Merge branch 'DSP_varying' of git.uwaterloo.ca:watcag-public/fpga-syspart into DSP_varying

optimization_algo/approaches/sq_approach_faster.py

@@ -35,7 +35,7 @@ targets = [
 ]
 
 seedings = [
-    'allzeros', 'allzeros'
+    'allzeros', 'optimised'
 ]
 
 MAX_TRIAL = 20
@@ -94,7 +94,7 @@ if __name__ == "__main__":
 
     pool = Pool(processes = cpu_count() - 2)
     for result in pool.imap_unordered(trial, approaches):
-        with open(pc.RESULT_CSV_PATH+'cma_logmore_sq_full_evo.csv', 'a') as csvFile:
+        with open(pc.RESULT_CSV_PATH+'cma_logmore_sq_full_evo_2.csv', 'a') as csvFile:
             for evo in result:
                 writer = csv.writer(csvFile, delimiter=',', lineterminator="\n")
                 writer.writerow(evo)

optimization_algo/rScripts/square-vs-rect.r

@@ -2,7 +2,7 @@ library(ggplot2)
 library(scales)
 
 ps=6
-ls=2
+ls=1
 ats=25
 ts=25
 
@@ -11,7 +11,7 @@ ts=25
 pdf(file="square_vs_rect.pdf", height=9, width=15)
 
 sq_data <- read.csv("../resulting_csv/cma_logmore_sq_full_evo.csv", header=TRUE, sep=",")
-sq_data_subset <- subset(sq_data, feasable == 1 & target=="DRAM_cycle" & seeding_type=="optimised")
+sq_data_subset <- subset(sq_data, feasable == 1 & target=="DRAM_cycle" & seeding_type=="allzeros")
 
 data <- read.csv("../resulting_csv/cma.csv", header=TRUE, sep=",")
 data_subset <- subset(data, feasable == 1 & target=="DRAM_cycle" & seeding_type=="optimised")
@@ -25,12 +25,12 @@ names(column_data) <- col_headings
 
 for (topo in topo_unique) {
     for (part in partition_unique) {
-        sq_data_uni = subset(sq_data_subset, topology==topo & partitions==part & res_unit==17280)
+        sq_data_uni = subset(sq_data_subset, topology==topo & partitions==part & res_unit==17280 & popsize==500)
         data_uni = subset(data_subset, topology==topo & partitions==part)
 
         if (dim(data_uni)[1]!=0 && dim(sq_data_uni)[1]!=0) {
             sq_max_evo = max(sq_data_uni$evo_counter)
-            sq_row = which(sq_data_uni$evo_counter==sq_max_evo)
+            sq_row = which(sq_data_uni$evo_counter==sq_max_evo)[1]
 
             max_evo = max(data_uni$evo_counter)
             row = which(data_uni$evo_counter==max_evo)