further experimentations

adapt-step.jl

@@ -7,12 +7,12 @@ module AdaptStep
   # Adaptive step size
   function adapt_step(H, x, t, step, m)
     Δ = norm([h(variables(H(t))=>x) for h in H(t-step)])
-    if Δ > 1e-8
+    if Δ > 1e-10
       step = 0.5 * step
       m = 0
     else
       m+=1
-      if (m == 5) && (step < 0.05)
+      if (m == 4)
         step = 2 * step
         m = 0
       end

report/report.tex

@@ -221,7 +221,8 @@ For sake of visualization, a set of smaller tests was run, in addition to the pa
 macro from the \textit{Threads.jl} package on the root tracking \texttt{for} loop in the file \hyperref[sec:listing]{solve.jl}); however the multi-threaded runs didn't improve the
 performance on these smaller systems, as the overhead of the multi-threading was too big compared to the actual computation time.
 
-% TODO: introduce conclusions about parallelization
+\ldots
+perhaps because of our choice of predictor-corrector which could be unsuitable for larger systems.
 
 The Julia implementation for the tests described above can be found in Appendix \hyperref[sec:listing]{B}.
 

solve.jl

@@ -24,9 +24,9 @@ end
   using .AdaptStep
 end
 
-@everywhere function compute_root(H, r, maxsteps=1000)
+@everywhere function compute_root(H, r, maxsteps=200)
   t = 1.0
-  step_size = 0.01
+  step_size = 0.001
   x0 = r
   m = 0
   steps = 0