The EvoApproxLibLITE is the lightweight version of our library of approximate circuits with formally guaranteed error parameters. Hardware as well as software models are provided for each circuit.

Circuit name MAE WCE MRE EP power area Download model
mul12s_2PP [1] 0.00 % 0.00 % 0.00 % 0.00 % 1.210 1650.5 Verilog PDK45Verilog fileC filePython PYX
mul12s_2PQ [1] 0.0000012 % 0.000006 % 0.00047 % 25.00 % 1.205 1644.4 Verilog PDK45Verilog fileC filePython PYX
mul12s_2QD [1] 0.0031 % 0.012 % 0.22 % 49.99 % 1.093 1528.0 Verilog PDK45Verilog fileC filePython PYX
mul12s_2QE [1] 0.0031 % 0.012 % 0.22 % 62.49 % 1.091 1524.3 Verilog PDK45Verilog fileC filePython PYX
mul12s_34K [1] 0.0051 % 0.024 % 0.41 % 74.98 % 0.965 1385.4 Verilog PDK45Verilog fileC filePython PYX
mul12s_2RP [1] 0.021 % 0.085 % 1.45 % 87.48 % 0.850 1300.4 Verilog PDK45Verilog fileC filePython PYX
mul12s_2TE [1] 0.19 % 0.77 % 12.72 % 98.41 % 0.497 874.8 Verilog PDK45Verilog fileC filePython PYX

Reported error parameters: MAE - Mean Absolute Error (Mean Error Magnitude), WCE - Worst-Case Absolute Error (Error Magnitude / Error Significance), MSE - Mean Squared Error, MRE - Mean Relative Error (Mean Relative Error Distance), WCRE - Worst-Case Relative Error, EP - Error Probability (Error Rate)  |  Reported design parameters: power - power consumption in mW, area - area on the chip in um2, dly - delay, all values obtained using Synopsys DC (45 nm PDK, 1 V, 25 ℃)  |  Error parameters marked by were verified using a formal technique analyzing all possible input combinations. There is a formal guarantee that the error is not worse than the shown value. The exact values are included at the beginning of each C file and Verilog file.

COMPARISON

Comparison with the complete EvoApproxLib dataset on various metrics. The first plot shows the performance wrt. the parameters used for pareto filtration. The black dots are the circuits included in this dataset. The blue dots are parameters of the circuits included in the full version of EvoApproxLib. Note that the parameters of the accurate implementation shown in the figure correspond with those exhibiting the lowest power consumption.

REFERENCES
  1. V. Mrazek, Z. Vasicek, L. Sekanina, H. Jiang and J. Han, Scalable Construction of Approximate Multipliers With Formally Guaranteed Worst Case Error in IEEE Transactions on Very Large Scale Integration (VLSI) Systems, vol. 26, no. 11, pp. 2572-2576, Nov. 2018.