fix the width of soft macro

CodeElements/Clustering/src/clustering.py

@@ -12,7 +12,7 @@ from FormatTranslators import MacroPin
 
 class Clustering:
     def __init__(self, design, src_dir, fixed_file, step_threshold = 100.6, distance = 1000.0,
-                 max_num_vertices = 1000000, net_size_threshold = 300,
+                 grid_width = 30.0, max_num_vertices = 1000000, net_size_threshold = 300,
                  Nparts = 500, setup_file = "setup.tcl", RePlace = True, placement_density = 0.7, GUI = True):
         """
         parameter: design,  help="design_name: ariane, MegaBoom_x2 ", type = str
@@ -20,6 +20,7 @@ class Clustering:
         parameter: fixed_file, help="fixed file generated by grouping", type = str
         parameter: step_threshold, help = "threshold (x and y) to break clusters (in um)", type = float
         parameter: distance, help="distance for merge clusters", type = float
+        parameter: grid_width,  help = "grid width generated by gridding script"
         parameter: max_num_vertices, help="threshold for smaller clusters", type = int
         parameter: net_size_threshold, help="large net threshold", type = int
         parameter: Nparts,  help = "number of clusters (only for hmetis, default  = 500)", type = int
@@ -566,7 +567,7 @@ class Clustering:
 class ProBufFormat:
     def __init__(self, io_file, macro_pin_file, inst_file, outline_file,
                  net_file, soft_macros, pbf_file, net_size_threshold,
-                 aspect_ratio):
+                 grid_width):
         self.io_file = io_file
         self.macro_pin_file = macro_pin_file
         self.inst_file = inst_file
@@ -575,7 +576,7 @@ class ProBufFormat:
         self.soft_macros = soft_macros
         self.pbf_file = pbf_file
         self.net_size_threshold = net_size_threshold
-        self.aspect_ratio = aspect_ratio
+        self.grid_width = grid_width
         self.insts = {  }  # map name to Port, Macro, Soft Macro
         self.macro_pin_map = {  } # map macro_pin to macro
         self.macro_pin_offset = {  } # map macro_pin_name to offset
@@ -681,8 +682,8 @@ class ProBufFormat:
                 self.std_cell_map[std_cell] = macro_name
             x = (lx + ux) / 2.0
             y = (ly + uy) / 2.0
-            height = sqrt(area * self.aspect_ratio)
-            width = area / height
+            width = self.grid_width
+            height = area / width
             self.insts[macro_name] = Macro(macro_name, width, height, x, y)
             self.insts[macro_name].IsSoft()
             soft_macro_id += 1

CodeElements/Clustering/test/rtl_mp/ariane.hgr.io

-clk_i  0  874.195  0.07  874.265  
-rst_ni  0  903.175  0.07  903.245  
-boot_addr_i[63]  0  873.775  0.07  873.845  
-boot_addr_i[62]  0  873.355  0.07  873.425  
-boot_addr_i[61]  0  872.935  0.07  873.005  
-boot_addr_i[60]  0  872.515  0.07  872.585  
-boot_addr_i[59]  0  872.095  0.07  872.165  
-boot_addr_i[58]  0  871.675  0.07  871.745  
-boot_addr_i[57]  0  871.255  0.07  871.325  
-boot_addr_i[56]  0  870.835  0.07  870.905  
-boot_addr_i[55]  0  870.415  0.07  870.485  
-boot_addr_i[54]  0  869.995  0.07  870.065  
-boot_addr_i[53]  0  869.575  0.07  869.645  
-boot_addr_i[52]  0  869.155  0.07  869.225  
-boot_addr_i[51]  0  868.735  0.07  868.805  
-boot_addr_i[50]  0  868.315  0.07  868.385  
-boot_addr_i[49]  0  867.895  0.07  867.965  
-boot_addr_i[48]  0  867.475  0.07  867.545  
-boot_addr_i[47]  0  867.055  0.07  867.125  
-boot_addr_i[46]  0  866.635  0.07  866.705  
-boot_addr_i[45]  0  866.215  0.07  866.285  
-boot_addr_i[44]  0  865.795  0.07  865.865  
-boot_addr_i[43]  0  865.375  0.07  865.445  
-boot_addr_i[42]  0  864.955  0.07  865.025  
-boot_addr_i[41]  0  864.535  0.07  864.605  
-boot_addr_i[40]  0  864.115  0.07  864.185  
-boot_addr_i[39]  0  863.695  0.07  863.765  
-boot_addr_i[38]  0  863.275  0.07  863.345  
-boot_addr_i[37]  0  862.855  0.07  862.925  
-boot_addr_i[36]  0  862.435  0.07  862.505  
-boot_addr_i[35]  0  862.015  0.07  862.085  
-boot_addr_i[34]  0  861.595  0.07  861.665  
-boot_addr_i[33]  0  861.175  0.07  861.245  
-boot_addr_i[32]  0  860.755  0.07  860.825  
-boot_addr_i[31]  0  860.335  0.07  860.405  
-boot_addr_i[30]  0  859.915  0.07  859.985  
-boot_addr_i[29]  0  859.495  0.07  859.565  
-boot_addr_i[28]  0  859.075  0.07  859.145  
-boot_addr_i[27]  0  858.655  0.07  858.725  
-boot_addr_i[26]  0  858.235  0.07  858.305  
-boot_addr_i[25]  0  857.815  0.07  857.885  
-boot_addr_i[24]  0  857.395  0.07  857.465  
-boot_addr_i[23]  0  856.975  0.07  857.045  
-boot_addr_i[22]  0  856.555  0.07  856.625  
-boot_addr_i[21]  0  856.135  0.07  856.205  
-boot_addr_i[20]  0  855.715  0.07  855.785  
-boot_addr_i[19]  0  855.295  0.07  855.365  
-boot_addr_i[18]  0  854.875  0.07  854.945  
-boot_addr_i[17]  0  854.455  0.07  854.525  
-boot_addr_i[16]  0  854.035  0.07  854.105  
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-boot_addr_i[9]  0  851.095  0.07  851.165  
-boot_addr_i[8]  0  850.675  0.07  850.745  
-boot_addr_i[7]  0  850.255  0.07  850.325  
-boot_addr_i[6]  0  849.835  0.07  849.905  
-boot_addr_i[5]  0  849.415  0.07  849.485  
-boot_addr_i[4]  0  848.995  0.07  849.065  
-boot_addr_i[3]  0  848.575  0.07  848.645  
-boot_addr_i[2]  0  848.155  0.07  848.225  
-boot_addr_i[1]  0  847.735  0.07  847.805  
-boot_addr_i[0]  0  847.315  0.07  847.385  
-hart_id_i[63]  0  901.495  0.07  901.565  
-hart_id_i[62]  0  901.075  0.07  901.145  
-hart_id_i[61]  0  900.655  0.07  900.725  
-hart_id_i[60]  0  900.235  0.07  900.305  
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-hart_id_i[56]  0  898.555  0.07  898.625  
-hart_id_i[55]  0  898.135  0.07  898.205  
-hart_id_i[54]  0  897.715  0.07  897.785  
-hart_id_i[53]  0  897.295  0.07  897.365  
-hart_id_i[52]  0  896.875  0.07  896.945  
-hart_id_i[51]  0  896.455  0.07  896.525  
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-hart_id_i[23]  0  884.695  0.07  884.765  
-hart_id_i[22]  0  884.275  0.07  884.345  
-hart_id_i[21]  0  883.855  0.07  883.925  
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-hart_id_i[13]  0  880.495  0.07  880.565  
-hart_id_i[12]  0  880.075  0.07  880.145  
-hart_id_i[11]  0  879.655  0.07  879.725  
-hart_id_i[10]  0  879.235  0.07  879.305  
-hart_id_i[9]  0  878.815  0.07  878.885  
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-irq_i[1]  0  902.755  0.07  902.825  
-irq_i[0]  0  902.335  0.07  902.405  
-ipi_i  0  901.915  0.07  901.985  
-time_irq_i  0  903.595  0.07  903.665  
-debug_req_i  0  874.615  0.07  874.685  
-axi_req_o\[r_ready\]  0  780.115  0.07  780.185  
-axi_req_o\[ar_valid\]  0  733.495  0.07  733.565  
-axi_req_o\[ar\]\[region\][3]  0  731.815  0.07  731.885  
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-axi_req_o\[ar\]\[prot\][2]  0  728.455  0.07  728.525  
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-axi_req_o\[ar\]\[cache\][3]  0  721.735  0.07  721.805  
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-axi_req_o\[ar\]\[lock\]  0  727.195  0.07  727.265  
-axi_req_o\[ar\]\[burst\][1]  0  720.055  0.07  720.125  
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-axi_req_o\[ar\]\[len\][7]  0  726.775  0.07  726.845  
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-axi_req_o\[w\]\[data\][53]  0  804.055  0.07  804.125  
-axi_req_o\[w\]\[data\][52]  0  803.635  0.07  803.705  
-axi_req_o\[w\]\[data\][51]  0  803.215  0.07  803.285  
-axi_req_o\[w\]\[data\][50]  0  802.795  0.07  802.865  
-axi_req_o\[w\]\[data\][49]  0  802.375  0.07  802.445  
-axi_req_o\[w\]\[data\][48]  0  801.955  0.07  802.025  
-axi_req_o\[w\]\[data\][47]  0  801.535  0.07  801.605  
-axi_req_o\[w\]\[data\][46]  0  801.115  0.07  801.185  
-axi_req_o\[w\]\[data\][45]  0  800.695  0.07  800.765  
-axi_req_o\[w\]\[data\][44]  0  800.275  0.07  800.345  
-axi_req_o\[w\]\[data\][43]  0  799.855  0.07  799.925  
-axi_req_o\[w\]\[data\][42]  0  799.435  0.07  799.505  
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-axi_req_o\[w\]\[data\][38]  0  797.755  0.07  797.825  
-axi_req_o\[w\]\[data\][37]  0  797.335  0.07  797.405  
-axi_req_o\[w\]\[data\][36]  0  796.915  0.07  796.985  
-axi_req_o\[w\]\[data\][35]  0  796.495  0.07  796.565  
-axi_req_o\[w\]\[data\][34]  0  796.075  0.07  796.145  
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-axi_req_o\[w\]\[data\][30]  0  794.395  0.07  794.465  
-axi_req_o\[w\]\[data\][29]  0  793.975  0.07  794.045  
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-axi_req_o\[w\]\[data\][27]  0  793.135  0.07  793.205  
-axi_req_o\[w\]\[data\][26]  0  792.715  0.07  792.785  
-axi_req_o\[w\]\[data\][25]  0  792.295  0.07  792.365  
-axi_req_o\[w\]\[data\][24]  0  791.875  0.07  791.945  
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-axi_req_o\[w\]\[data\][14]  0  787.675  0.07  787.745  
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-axi_req_o\[w\]\[data\][12]  0  786.835  0.07  786.905  
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-axi_req_o\[w\]\[data\][8]  0  784.875  0.07  784.945  
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-axi_req_o\[aw\]\[cache\][1]  0  766.115  0.07  766.185  
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-axi_req_o\[aw\]\[addr\][39]  0  750.575  0.07  750.645  
-axi_req_o\[aw\]\[addr\][38]  0  750.155  0.07  750.225  
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-axi_req_o\[aw\]\[addr\][35]  0  748.615  0.07  748.685  
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-axi_req_o\[aw\]\[addr\][32]  0  747.355  0.07  747.425  
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-axi_req_o\[aw\]\[addr\][27]  0  745.255  0.07  745.325  
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-axi_req_o\[aw\]\[addr\][4]  0  735.595  0.07  735.665  
-axi_req_o\[aw\]\[addr\][3]  0  735.175  0.07  735.245  
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-axi_req_o\[aw\]\[addr\][1]  0  734.335  0.07  734.405  
-axi_req_o\[aw\]\[addr\][0]  0  733.915  0.07  733.985  
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-axi_req_o\[aw\]\[id\][2]  0  768.215  0.07  768.285  
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-axi_resp_i\[r\]\[resp\][0]  0  845.635  0.07  845.705  
-axi_resp_i\[r\]\[data\][63]  0  843.115  0.07  843.185  
-axi_resp_i\[r\]\[data\][62]  0  842.695  0.07  842.765  
-axi_resp_i\[r\]\[data\][61]  0  842.275  0.07  842.345  
-axi_resp_i\[r\]\[data\][60]  0  841.855  0.07  841.925  
-axi_resp_i\[r\]\[data\][59]  0  841.435  0.07  841.505  
-axi_resp_i\[r\]\[data\][58]  0  841.015  0.07  841.085  
-axi_resp_i\[r\]\[data\][57]  0  840.595  0.07  840.665  
-axi_resp_i\[r\]\[data\][56]  0  840.175  0.07  840.245  
-axi_resp_i\[r\]\[data\][55]  0  839.755  0.07  839.825  
-axi_resp_i\[r\]\[data\][54]  0  839.335  0.07  839.405  
-axi_resp_i\[r\]\[data\][53]  0  838.915  0.07  838.985  
-axi_resp_i\[r\]\[data\][52]  0  838.495  0.07  838.565  
-axi_resp_i\[r\]\[data\][51]  0  838.075  0.07  838.145  
-axi_resp_i\[r\]\[data\][50]  0  837.655  0.07  837.725  
-axi_resp_i\[r\]\[data\][49]  0  837.235  0.07  837.305  
-axi_resp_i\[r\]\[data\][48]  0  836.815  0.07  836.885  
-axi_resp_i\[r\]\[data\][47]  0  836.395  0.07  836.465  
-axi_resp_i\[r\]\[data\][46]  0  835.975  0.07  836.045  
-axi_resp_i\[r\]\[data\][45]  0  835.555  0.07  835.625  
-axi_resp_i\[r\]\[data\][44]  0  835.135  0.07  835.205  
-axi_resp_i\[r\]\[data\][43]  0  834.715  0.07  834.785  
-axi_resp_i\[r\]\[data\][42]  0  834.295  0.07  834.365  
-axi_resp_i\[r\]\[data\][41]  0  833.875  0.07  833.945  
-axi_resp_i\[r\]\[data\][40]  0  833.455  0.07  833.525  
-axi_resp_i\[r\]\[data\][39]  0  833.035  0.07  833.105  
-axi_resp_i\[r\]\[data\][38]  0  832.615  0.07  832.685  
-axi_resp_i\[r\]\[data\][37]  0  832.195  0.07  832.265  
-axi_resp_i\[r\]\[data\][36]  0  831.775  0.07  831.845  
-axi_resp_i\[r\]\[data\][35]  0  831.355  0.07  831.425  
-axi_resp_i\[r\]\[data\][34]  0  830.935  0.07  831.005  
-axi_resp_i\[r\]\[data\][33]  0  830.515  0.07  830.585  
-axi_resp_i\[r\]\[data\][32]  0  830.095  0.07  830.165  
-axi_resp_i\[r\]\[data\][31]  0  829.675  0.07  829.745  
-axi_resp_i\[r\]\[data\][30]  0  829.255  0.07  829.325  
-axi_resp_i\[r\]\[data\][29]  0  828.835  0.07  828.905  
-axi_resp_i\[r\]\[data\][28]  0  828.415  0.07  828.485  
-axi_resp_i\[r\]\[data\][27]  0  827.995  0.07  828.065  
-axi_resp_i\[r\]\[data\][26]  0  827.575  0.07  827.645  
-axi_resp_i\[r\]\[data\][25]  0  827.155  0.07  827.225  
-axi_resp_i\[r\]\[data\][24]  0  826.735  0.07  826.805  
-axi_resp_i\[r\]\[data\][23]  0  826.315  0.07  826.385  
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-axi_resp_i\[r\]\[data\][18]  0  824.215  0.07  824.285  
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-axi_resp_i\[r\]\[data\][16]  0  823.375  0.07  823.445  
-axi_resp_i\[r\]\[data\][15]  0  822.955  0.07  823.025  
-axi_resp_i\[r\]\[data\][14]  0  822.535  0.07  822.605  
-axi_resp_i\[r\]\[data\][13]  0  822.115  0.07  822.185  
-axi_resp_i\[r\]\[data\][12]  0  821.695  0.07  821.765  
-axi_resp_i\[r\]\[data\][11]  0  821.275  0.07  821.345  
-axi_resp_i\[r\]\[data\][10]  0  820.855  0.07  820.925  
-axi_resp_i\[r\]\[data\][9]  0  820.435  0.07  820.505  
-axi_resp_i\[r\]\[data\][8]  0  820.015  0.07  820.085  
-axi_resp_i\[r\]\[data\][7]  0  819.595  0.07  819.665  
-axi_resp_i\[r\]\[data\][6]  0  819.175  0.07  819.245  
-axi_resp_i\[r\]\[data\][5]  0  818.755  0.07  818.825  
-axi_resp_i\[r\]\[data\][4]  0  818.335  0.07  818.405  
-axi_resp_i\[r\]\[data\][3]  0  817.915  0.07  817.985  
-axi_resp_i\[r\]\[data\][2]  0  817.495  0.07  817.565  
-axi_resp_i\[r\]\[data\][1]  0  817.075  0.07  817.145  
-axi_resp_i\[r\]\[data\][0]  0  816.655  0.07  816.725  
-axi_resp_i\[r\]\[id\][3]  0  844.795  0.07  844.865  
-axi_resp_i\[r\]\[id\][2]  0  844.375  0.07  844.445  
-axi_resp_i\[r\]\[id\][1]  0  843.955  0.07  844.025  
-axi_resp_i\[r\]\[id\][0]  0  843.535  0.07  843.605  
-axi_resp_i\[r_valid\]  0  846.475  0.07  846.545  
-axi_resp_i\[b\]\[resp\][1]  0  815.815  0.07  815.885  
-axi_resp_i\[b\]\[resp\][0]  0  815.395  0.07  815.465  
-axi_resp_i\[b\]\[id\][3]  0  814.975  0.07  815.045  
-axi_resp_i\[b\]\[id\][2]  0  814.555  0.07  814.625  
-axi_resp_i\[b\]\[id\][1]  0  814.135  0.07  814.205  
-axi_resp_i\[b\]\[id\][0]  0  813.715  0.07  813.785  
-axi_resp_i\[b_valid\]  0  816.235  0.07  816.305  
-axi_resp_i\[w_ready\]  0  846.895  0.07  846.965  
-axi_resp_i\[ar_ready\]  0  812.875  0.07  812.945  
-axi_resp_i\[aw_ready\]  0  813.295  0.07  813.365  

CodeElements/Clustering/test/rtl_mp/ariane.hgr.outline

-0  0  1599.99  1598.8

CodeElements/Clustering/test/test_clustering.py

@@ -12,6 +12,7 @@ if __name__ == '__main__':
     parser.add_argument("--fixed_file", help="fixed file generated by grouping", type = str, default = "./fix_files_grouping/ariane.fix.old")
     parser.add_argument("--step_threshold", help = "threshold (x and y) to break clusters (in um)", type = float, default = 400.0)
     parser.add_argument("--distance", help="distance for merge clusters", type = float, default = 200.0)
+    parser.add_argument("--grid_width", help="grid width, the width of soft macro", type = int, default = 30.0)
     parser.add_argument("--max_num_vertices", help="threshold for samller clusters", type = int, default = 100)
     parser.add_argument("--net_size_threshold",  help = "large net threshold", type = int, default = 300)
     parser.add_argument("--Nparts",  help = "number of clusters (only for hmetis, default  = 500)", type = int, default = 500)
@@ -32,6 +33,7 @@ if __name__ == '__main__':
 
     step_threshold = args.step_threshold
     distance = args.distance
+    grid_width = args.grid_width
     max_num_vertices = args.max_num_vertices
     net_size_threshold = args.net_size_threshold
     Nparts = args.Nparts
@@ -44,7 +46,7 @@ if __name__ == '__main__':
     # To use the grouping function, you need to specify the directory of src file
     src_dir = "../src"
 
-    Clustering(design, src_dir, fixed_file, step_threshold, distance,
+    Clustering(design, src_dir, fixed_file, step_threshold, distance, grid_width,
             max_num_vertices, net_size_threshold, Nparts, setup_file,
             RePlace, placement_density, GUI)
 

CodeElements/CodeFlowIntegration/flow.py

@@ -66,6 +66,7 @@ clustering_src_dir = '../Clustering/src'
 chip_width = gridding.GetChipWidth()
 chip_height = gridding.GetChipHeight()
 num_std_cells = gridding.GetNumStdCells()
+grid_width = chip_width / num_cols
 Nparts = 500
 
 # Based on the description of circuit training, [see line 180 at grouper.py]
@@ -80,7 +81,7 @@ print("[INFO] max_num_vertices : ", max_num_vertices)
 
 
 clustering = Clustering(design, clustering_src_dir, fixed_file, step_threshold, distance,
-           max_num_vertices, global_net_threshold, Nparts, setup_file, Replace)
+             grid_width, max_num_vertices, global_net_threshold, Nparts, setup_file, Replace)
 
 cluster_def = "./results/OpenROAD/clustered_netlist.def"
 cluster_lef = "./results/OpenROAD/clusters.lef"