Merge remote-tracking branch 'origin/development' into development

Author: gjbex

source-code/performance/README.md

@@ -8,3 +8,5 @@ These are some resources about general performance considerations.
 1. `number_puzzle.ipynb`: jupyter notebbook solving a number puzzle
    in a variety of ways, shwoing some aspects of performance
    optimization.
+1. `cellular_automata`: some illustrations of profiling and performance
+   optimizations.

source-code/performance/cellular_automata/Makefile

@@ -0,0 +1,11 @@
+CXX=g++
+CXXFLAGS=-O3 -std=c++17 -Wall -Wextra -Wpedantic
+
+all: cellular_automaton.exe
+
+cellular_automaton.exe: automaton_runner.o main.o
+	g++ $(CXXFLAGS) -o $@ $^
+
+clean:
+	$(RM) $(wildcard *.o) $(wildcard *.exe)
+	$(RM) core

source-code/performance/cellular_automata/README.md

@@ -0,0 +1,14 @@
+# Cellular automata
+
+Performance of various implemenations of cellular automata.
+
+## What is it?
+
+1. `cellular_automaton.py`: Python script to run from the command line.
+2. C++ implementation
+  a. `automaton_runner.h`: automaton runner class definition.
+  a. `automaton_runner.cpp`: automaton runner method definitions.
+  a. `main.cpp`: C++ application to run cellular automata.
+  a. `Makefile`: make file to build the C++ application.
+3. `cellular_automaton.ipynb`: Jupyter notebook comparing various
+  implementations.

source-code/performance/cellular_automata/automaton_runner.cpp

@@ -0,0 +1,35 @@
+#include "automaton_runner.h"
+
+AutomatonRunner::AutomatonRunner(uint8_t rule_nr) {
+    for (uint8_t i = 0; i < rules.size(); ++i) {
+        rules[i] = rule_nr % 2;
+        rule_nr /= 2;
+    }
+}
+
+Automaton AutomatonRunner::next_generation(const Automaton& automaton) {
+    uint8_t idx;
+    size_t nr_cells {automaton.size()};
+    Automaton ng_automaton(nr_cells);
+    // first cell
+    idx = automaton[nr_cells - 1] << 2 | automaton[0] << 1 | automaton[1];
+    ng_automaton[0] = rules[idx];
+    // second to one before last cell
+    for (size_t cell_nr = 1; cell_nr < nr_cells - 1; ++cell_nr) {
+        idx = automaton[cell_nr - 1] << 2 | automaton[cell_nr] << 1 | automaton[cell_nr + 1];
+        ng_automaton[cell_nr] = rules[idx];
+    }
+    // last cell
+    idx = automaton[nr_cells - 2] << 2 | automaton[nr_cells - 1] << 1 | automaton[0];
+    ng_automaton[nr_cells - 1] = rules[idx];
+    return ng_automaton;
+}
+
+void AutomatonRunner::evolve(Automaton& automaton, const size_t nr_generations,
+                             GenerationHandler handler) {
+    if (!handler(automaton)) return;
+    for (size_t gen_nr = 0; gen_nr < nr_generations; ++gen_nr) {
+        automaton  = next_generation(automaton);
+        if (!handler(automaton)) return;
+    }
+}

source-code/performance/cellular_automata/automaton_runner.h

@@ -0,0 +1,22 @@
+#ifndef AUTOMATON_RUNNER_HDR
+#define AUTOMATON_RUNNER_HDR
+
+#include <array>
+#include <valarray>
+#include <functional>
+
+using Rules = std::array<uint8_t, 8>;
+using Automaton = std::valarray<uint8_t>;
+using GenerationHandler = std::function<bool(const Automaton&)>;
+
+class AutomatonRunner {
+    private:
+        Rules rules;
+        Automaton next_generation(const Automaton& automaton);
+    public:
+        AutomatonRunner(uint8_t rule_nr);
+        void evolve(Automaton& automaton, const size_t nr_generations,
+                    GenerationHandler handler);
+};
+
+#endif