finalize plotter script and add timing results

qdp_project/plotter.py

@@ -5,8 +5,10 @@ import seaborn as sns
 import matplotlib.pyplot as plt
 
 output_path = "./plots"
-prefetch_result = "./evaluation-results/qdp-xeonmax-prefetch-tca2-tcb1-tcj1-tmul8-wl4294967296-cs16777216.csv"
-dram_result = "./evaluation-results/qdp-xeonmax-dram-tca2-tcb0-tcj1-tmul8-wl4294967296-cs2097152.csv"
+hbm_result = "./evaluation-results/baseline/current-hbm/qdp-xeonmax-hbm-tca2-tcb0-tcj1-tmul16-wl4294967296-cs2097152.csv"
+dram_result = "./evaluation-results/baseline/current-dram/qdp-xeonmax-dram-tca2-tcb0-tcj1-tmul16-wl4294967296-cs2097152.csv"
+prefetch_result = "./evaluation-results/outofcacheallocation/qdp-xeonmax-prefetch-tca2-tcb1-tcj1-tmul16-wl4294967296-cs8388608.csv"
+distprefetch_result = "./evaluation-results/distprefetch/qdp-xeonmax-distprefetch-tca1-tcb1-tcj1-tmul32-wl4294967296-cs8388608.csv"
 
 tt_name = "rt-ns"
 function_names = [ "scana-run", "scanb-run", "aggrj-run" ]
@@ -14,30 +16,26 @@ fn_nice = [ "Scan A, Filter", "Scan B, Prefetch", "Aggregate, Project + Sum" ]
 
 def read_timings_from_csv(fname) -> tuple[list[float], list[str]]:
     t = {}
-    total_time = 0
 
-    # Read data from CSV file
+    row_count = 0
+    
     with open(fname, newline='') as csvfile:
         reader = csv.DictReader(csvfile, delimiter=';')
         for row in reader:
-            total_time += int(row[tt_name])
+            row_count = row_count + 1
             for i in range(len(function_names)):
                 t[fn_nice[i]] = t.get(fn_nice[i], 0) + int(row[function_names[i]])
 
-    t = {key: value * 100 / total_time for key, value in t.items() if value != 0}
-
-    total = sum(list(t.values()))
-    if total < 100.0:
-        t["Waiting / Other"] = 100.0 - total
+    t = {key: value / (1000 * 1000 * row_count) for key, value in t.items() if value != 0}
 
     return list(t.values()), list(t.keys())
 
 
 def get_data_prefetch_cache_access() -> tuple[list[float], list[str]]:
-    total = 0.3
-    data = [ 0.07, 0.19, 0.04 ]
+    total = 0.47
+    data = [ 0.01, 0.01, 0.04, 0.42 ]
     data = [ x * 100 / total for x in data ]
-    keys = ["numa_alloc_onnode", "dml::make_mem_move_task", "dml::hardware_device::submit"]
+    keys = ["Cache::GetCacheNode", "Cache::Access Itself", "dml::hardware_device::submit", "dml::make_mem_move_task (operator new)"]
 
     return data,keys
 
@@ -45,13 +43,13 @@ def get_data_prefetch_total() -> tuple[list[float], list[str]]:
     return read_timings_from_csv(prefetch_result)
 
 def get_data_dram_total() -> tuple[list[float], list[str]]:
-    return read_timings_from_csv(dram_result)
+    return 
 
 # loops over all possible configuration combinations and calls
 # process_file_to_dataset for them in order to build a dataframe
 # which is then displayed and saved
-def main(data: tuple[list[float], list[str]], fname):
-    palette_color = sns.color_palette('mako') 
+def main(data: tuple[list[float], list[str]], fname, unit):
+    palette_color = sns.color_palette('mako_r') 
     fig, ax = plt.subplots(figsize=(6, 3), subplot_kw=dict(aspect="equal"))
 
     wedges, texts = ax.pie(data[0], wedgeprops=dict(width=0.5), startangle=-40, colors=palette_color)
@@ -66,12 +64,14 @@ def main(data: tuple[list[float], list[str]], fname):
         horizontalalignment = {-1: "right", 1: "left"}[int(np.sign(x))]
         connectionstyle = f"angle,angleA=0,angleB={ang}"
         kw["arrowprops"].update({"connectionstyle": connectionstyle})
-        ax.annotate(f"{data[1][i]} - {data[0][i]:2.1f}%", xy=(x, y), xytext=(1.35*np.sign(x), 1.4*y), horizontalalignment=horizontalalignment, **kw)    
+        ax.annotate(f"{data[1][i]} - {data[0][i]:2.2f} {unit}", xy=(x, y), xytext=(1.35*np.sign(x), 1.4*y), horizontalalignment=horizontalalignment, **kw)    
     
     fig.savefig(os.path.join(output_path, fname), bbox_inches='tight')
 
 
 if __name__ == "__main__":
-    main(get_data_prefetch_cache_access(), "plot-timing-prefetch-cacheaccess.pdf")
-    main(get_data_prefetch_total(), "plot-timing-prefetch-totalexec.pdf")
-    main(get_data_dram_total(), "plot-timing-dram-totalexec.pdf")
+    main(get_data_prefetch_cache_access(), "plot-timing-cacheaccess.pdf", "%")
+    main(read_timings_from_csv(prefetch_result), "plot-timing-prefetch.pdf", "ms")
+    main(read_timings_from_csv(distprefetch_result), "plot-timing-distprefetch.pdf", "ms")
+    main(read_timings_from_csv(dram_result), "plot-timing-dram.pdf", "ms")
+    main(read_timings_from_csv(hbm_result), "plot-timing-hbm.pdf", "ms")