@@ -83,26 +83,31 @@ def spatial_report(filepath):
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fig ,ax1 = plt .subplots ()
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loop_k = np .arange (16 )+ 1
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maker = ['v' ,'D' ,'o' ]
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- for i , r in enumerate (plot_res .keys ()):
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- y = plot_res [r ][1 :]
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- ax1 .plot (loop_k , y , maker [i ], ls = '-' , ms = 8 , color = cl [i ],linewidth = 3 )
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- size = 6
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- plt .xticks (fontsize = 16 )
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- plt .yticks (fontsize = 16 )
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- ax1 .set_ylabel ('Normalized Resource Usages' ,fontsize = 18 )
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- ax1 .set_xlabel ('Unrolling Factor' ,fontsize = 18 )
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- PERF_RESOURCES_NAME = ['DSP used' , 'BRAM used' ,'LUT used' ]
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- ax1 .legend (PERF_RESOURCES_NAME ,prop = {'size' : 16 })
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+ # for i, r in enumerate(plot_res.keys()):
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+ # y = plot_res[r][1:]
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+ # ax1.plot(loop_k, y, maker[i], ls='-', ms=8, color = cl[i],linewidth=3 )
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+ # size = 6
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+ # plt.xticks(fontsize = 16)
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+ # plt.yticks(fontsize = 16)
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+ # ax1.set_ylabel('Normalized Resource Usages',fontsize= 18)
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+ # ax1.set_xlabel('Unrolling Factor',fontsize = 18)
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+ # PERF_RESOURCES_NAME = ['DSP used', 'BRAM used','LUT used']
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+ # ax1.legend(PERF_RESOURCES_NAME,prop={'size': 16})
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- # marker = {'input_matrix_a':'s','input_matrix_b':'+'}
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- #leg2 = ['input matrix a','input matrix b']
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+ marker = {'input_matrix_a' :'s' ,'input_matrix_b' :'+' }
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+ leg1 = ['input matrix a' ,'input matrix b' ]
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#ax2 = ax1.twinx()
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- #for i, sram in enumerate(marker):
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- # df = pd.read_csv(sram+'.csv')
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- # bank = [ eval(re.sub("\s+", ",", n.strip()))[0] for n in df[' N']]
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- # ax2.plot(loop_k,bank, marker[sram], color=cl[i+1])
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- #ax2.legend(leg2,loc=4)
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- #ax2.set_ylabel('Banking Decisions')
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-
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- plt .savefig ('paper-normalized.pdf' , bbox_inches = 'tight' )
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+ ms = [8 ,12 ]
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+ for i , sram in enumerate (marker ):
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+ df = pd .read_csv (sram + '.csv' )
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+ bank = [ eval (re .sub ("\s+" , "," , n .strip ()))[0 ] for n in df [' N' ]]
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+ ax1 .plot (loop_k ,bank , marker [sram ], color = cl [i ], ms = ms [i ], mew = 3 )
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+ ax1 .legend (leg1 ,loc = 4 )
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+ ax1 .set_ylabel ('Banking Decisions' , fontsize = 18 )
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+ ax1 .set_xlabel ('Unrolling Factor' ,fontsize = 18 )
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+ plt .xticks (fontsize = 16 )
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+ plt .yticks (fontsize = 16 )
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+ #PERF_RESOURCES_NAME = ['DSP used', 'BRAM used','LUT used']
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+ #ax1.legend(PERF_RESOURCES_NAME,prop={'size': 16})
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+ plt .savefig ('paper-banking.pdf' , bbox_inches = 'tight' )
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plt .show ()
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