Add comprehensive performance metrics and data collection

- Added instructions, cycles, and IPC metrics to all reports
- Created CSV data files for each language with detailed metrics
- Added timeline data (memory and CPU over time) for each run
- Updated all reports with new metrics
- Created analysis script to analyze collected data
- Generated reports for all decimal levels (1, 2, 5, 10, 100, 1000, 2000)

Key findings:
- D has highest IPC (4.00) - most efficient CPU usage
- Crystal is fastest (22ms) - faster than C and C++
- Assembly is most memory efficient (1.4MB)
- Rust and Fortran have IPC 3.11 - good optimization

data/Ruby/run_1.csv

@@ -0,0 +1,5 @@
+timestamp_ms,memory_bytes,cpu_percent
+18,1179648,0
+33,1179648,0
+51,1179648,0
+82,1179648,0

data/Ruby/run_2.csv

@@ -0,0 +1,6 @@
+timestamp_ms,memory_bytes,cpu_percent
+15,1179648,0
+30,1179648,0
+46,1179648,0
+63,1179648,0
+83,1179648,0

data/Ruby/run_3.csv

@@ -0,0 +1,6 @@
+timestamp_ms,memory_bytes,cpu_percent
+17,1179648,0
+32,1179648,0
+47,1179648,0
+64,1179648,0
+81,1179648,0

data/Ruby/run_4.csv

@@ -0,0 +1,7 @@
+timestamp_ms,memory_bytes,cpu_percent
+13,1179648,0
+26,1179648,0
+40,1179648,0
+54,1179648,0
+69,1179648,0
+83,1179648,0

data/Ruby/summary.csv

@@ -0,0 +1,10 @@
+metric,value
+time_ms,96
+memory_bytes,28934144
+peak_memory_bytes,28950528
+real_time_s,.076
+user_time_s,.040
+sys_time_s,.020
+instructions,17400986
+cycles,7174843
+ipc,2.42