Update README.md

README.md

@@ -118,7 +118,7 @@ In the table below, we quantify the performance of the NeuralFoil ("NF") models
 
 This table details both of these considerations. The first few columns show the error with respect to XFoil on the test dataset. [The test dataset is completely isolated from the training dataset, and NeuralFoil was not allowed to learn from the test dataset](#geometry-parameterization-and-training-data). Thus, the performance on the test dataset gives a good idea of NeuralFoil's performance "in the wild". The second set of columns gives the runtime speed of the models, both for a single analysis and for a large batch analysis.
 
-<table><thead><tr><th>Aerodynamics Model</th><th colspan="4">Mean Absolute Error (MAE) of Given Metric, on the Test Dataset, with respect to XFoil</th><th colspan="2">Computational Cost to Run</th></tr></thead><tbody><tr><td></td><td>Lift Coeff.<br>$C_L$</td><td>Fractional Drag Coeff.<br>$\ln(C_D)$&nbsp;&nbsp;&nbsp;†</td><td>Moment Coeff.<br>$C_M$</td><td>Transition Locations<br>$x_{tr}/c$</td><td>Runtime<br>(1 run)</td><td>Total Runtime<br>(100,000 runs)</td></tr>
+<table><thead><tr><th>Aerodynamics Model</th><th colspan="4">Mean Absolute Error (MAE) of Given Metric, on the Test Dataset, with respect to XFoil</th><th colspan="2">Computational Cost to Run (CPU)</th></tr></thead><tbody><tr><td></td><td>Lift Coeff.<br>$C_L$</td><td>Fractional Drag Coeff.<br>$\ln(C_D)$&nbsp;&nbsp;&nbsp;†</td><td>Moment Coeff.<br>$C_M$</td><td>Transition Locations<br>$x_{tr}/c$</td><td>Runtime<br>(1 run)</td><td>Total Runtime<br>(100,000 runs)</td></tr>
 <tr><td>NF "xxsmall"</td><td>0.040</td><td>0.078</td><td>0.007</td><td>0.044</td><td>1.2 ms</td><td>0.87 sec</td></tr>
 <tr><td>NF "xsmall"</td><td>0.030</td><td>0.057</td><td>0.005</td><td>0.033</td><td>1.2 ms</td><td>1.03 sec</td></tr>
 <tr><td>NF "small"</td><td>0.027</td><td>0.050</td><td>0.005</td><td>0.027</td><td>1.3 ms</td><td>1.14 sec</td></tr>