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
add16u_1A5 [1] 0.00 % 0.00 % 0.00 % 0.00 % 0.072 141.7 Verilog fileC fileMatlab MEXPython PYX
add16u_0TA [1] 0.00061 % 0.0031 % 0.0016 % 18.75 % 0.069 144.5 Verilog fileC fileMatlab MEXPython PYX
add16u_15Q [1] 0.0014 % 0.0076 % 0.0037 % 29.69 % 0.066 144.5 Verilog fileC fileMatlab MEXPython PYX
add16u_162 [1] 0.00069 % 0.0031 % 0.0019 % 37.50 % 0.065 138.4 Verilog fileC fileMatlab MEXPython PYX
add16u_0U8 [1] 0.015 % 0.049 % 0.041 % 49.22 % 0.062 136.1 Verilog fileC fileMatlab MEXPython PYX
add16u_0UV [1] 0.056 % 0.32 % 0.15 % 68.55 % 0.057 143.1 Verilog fileC fileMatlab MEXPython PYX
add16u_0VA [1] 2.01 % 6.46 % 5.41 % 89.45 % 0.052 122.0 Verilog fileC fileMatlab MEXPython PYX
add16u_067 9.90 % 34.18 % 22.35 % 100.00 % 0.0041 18.3 Verilog fileC fileMatlab MEXPython 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. Optimization of BDD-based Approximation Error Metrics Calculations. In: IEEE Computer Society Annual Symposium on VLSI (ISVLSI '22). Paphos: Institute of Electrical and Electronics Engineers, 2022, pp. 86-91. ISBN 978-1-6654-6605-9.