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toymap: Toy technology mapper

Toymap maps logic networks onto LUTs or simple logic gates. The basic principle is cutting up an And-Inverter Graph representing the desired logic function into small subgraphs such that each subgraph can be implemented with (mapped onto) a LUT or a simple gate. Technology mapping like this is a step in the compilation of logic designs to be programmed onto an FPGA or manufactured as an IC.

Some features:

  • Employs the method of "priority cuts" to come up with candidate cuts of the graph (see the reference below)

  • Attempts to preserve wire names

  • Uses internal representation capable of expressing sequential circuits

    • This isn't useful yet since only acyclic graphs can be mapped and sequential elements are ignored in depth estimation. Import, export and emission of LUTs do handle sequential circuits correctly.
  • Integrates into Yosys

  • Comes with a pass for basic LUT4 graph rewriting

Build

python3 pmgen.py lutcuts.pmg > lutcuts_pmg.h && yosys-config --build toymap.so toymap.cc lutdepth.cc post.cc --std=c++20

References

  • A. Mishchenko, S. Cho, S. Chatterjee, and R. Brayton, "Combinational and sequential mapping with priority cuts", Proc. ICCAD '07, pp. 354-361. PDF

  • S. Jang, B. Chan, K. Chung, and A. Mishchenko, "WireMap: FPGA technology mapping for improved routability". Proc. FPGA '08, pp. 47-55. PDF

Benchmarks

Following is a result of comparing ABC (invoked with the abc -lut N Yosys command) against toymap on the EPFL benchmarks (the benchmarks/ submodule). On each benchmark LUT4 and LUT6 mappings are attempted, once with ABC, once with toymap, and once with toymap after ABC preprocessed the AIG (labeled abc+toymap). See run_benchmark.tcl for detailed commands.

Results as of toymap commit 8587180:

Benchmark abc LUT4 area toymap LUT4 area toymap/abc relative area abc+toymap LUT4 area abc+toymap/abc relative area abc LUT4 depth toymap LUT4 depth abc+toymap LUT4 depth abc LUT6 area toymap LUT6 area toymap/abc relative area abc+toymap LUT6 area abc+toymap/abc relative area abc LUT6 depth toymap LUT6 depth abc+toymap LUT6 depth extra toymap args (LUT4) extra toymap args(LUT6)
arithmetic/adder.aig 339 339 100.0% 339 100.0% 85 85 85 274 268 97.8% 268 97.8% 51 51 51
arithmetic/bar.aig 1156 1280 110.7% 1156 100.0% 6 6 6 512 512 100.0% 512 100.0% 4 4 4
arithmetic/div.aig 6551 25931 395.8% 6635 101.3% 1437 1443 1437 5048 22014 436.1% 5261 104.2% 860 864 860
arithmetic/hyp.aig 64232 63752 99.3% 63619 99.0% 8254 8259 8254 44985 47045 104.6% 47401 105.4% 4193 4198 4195
arithmetic/log2.aig 10661 10075 94.5% 10034 94.1% 126 126 126 7880 7747 98.3% 7789 98.8% 70 72 70
arithmetic/max.aig 1013 982 96.9% 997 98.4% 67 76 67 799 774 96.9% 785 98.2% 40 44 40
arithmetic/multiplier.aig 7463 7439 99.7% 7428 99.5% 87 87 87 5880 5828 99.1% 5981 101.7% 53 53 53
arithmetic/sin.aig 1968 1878 95.4% 1921 97.6% 56 60 56 1450 1407 97.0% 1459 100.6% 36 36 36
arithmetic/sqrt.aig 4529 8450 186.6% 4399 97.1% 1995 2015 1995 3183 5682 178.5% 3299 103.6% 1017 1033 1017
arithmetic/square.aig 6248 6403 102.5% 6400 102.4% 83 84 83 3928 3806 96.9% 3902 99.3% 50 50 50
random_control/arbiter.aig 4068 4222 103.8% 4245 104.4% 30 30 30 2719 2722 100.1% 2722 100.1% 18 18 18
random_control/cavlc.aig 269 281 104.5% 279 103.7% 6 6 6 107 100 93.5% 99 92.5% 4 4 4
random_control/ctrl.aig 52 50 96.2% 52 100.0% 3 3 3 29 28 96.6% 29 100.0% 2 2 2
random_control/dec.aig 288 288 100.0% 288 100.0% 2 2 2 287 282 98.3% 272 94.8% 2 2 2
random_control/i2c.aig 434 513 118.2% 457 105.3% 5 6 5 303 344 113.5% 312 103.0% 3 4 3
random_control/int2float.aig 76 82 107.9% 81 106.6% 6 6 6 41 42 102.4% 41 100.0% 4 3 4
random_control/mem_ctrl.aig 14867 16730 112.5% 16735 112.6% 36 40 36 9202 11202 121.7% 11002 119.6% 22 25 22
random_control/priority.aig 169 218 129.0% 202 119.5% 43 60 36 127 214 168.5% 174 137.0% 26 31 26
random_control/priority.aig 169 218 129.0% 192 113.6% 43 60 43 127 214 168.5% 173 136.2% 26 30 26 -target 43
random_control/router.aig 72 95 131.9% 84 116.7% 9 10 9 40 73 182.5% 56 140.0% 6 7 6
random_control/voter.aig 2236 3621 161.9% 2441 109.2% 17 22 18 1461 2733 187.1% 1498 102.5% 12 16 13

Credits

  • Hannah Ravensloft (@Ravenslofty) -- suggestions and critique

Copyright notice

Except for the benchmarks/ submodule, the code is:

Copyright 2023 Martin Povišer

No explicit license assigned at this point