Commit 9651e3c3 authored by Tomáš Oberhuber's avatar Tomáš Oberhuber Committed by Jakub Klinkovský
Browse files

Splitting graphs of symmetric anf binary matrices in spmv benchmark results postporcessing script.

parent 38912934

src/Benchmarks/scripts/tnl-spmv-benchmark-make-tables-json.py

+54 −15
Original line number Diff line number Diff line
@@ -68,7 +68,7 @@ def get_multiindex( input_df, formats ): 
         level3.append( 'speed-up')

         level4.append( 'non-symmetric' )

         df_data[ 0 ].append( ' ' )

      if format == 'CSR< Light >':

      if format == 'CSR< Light > Automatic':

         level1.append( format )

         level2.append( 'GPU' )

         level3.append( 'speed-up')
@@ -174,7 +174,8 @@ def compute_cusparse_speedup( df, formats ): 
####

# Compute speedup of Light CSR

def compute_csr_light_speedup( df ):

   csr_light_bdw_list = df[('CSR< Light >','GPU','bandwidth')]

   for light in [ 'CSR< Light > Automatic', 'CSR< Light > Automatic Light']:

      csr_light_bdw_list = df[(light,'GPU','bandwidth')]

      light_spmv_bdw_list = df[('LightSpMV Vector','GPU','bandwidth')]



      csr_light_speedup_list = []
@@ -183,7 +184,7 @@ def compute_csr_light_speedup( df ): 
            csr_light_speedup_list.append( csr_light_bdw / light_spmv_bdw  )

         except:

            csr_light_speedup_list.append(float('nan'))

   df[('CSR< Light >','GPU','speed-up','LightSpMV Vector')] = csr_light_speedup_list

      df[(light,'GPU','speed-up','LightSpMV Vector')] = csr_light_speedup_list



####

# Compute speed-up of binary formats
@@ -211,6 +212,7 @@ def compute_symmetric_speedup( df, formats ): 
         print( f'Adding speed-up of {format} vs {non_symmetric_format}' )

         format_bdw_list = df[(format,'GPU','bandwidth')]

         non_symmetric_bdw_list = df[(non_symmetric_format,'GPU','bandwidth')]



         symmetric_speedup_list = []

         for ( format_bdw, non_symmetric_bdw ) in zip( format_bdw_list, non_symmetric_bdw_list ):

            try:
@@ -526,16 +528,53 @@ def cusparse_speedup_comparison( df, formats, head_size=10 ): 
   ylabel = "Speedup"

   current_formats = []

   for format in formats:

      if( 'Ellpack' in format and not 'Binary' in format and not 'Legacy' in format ):

      if( 'Ellpack' in format and not 'Symmetric' in format and not 'Binary' in format and not 'Legacy' in format ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "ellpack-profiles-cusparse-speedup.pdf", "draw-bar" )



   current_formats.clear()

   for format in formats:

      if( 'Ellpack' in format and 'Symmetric' in format and not 'Binary' in format and not 'Legacy' in format ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "symmetric-ellpack-profiles-cusparse-speedup.pdf", "draw-bar" )



   current_formats.clear()

   for format in formats:

      if( 'Ellpack' in format and not 'Symmetric' in format and 'Binary' in format and not 'Legacy' in format ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "binary-ellpack-profiles-cusparse-speedup.pdf", "draw-bar" )



   current_formats.clear()

   for format in formats:

      if( 'Ellpack' in format and 'Symmetric' in format and 'Binary' in format and not 'Legacy' in format ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "symmetric-binary-ellpack-profiles-cusparse-speedup.pdf", "draw-bar" )





   # Draw CSR formats profiles

   current_formats.clear()

   for format in formats:

      if( 'CSR' in format and not 'Binary' in format and not 'Legacy' in format and not 'Hybrid' in format and format != 'CSR' ):

      if( 'CSR' in format and not 'Symmetric' in format and not 'Binary' in format and not 'Legacy' in format and not 'Hybrid' in format and format != 'CSR' ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "csr-profiles-cusparse-speedup.pdf", "draw-bar" )

   current_formats.clear()

   for format in formats:

      if( 'CSR' in format and 'Symmetric' in format and not 'Binary' in format and not 'Legacy' in format and not 'Hybrid' in format and format != 'CSR' ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "symmetric-csr-profiles-cusparse-speedup.pdf", "draw-bar" )

   current_formats.clear()



   for format in formats:

      if( 'CSR' in format and not 'Symmetric' in format and 'Binary' in format and not 'Legacy' in format and not 'Hybrid' in format and format != 'CSR' ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "binary-csr-profiles-cusparse-speedup.pdf", "draw-bar" )

   current_formats.clear()



   for format in formats:

      if( 'CSR' in format and 'Symmetric' in format and 'Binary' in format and not 'Legacy' in format and not 'Hybrid' in format and format != 'CSR' ):

         current_formats.append( format )

   draw_profiles( current_formats, profiles, xlabel, ylabel, "-symmetric-binary-csr-profiles-cusparse-speedup.pdf", "draw-bar" )

   current_formats.clear()



####

# Comparison of binary matrices
@@ -654,7 +693,7 @@ def symmetric_matrices_comparison( df, formats, head_size = 10 ): 
####

# Comparison of speed-up w.r.t. LightSpMV

def csr_light_speedup_comparison( df, head_size=10 ):

   format = 'CSR< Light >'

   format = 'CSR< Light > Automatic Light'

   print( f"Writing comparison of speed-up of CSR Light compared to LightSPMV" )

   df['tmp'] = df[(format, 'GPU','bandwidth')]

   filtered_df=df.dropna(subset=[('tmp','','','')])
@@ -717,7 +756,7 @@ formats.append('TNL Best') 
multicolumns, df_data = get_multiindex( input_df, formats )



print( "Converting data..." )

result = convert_data_frame( input_df, multicolumns, df_data, 0, 10000 )

result = convert_data_frame( input_df, multicolumns, df_data, 0, 200 )

compute_speedup( result, formats )



result.replace( to_replace=' ',value=np.nan,inplace=True)