimizer. The capabilities of this covers a combination of V3Const and V3Gate, but is also more capable of transforming combinational logic into simplified forms and more. This entail adding a new internal representation, `DfgGraph`, and appropriate `astToDfg` and `dfgToAst` conversion functions. The graph represents some of the combinational equations (~continuous assignments) in a module, and for the duration of the DFG passes, it takes over the role of AstModule. A bulk of the Dfg vertices represent expressions. These vertex classes, and the corresponding conversions to/from AST are mostly auto-generated by astgen, together with a DfgVVisitor that can be used for dynamic dispatch based on vertex (operation) types. The resulting combinational logic graph (a `DfgGraph`) is then optimized in various ways. Currently we perform common sub-expression elimination, variable inlining, and some specific peephole optimizations, but there is scope for more optimizations in the future using the same representation. The optimizer is run directly before and after inlining. The pre inline pass can operate on smaller graphs and hence converges faster, but still has a chance of substantially reducing the size of the logic on some designs, making inlining both faster and less memory intensive. The post inline pass can then optimize across the inlined module boundaries. No optimization is performed across a module boundary. For debugging purposes, each peephole optimization can be disabled individually via the -fno-dfg-peepnole-<OPT> option, where <OPT> is one of the optimizations listed in V3DfgPeephole.h, for example -fno-dfg-peephole-remove-not-not. The peephole patterns currently implemented were mostly picked based on the design that inspired this work, and on that design the optimizations yields ~30% single threaded speedup, and ~50% speedup on 4 threads. As you can imagine not having to haul around redundant combinational networks in the rest of the compilation pipeline also helps with memory consumption, and up to 30% peak memory usage of Verilator was observed on the same design. Gains on other arbitrary designs are smaller (and can be improved by analyzing those designs). For example OpenTitan gains between 1-15% speedup depending on build type. |
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verilator | ||
verilator_ccache_report | ||
verilator_coverage | ||
verilator_difftree | ||
verilator_gantt | ||
verilator_includer | ||
verilator_profcfunc |