update mlmd results

doc/sphinx/05_mlmd/gpu.csv

@@ -1,22 +1,12 @@
 No. Particles,Actual
-100000,1.93E+02
-200000,3.45E+02
-300000,4.42E+02
-400000,5.27E+02
-500000,5.97E+02
-600000,6.48E+02
-700000,6.90E+02
-800000,7.26E+02
-900000,7.57E+02
-1000000,7.84E+02
-2000000,9.50E+02
-3000000,9.76E+02
-4000000,9.74E+02
-5000000,9.58E+02
-6000000,9.22E+02
-8000000,8.90E+02
-9000000,8.78E+02
-10000000,8.59E+02
-15000000,7.94E+02
-20000000,7.43E+02
-50000000,5.45E+02
+568, 110.105
+1136, 257.538 
+2272, 501.101
+3408, 628.085
+4544, 890.587
+6816, 1255.000 
+9088, 1932.000
+11360, 2234.000 
+13632, 2257.000
+15904, 2545.000
+18176, 2634.000

doc/sphinx/05_mlmd/mlmd.rst

@@ -43,16 +43,16 @@ Building on Chicoma
 
    #Load modules:
    module switch PrgEnv-cray PrgEnv-gnu
-   module load cuda/11.6
+   module load cuda
    module load cpe-cuda
    module load cray-libsci
    module load cray-fftw
-   module load python/3.9-anaconda-2021.11
+   module load python
    module load cmake
-   module load cudatoolkit/22.3_11.6
+   module load cudatoolkit
    
    #Create virtual python environment
-   virtenvpath = <Set Path> 
+   virtenvpath =virt <Set Path> 
    conda create --prefix=${virtenvpath} python=3.10
    source activate ${virtenvpath}
    conda install pytorch-gpu cudatoolkit=11.6 cupy -c pytorch -c nvidia
@@ -261,7 +261,7 @@ Training HIPNN Model
 --------------------
 For the training task, only a single FOM needs to be reported, the average epoch time found in the ``model_results.txt`` file. 
 
-* On Chicoma using a single GPU - FOM Average Epoch time:  0.27951446 
+* On Chicoma using a single GPU - FOM Average Epoch time:  0.24648178 
 * On Crossroads using a single node - FOM Average Epoch time:   2.63468153
 
 Simulation+Inference