Commit 1f3e9727 authored by Tomáš Oberhuber's avatar Tomáš Oberhuber Committed by Jakub Klinkovský
Browse files

Added CSR speedup on CPU into skript for processing of SpMV benchmark results.

parent 546a69d0

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

+104 −46
Original line number Diff line number Diff line
@@ -155,15 +155,20 @@ def convert_data_frame( input_df, multicolumns, df_data, begin_idx = 0, end_idx 
####

# Compute speed-up of particular formats compared to Cusparse on GPU and CSR on CPU

def compute_cusparse_speedup( df, formats ):

   for device in [ 'CPU', 'GPU' ]:

      for format in formats:

         if not format in [ 'cusparse', 'CSR' ]:

            print( 'Adding speed-up for ', format )

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

            try:

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

            except:

               continue

            cusparse_bdw_list = df[('cusparse','GPU','bandwidth')]

            csr_bdw_list = df[('CSR','CPU','bandwidth')]

            cusparse_speedup_list = []

            csr_speedup_list = []

            for( format_bdw, cusparse_bdw, csr_bdw ) in zip( format_bdw_list, cusparse_bdw_list,csr_bdw_list ):

               if( device == 'GPU' ):

                  try:

                     cusparse_speedup_list.append( format_bdw / cusparse_bdw )

                  except:
@@ -172,8 +177,9 @@ def compute_cusparse_speedup( df, formats ): 
                  csr_speedup_list.append( format_bdw / csr_bdw )

               except:

                  csr_speedup_list.append(float('nan'))

            if( device == 'GPU' ):

               df[(format,'GPU','speed-up','cusparse')] = cusparse_speedup_list

         df[(format,'GPU','speed-up','CSR CPU')] = csr_speedup_list

            df[(format,device,'speed-up','CSR CPU')] = csr_speedup_list



####

# Compute speedup of Light CSR
@@ -359,20 +365,22 @@ def cusparse_comparison( df, formats, head_size=10 ): 
def csr_comparison( df, formats, head_size=10 ):

   if not os.path.exists("CSR-bw"):

      os.mkdir("CSR-bw")

   for device in [ 'CPU', 'GPU' ]:

      for format in formats:

         if not format in ['cusparse','CSR']:

            print( f"Writing comparison of {format} and CSR on CPU" )

         ascend_df = df.copy()

         df.sort_values(by=[(format,'GPU','bandwidth')],inplace=True,ascending=False)

         ascend_df.sort_values(by=[(format,'GPU','bandwidth')],inplace=True,ascending=True)

            try:

               df.sort_values(by=[(format,device,'bandwidth')],inplace=True,ascending=False)

            except:

               continue

            fig, axs = plt.subplots( 2, 1 )

         t = np.arange(df[(format,'GPU','bandwidth')].size )

         axs[0].plot( t, df[(format,'GPU','bandwidth')], '-o', ms=1, lw=1 )

            t = np.arange(df[(format,device,'bandwidth')].size )

            axs[0].plot( t, df[(format,device,'bandwidth')], '-o', ms=1, lw=1 )

            axs[0].plot( t, df[('CSR','CPU','bandwidth')], '-o', ms=1, lw=1 )

            axs[0].legend( [ latexFormatName(format), 'CSR on CPU' ], loc='upper right' )

            axs[0].set_ylabel( 'Bandwidth in GB/sec' )

            axs[1].set_yscale( 'log' )

         axs[1].plot( t, result[(format,'GPU','bandwidth')], '-o', ms=1, lw=1 )

            axs[1].plot( t, result[(format,device,'bandwidth')], '-o', ms=1, lw=1 )

            axs[1].plot( t, result[('CSR','CPU','bandwidth')], '-o', ms=1, lw=1 )

            axs[1].legend( [ latexFormatName(format), 'CSR on CPU' ], loc='lower left' )

            axs[1].set_xlabel( f"Matrix ID - sorted w.r.t. {latexFormatName(format)} performance" )
@@ -381,13 +389,13 @@ def csr_comparison( df, formats, head_size=10 ): 
               "text.usetex": True,

               "font.family": "sans-serif",

               "font.sans-serif": ["Helvetica"]})

         plt.savefig( f"CSR-bw/{format}.pdf")

            plt.savefig( f"CSR-bw/{format}-{device}.pdf")

            plt.close(fig)

            copy_df = df.copy()

            for f in formats:

               if not f in ['cusparse','CSR',format]:

                  copy_df.drop( labels=f, axis='columns', level=0, inplace=True )

         copy_df.to_html( f"CSR-bw/{format}.html" )

            copy_df.to_html( f"CSR-bw/{format}-{device}.html" )



####

# Comparison of Legacy formats
@@ -430,6 +438,55 @@ def legacy_formats_comparison( df, formats, head_size=10 ): 
               copy_df.drop( labels=f, axis='columns', level=0, inplace=True )

         copy_df.to_html( f"Legacy-bw/{format}.html" )



####

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

def csr_speedup_comparison( df, formats, head_size=10 ):

   if not os.path.exists("CSR-speed-up"):

      os.mkdir("CSR-speed-up")

   for device in ['CPU', 'GPU']:

      profiles = {}

      for format in formats:

         if not format in ['cusparse','CSR']:

            print( f"Writing comparison of speed-up of {format} compared to CSR" )

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

            filtered_df=df.dropna(subset=[('tmp','','','')])

            try:

               filtered_df.sort_values(by=[(format,device,'speed-up','CSR CPU')],inplace=True,ascending=False)

            except:

               continue

            profiles[format] = filtered_df[(format,device,'speed-up','CSR CPU')].copy()

            fig, axs = plt.subplots( 1, 1, figsize=(6,4) )

            size = len(filtered_df[(format,device,'speed-up','CSR CPU')].index)

            t = np.arange( size )

            bar = np.full( size, 1 )

            axs.plot( t, filtered_df[(format,device,'speed-up','CSR CPU')], '-o', ms=1, lw=1 )

            axs.plot( t, bar, '-', ms=1, lw=1 )

            axs.legend( [ latexFormatName(format), 'CSR CPU' ], loc='upper right' )

            axs.set_ylabel( 'Speedup' )

            axs.set_xlabel( f"Matrix ID - sorted w.r.t. {latexFormatName(format)} speed-up" )

            plt.rcParams.update({

               "text.usetex": True,

               "font.family": "sans-serif",

               "font.sans-serif": ["Helvetica"]})

            plt.savefig( f"CSR-speed-up/{format}.pdf")

            plt.close(fig)



            fig, axs = plt.subplots( 1, 1, figsize=(6,4) )

            axs.set_yscale( 'log' )

            axs.plot( t, filtered_df[(format,device,'speed-up','CSR CPU')], '-o', ms=1, lw=1 )

            axs.plot( t, bar, '-', ms=1, lw=1 )

            axs.legend( [ latexFormatName(format), 'CSR' ], loc='lower left' )

            axs.set_xlabel( f"Matrix ID - sorted w.r.t. {latexFormatName(format)} speed-up" )

            axs.set_ylabel( 'Speedup' )

            plt.savefig( f"CSR-speed-up/{format}-{device}-log.pdf")

            plt.close(fig)

            copy_df = df.copy()

            for f in formats:

               if not f in ['cusparse','CSR',format]:

                  copy_df.drop( labels=f, axis='columns', level=0, inplace=True )

            copy_df.to_html( f"CSR-speed-up/{format}-{device}.html" )





####

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

def cusparse_speedup_comparison( df, formats, head_size=10 ):
@@ -685,6 +742,7 @@ def processDf( df, formats, head_size = 10 ): 
   cusparse_comparison( df, formats, head_size )

   csr_comparison( df, formats, head_size )

   legacy_formats_comparison( df, formats, head_size )

   csr_speedup_comparison( df, formats, head_size )

   cusparse_speedup_comparison( df, formats, head_size )

   binary_matrices_comparison( df, formats, head_size )

   symmetric_matrices_comparison( df, formats, head_size )